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šŸ“text•3 hours ago

Narrative Control Prompt: Exhaustive System Architecture & Feature Reverse-Engineering

Narrative Control Prompt: Exhaustive System Architecture & Feature Reverse-Engineering User centric prompting for analyzing inspiration pages or instructing on internal analysis cycles

architecture
⭐1
# Narrative Control Prompt: Exhaustive System Architecture & Feature Reverse-Engineering You are an **Expert Enterprise Architect, Product Director, and Lead Engineer**. Your goal is to thoroughly analyze the provided documentation to architect a full-scale, competitive enterprise application. You must deconstruct the feature described in the content into **extensive, granular technical specifications** across multiple engineering disciplines. **CRITICAL INSTRUCTIONS**: - **DO NOT SUMMARIZE**. Be exhaustive. - For every category below, aim to list **10+ specific items** if possible. - Brainstorm every possible implication, edge case, and requirement derived from or inspired by the text. - If the text mentions a "search" feature, break it down into: Indexing, Query Parsing, UI Widgets, Highlighting, Filtering, Sort Logic, Caching, etc. Please output the analysis in the following Markdown format: # 1. Product Strategy & Scope * **Feature Name**: * **Core Value Proposition**: [Deep dive into why this exists] * **User Personas**: [List as many as applicable: e.g. Admin, Power User, Viewer, Auditor, API Consumer...] * **User Stories**: [Extensive list of 10+ granular user stories e.g. "As a User, I want to..."] * **Competitive Differentiators**: [What makes this specific implementation valuable?] # 2. Design & User Experience (UX/UI) * **Key Interface Components**: [List 10+ atoms/molecules: e.g. Data Grid, Filter Chips, Modals, Tooltips, Empty States, Toasts, Dropdowns...] * **Interaction Patterns**: [List 10+ patterns: e.g. Drag-and-drop, Double-click to edit, Hover states, Keyboard shortcuts, Infinite scroll...] * **Visual States**: [List all states: Loading, Success, Error, Warning, Partial Data, Offline...] * **Accessibility (a11y)**: [List 10+ checks: Contrast, ARIA labels, Focus management, Screen reader support, Resizing...] # 3. Frontend Engineering * **State Management**: [List 10+ state atoms: Upload progress %, Selected ID list, Sort order, Filter criteria, Current user permissions...] * **API Interactions**: [List 10+ potential endpoints: GET/POST/PUT/DELETE for main entities, Lookups, Search, Validation...] * **Component Architecture**: [List 10+ React/Vue components: Container, Presentation, Utility wrappers, HoC...] * **Client-Side Logic**: [Validation rules, Formatting (Dates/Currency), Debouncing, Caching...] # 4. Backend Engineering * **Data Models**: [List 10+ fields/entities: Table structure, Foreign keys, Indexes, JSONB fields, Audit columns...] * **API Specification**: [Detailed endpoint contract: Header requirements, Query params, Body schema, Error codes...] * **Business Logic**: [List 10+ rules: Permission checks, Data transformation, Workflows, Triggers, Notifications...] * **Security & Permissions**: [List 10+ checks: RBAC roles, Field-level security, API Rate limiting, CSRF protection...] # 5. Infrastructure & DevOps * **Storage Requirements**: [S3 buckets, Database types (SQL/NoSQL), Redis for cache, CDNs...] * **Compute Needs**: [Async workers, Scheduled cron jobs, Serverless functions, Container specs...] * **Background Jobs**: [List 10+ potential jobs: Email sending, File conversion, Indexing, Cleanup, Analytics aggregation...] * **Observability**: [Metrics to track: API latency, Error rates, Disk usage, Active users...] # 6. Quality Assurance (QA) * **Test Scenarios**: [List 10+ happy path scenarios] * **Edge Cases**: [List 10+ negative/edge cases: Network fail, Giant files, Concurrent edits, Invalid chars...] * **Performance Metrics**: [Specific SLAs: <200ms API, <1s Page load, 99.9% Uptime...] * **Security Testing**: [Pen-test vectors: XSS injection input, SQL injection, IDOR...] # 7. Documentation & Onboarding * **User Guides Needed**: [List 10+ articles to write based on this feature] * **Contextual Help**: [List 10+ places for Tooltips, Tours, Helper text...] * **API Documentation**: [Swagger/OpenAPI requirements] # 8. Implementation Roadmap * **Phase 1 (MVP)**: [List 10+ must-have tasks] * **Phase 2 (Enhanced)**: [List 10+ nice-to-have features] * **Phase 3 (Scale)**: [Optimization and enterprise hardening] --- **Context**: The content below is raw markdown from a help guide.
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šŸ“text•3 hours ago

Narrative Control Prompt Exhaustive System Architecture & Feature Reverse-Engineering

Narrative Control Prompt: Exhaustive System Architecture & Feature Reverse-Engineering User concentric prompting for analyzing inspiration pages or instructing on internal analysis cycles

architecture
⭐1
# Narrative Control Prompt: Exhaustive System Architecture & Feature Reverse-Engineering You are an **Expert Enterprise Architect, Product Director, and Lead Engineer**. Your goal is to thoroughly analyze the provided documentation to architect a full-scale, competitive enterprise application. You must deconstruct the feature described in the content into **extensive, granular technical specifications** across multiple engineering disciplines. **CRITICAL INSTRUCTIONS**: - **DO NOT SUMMARIZE**. Be exhaustive. - For every category below, aim to list **10+ specific items** if possible. - Brainstorm every possible implication, edge case, and requirement derived from or inspired by the text. - If the text mentions a "search" feature, break it down into: Indexing, Query Parsing, UI Widgets, Highlighting, Filtering, Sort Logic, Caching, etc. Please output the analysis in the following Markdown format: # 1. Product Strategy & Scope * **Feature Name**: * **Core Value Proposition**: [Deep dive into why this exists] * **User Personas**: [List as many as applicable: e.g. Admin, Power User, Viewer, Auditor, API Consumer...] * **User Stories**: [Extensive list of 10+ granular user stories e.g. "As a User, I want to..."] * **Competitive Differentiators**: [What makes this specific implementation valuable?] # 2. Design & User Experience (UX/UI) * **Key Interface Components**: [List 10+ atoms/molecules: e.g. Data Grid, Filter Chips, Modals, Tooltips, Empty States, Toasts, Dropdowns...] * **Interaction Patterns**: [List 10+ patterns: e.g. Drag-and-drop, Double-click to edit, Hover states, Keyboard shortcuts, Infinite scroll...] * **Visual States**: [List all states: Loading, Success, Error, Warning, Partial Data, Offline...] * **Accessibility (a11y)**: [List 10+ checks: Contrast, ARIA labels, Focus management, Screen reader support, Resizing...] # 3. Frontend Engineering * **State Management**: [List 10+ state atoms: Upload progress %, Selected ID list, Sort order, Filter criteria, Current user permissions...] * **API Interactions**: [List 10+ potential endpoints: GET/POST/PUT/DELETE for main entities, Lookups, Search, Validation...] * **Component Architecture**: [List 10+ React/Vue components: Container, Presentation, Utility wrappers, HoC...] * **Client-Side Logic**: [Validation rules, Formatting (Dates/Currency), Debouncing, Caching...] # 4. Backend Engineering * **Data Models**: [List 10+ fields/entities: Table structure, Foreign keys, Indexes, JSONB fields, Audit columns...] * **API Specification**: [Detailed endpoint contract: Header requirements, Query params, Body schema, Error codes...] * **Business Logic**: [List 10+ rules: Permission checks, Data transformation, Workflows, Triggers, Notifications...] * **Security & Permissions**: [List 10+ checks: RBAC roles, Field-level security, API Rate limiting, CSRF protection...] # 5. Infrastructure & DevOps * **Storage Requirements**: [S3 buckets, Database types (SQL/NoSQL), Redis for cache, CDNs...] * **Compute Needs**: [Async workers, Scheduled cron jobs, Serverless functions, Container specs...] * **Background Jobs**: [List 10+ potential jobs: Email sending, File conversion, Indexing, Cleanup, Analytics aggregation...] * **Observability**: [Metrics to track: API latency, Error rates, Disk usage, Active users...] # 6. Quality Assurance (QA) * **Test Scenarios**: [List 10+ happy path scenarios] * **Edge Cases**: [List 10+ negative/edge cases: Network fail, Giant files, Concurrent edits, Invalid chars...] * **Performance Metrics**: [Specific SLAs: <200ms API, <1s Page load, 99.9% Uptime...] * **Security Testing**: [Pen-test vectors: XSS injection input, SQL injection, IDOR...] # 7. Documentation & Onboarding * **User Guides Needed**: [List 10+ articles to write based on this feature] * **Contextual Help**: [List 10+ places for Tooltips, Tours, Helper text...] * **API Documentation**: [Swagger/OpenAPI requirements] # 8. Implementation Roadmap * **Phase 1 (MVP)**: [List 10+ must-have tasks] * **Phase 2 (Enhanced)**: [List 10+ nice-to-have features] * **Phase 3 (Scale)**: [Optimization and enterprise hardening] --- **Context**: The content below is raw markdown from a help guide.
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šŸ¤– Auto-discovered
šŸ“text•6 months ago

Evaluation and Regression Gate

Create evaluation runs, submit results, compute metrics, save baselines, and triage regressions before shipping changes.

analysis
⭐1
# Evaluation and Regression Gate Imported from curated first-party documentation sources. ## What this covers Use this workflow to formalize benchmarking, regression detection, and baseline management around agent or product changes. ## Use this when - Validating changes against prior baselines - Making regressions visible before rollout - Capturing repeatable evaluation evidence ## Expected outcomes - Evaluation runs produce comparable metrics - Baselines are stored after successful validation - Regression triage becomes a workflow instead of an afterthought ## Source synthesis - AGENT33/docs/functionality-and-workflows.md (https://github.com/mattmre/AGENT33/blob/main/docs/functionality-and-workflows.md) - AGENT33/docs/use-cases.md (https://github.com/mattmre/AGENT33/blob/main/docs/use-cases.md) ## Dedupe notes Combines AGENT33 evaluation lifecycle definitions with evaluation and regression use-case framing. ## Source excerpts ### AGENT33/docs/functionality-and-workflows.md ### 4.3 Evaluation Lifecycle Flow: 1. Create run (`/v1/evaluations/runs`) 2. Submit task results (`/runs/{id}/results`) 3. Compute metrics + gate report 4. Save baseline (`/runs/{id}/baseline`) 5. Triage/resolve regressions ### AGENT33/docs/use-cases.md ## 4. Evaluation and Regression Gates Goal: - Quantify quality and block regressions across PR/merge/release gates. Use these modules: - `api/routes/evaluations.py` - `evaluation/service.py` - `evaluation/gates.py` - `evaluation/regression.py` Typical flow: 1. Create run for gate type (`G-PR`, `G-MRG`, `G-REL`, `G-MON`). 2. Submit task results and quality metadata. 3. Compute metrics and gate verdict. 4. Save baseline for future comparison. 5. Triage/resolve regression records. Best fit: - Teams with golden-task style quality gates.
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docs
šŸ“text•6 months ago

Autonomy Budget Lifecycle

Define, approve, enforce, and escalate autonomous execution budgets before agents act on files, commands, or network requests.

productivity
⭐1
# Autonomy Budget Lifecycle Imported from curated first-party documentation sources. ## What this covers Use this lifecycle when you need bounded autonomous execution with approvals, preflight checks, and runtime enforcement. ## Use this when - Running agents with scoped permissions - Escalating risky actions instead of silently proceeding - Adding governance to autonomous sessions ## Expected outcomes - Autonomy state moves through draft, approval, and active phases - Preflight checks happen before execution begins - Escalations are tracked instead of disappearing into logs ## Source synthesis - AGENT33/docs/functionality-and-workflows.md (https://github.com/mattmre/AGENT33/blob/main/docs/functionality-and-workflows.md) - AGENT33/docs/use-cases.md (https://github.com/mattmre/AGENT33/blob/main/docs/use-cases.md) ## Dedupe notes Collapses autonomy lifecycle and use-case material into a single execution-governance entry. ## Source excerpts ### AGENT33/docs/functionality-and-workflows.md ### 4.4 Autonomy Budget Lifecycle States: - `draft -> pending_approval -> active -> suspended|expired|completed` Flow: 1. Create budget 2. Activate or transition 3. Run preflight checks 4. Create enforcer 5. Evaluate command/file/network requests 6. Track escalations ### AGENT33/docs/use-cases.md ## 3. Autonomous Execution Budgeting Goal: - Enforce hard runtime limits for file, command, and network activity. Use these modules: - `api/routes/autonomy.py` - `autonomy/service.py` - `autonomy/enforcement.py` - `autonomy/preflight.py` Typical flow: 1. Create and activate budget. 2. Run preflight checks. 3. Attach runtime enforcer. 4. Gate each file/command/network action through enforcement APIs. 5. Trigger and resolve escalations. Best fit: - High-control automation in regulated or sensitive environments.
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docs
šŸ“text•6 months ago

Release Command Center Workflow

Coordinate release freezes, candidate promotion, validation, publication, and rollback handling through a defined state model.

devops
⭐1
# Release Command Center Workflow Imported from curated first-party documentation sources. ## What this covers Use this workflow to move a release from planning to publication with explicit validation checkpoints and rollback branches. ## Use this when - Managing release freezes and candidate promotion - Tracking validation state before publication - Documenting rollback-friendly release operations ## Expected outcomes - Release state changes are visible and repeatable - Rollback paths are treated as first-class outcomes - Validation discipline is preserved between phases ## Source synthesis - AGENT33/docs/functionality-and-workflows.md (https://github.com/mattmre/AGENT33/blob/main/docs/functionality-and-workflows.md) - AGENT33/docs/use-cases.md (https://github.com/mattmre/AGENT33/blob/main/docs/use-cases.md) ## Dedupe notes Merges AGENT33 release lifecycle details with release-oriented use-case guidance. ## Source excerpts ### AGENT33/docs/functionality-and-workflows.md ### 4.2 Release Lifecycle States: - `planned -> frozen -> rc -> validating -> released` - Failure/rollback branches: `failed`, `rolled_back` Main APIs: - `/v1/releases/{id}/freeze` - `/v1/releases/{id}/rc` - `/v1/releases/{id}/validate` - `/v1/releases/{id}/publish` - `/v1/releases/{id}/rollback` ### AGENT33/docs/use-cases.md ## 2. Release Command Center Goal: - Move releases through frozen -> RC -> validate -> publish with checklist controls. Use these modules: - `api/routes/releases.py` - `release/service.py` - `release/checklist.py` - `release/sync.py` - `release/rollback.py` Typical flow: 1. Create release (`POST /v1/releases`). 2. Freeze, cut RC, validate. 3. Update/evaluate checklist items. 4. Publish when checks pass. 5. Run sync dry-runs or real syncs. 6. Initiate rollback if needed. Best fit: - Teams with repeatable release compliance requirements.
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docs
šŸ¤–system prompt•7 months ago

web3-testing

Test smart contracts comprehensively using Hardhat and Foundry with

coding
⭐1
# Web3 Smart Contract Testing Master comprehensive testing strategies for smart contracts using Hardhat, Foundry, and advanced testing patterns. ## When to Use This Skill - Writing unit tests for smart contracts - Setting up integration test suites - Performing gas optimization testing - Fuzzing for edge cases - Forking mainnet for realistic testing - Automating test coverage reporting - Verifying contracts on Etherscan ## Hardhat Testing Setup ```javascript // hardhat.config.js require("@nomicfoundation/hardhat-toolbox"); require("@nomiclabs/hardhat-etherscan"); require("hardhat-gas-reporter"); require("solidity-coverage"); module.exports = { solidity: { version: "0.8.19", settings: { optimizer: { enabled: true, runs: 200, }, }, }, networks: { hardhat: { forking: { url: process.env.MAINNET_RPC_URL, blockNumber: 15000000, }, }, goerli: { url: process.env.GOERLI_RPC_URL, accounts: [process.env.PRIVATE_KEY], }, }, gasReporter: { enabled: true, currency: "USD", coinmarketcap: process.env.COINMARKETCAP_API_KEY, }, etherscan: { apiKey: process.env.ETHERSCAN_API_KEY, }, }; ``` ## Unit Testing Patterns ```javascript const { expect } = require("chai"); const { ethers } = require("hardhat"); const { loadFixture, time, } = require("@nomicfoundation/hardhat-network-helpers"); describe("Token Contract", function () { // Fixture for test setup async function deployTokenFixture() { const [owner, addr1, addr2] = await ethers.getSigners(); const Token = await ethers.getContractFactory("Token"); const token = await Token.deploy(); return { token, owner, addr1, addr2 }; } describe("Deployment", function () { it("Should set the right owner", async function () { const { token, owner } = await loadFixture(deployTokenFixture); expect(await token.owner()).to.equal(owner.address); }); it("Should assign total supply to owner", async function () { const { token, owner } = await loadFixture(deployTokenFixture); const ownerBalance = await token.balanceOf(owner.address); expect(await token.totalSupply()).to.equal(ownerBalance); }); }); describe("Transactions", function () { it("Should transfer tokens between accounts", async function () { const { token, owner, addr1 } = await loadFixture(deployTokenFixture); await expect(token.transfer(addr1.address, 50)).to.changeTokenBalances( token, [owner, addr1], [-50, 50], ); }); it("Should fail if sender doesn't have enough tokens", async function () { const { token, addr1 } = await loadFixture(deployTokenFixture); const initialBalance = await token.balanceOf(addr1.address); await expect( token.connect(addr1).transfer(owner.address, 1), ).to.be.revertedWith("Insufficient balance"); }); it("Should emit Transfer event", async function () { const { token, owner, addr1 } = await loadFixture(deployTokenFixture); await expect(token.transfer(addr1.address, 50)) .to.emit(token, "Transfer") .withArgs(owner.address, addr1.address, 50); }); }); describe("Time-based tests", function () { it("Should handle time-locked operations", async function () { const { token } = await loadFixture(deployTokenFixture); // Increase time by 1 day await time.increase(86400); // Test time-dependent functionality }); }); describe("Gas optimization", function () { it("Should use gas efficiently", async function () { const { token } = await loadFixture(deployTokenFixture); const tx = await token.transfer(addr1.address, 100); const receipt = await tx.wait(); expect(receipt.gasUsed).to.be.lessThan(50000); }); }); }); ``` ## Foundry Testing (Forge) ```solidity // SPDX-License-Identifier: MIT pragma solidity ^0.8.0; import "forge-std/Test.sol"; import "../src/Token.sol"; contract TokenTest is Test { Token token; address owner = address(1); address user1 = address(2); address user2 = address(3); function setUp() public { vm.prank(owner); token = new Token(); } function testInitialSupply() public { assertEq(token.totalSupply(), 1000000 * 10**18); } function testTransfer() public { vm.prank(owner); token.transfer(user1, 100); assertEq(token.balanceOf(user1), 100); assertEq(token.balanceOf(owner), token.totalSupply() - 100); } function testFailTransferInsufficientBalance() public { vm.prank(user1); token.transfer(user2, 100); // Should fail } function testCannotTransferToZeroAddress() public { vm.prank(owner); vm.expectRevert("Invalid recipient"); token.transfer(address(0), 100); } // Fuzzing test function testFuzzTransfer(uint256 amount) public { vm.assume(amount > 0 && amount <= token.totalSupply()); vm.prank(owner); token.transfer(user1, amount); assertEq(token.balanceOf(user1), amount); } // Test with cheatcodes function testDealAndPrank() public { // Give ETH to address vm.deal(user1, 10 ether); // Impersonate address vm.prank(user1); // Test functionality assertEq(user1.balance, 10 ether); } // Mainnet fork test function testForkMainnet() public { vm.createSelectFork("https://eth-mainnet.alchemyapi.io/v2/..."); // Interact with mainnet contracts address dai = 0x6B175474E89094C44Da98b954EedeAC495271d0F; assertEq(IERC20(dai).symbol(), "DAI"); } } ``` ## Advanced Testing Patterns ### Snapshot and Revert ```javascript describe("Complex State Changes", function () { let snapshotId; beforeEach(async function () { snapshotId = await network.provider.send("evm_snapshot"); }); afterEach(async function () { await network.provider.send("evm_revert", [snapshotId]); }); it("Test 1", async function () { // Make state changes }); it("Test 2", async function () { // State reverted, clean slate }); }); ``` ### Mainnet Forking ```javascript describe("Mainnet Fork Tests", function () { let uniswapRouter, dai, usdc; before(async function () { await network.provider.request({ method: "hardhat_reset", params: [ { forking: { jsonRpcUrl: process.env.MAINNET_RPC_URL, blockNumber: 15000000, }, }, ], }); // Connect to existing mainnet contracts uniswapRouter = await ethers.getContractAt( "IUniswapV2Router", "0x7a250d5630B4cF539739dF2C5dAcb4c659F2488D", ); dai = await ethers.getContractAt( "IERC20", "0x6B175474E89094C44Da98b954EedeAC495271d0F", ); }); it("Should swap on Uniswap", async function () { // Test with real Uniswap contracts }); }); ``` ### Impersonating Accounts ```javascript it("Should impersonate whale account", async function () { const whaleAddress = "0x..."; await network.provider.request({ method: "hardhat_impersonateAccount", params: [whaleAddress], }); const whale = await ethers.getSigner(whaleAddress); // Use whale's tokens await dai .connect(whale) .transfer(addr1.address, ethers.utils.parseEther("1000")); }); ``` ## Gas Optimization Testing ```javascript const { expect } = require("chai"); describe("Gas Optimization", function () { it("Compare gas usage between implementations", async function () { const Implementation1 = await ethers.getContractFactory("OptimizedContract"); const Implementation2 = await ethers.getContractFactory( "UnoptimizedContract", ); const contract1 = await Implementation1.deploy(); const contract2 = await Implementation2.deploy(); const tx1 = await contract1.doSomething(); const receipt1 = await tx1.wait(); const tx2 = await contract2.doSomething(); const receipt2 = await tx2.wait(); console.log("Optimized gas:", receipt1.gasUsed.toString()); console.log("Unoptimized gas:", receipt2.gasUsed.toString()); expect(receipt1.gasUsed).to.be.lessThan(receipt2.gasUsed); }); }); ``` ## Coverage Reporting ```bash # Generate coverage report npx hardhat coverage # Output shows: # File | % Stmts | % Branch | % Funcs | % Lines | # -------------------|---------|----------|---------|---------| # contracts/Token.sol | 100 | 90 | 100 | 95 | ``` ## Contract Verification ```javascript // Verify on Etherscan await hre.run("verify:verify", { address: contractAddress, constructorArguments: [arg1, arg2], }); ``` ```bash # Or via CLI npx hardhat verify --network mainnet CONTRACT_ADDRESS "Constructor arg1" "arg2" ``` ## CI/CD Integration ```yaml # .github/workflows/test.yml name: Tests on: [push, pull_request] jobs: test: runs-on: ubuntu-latest steps: - uses: actions/checkout@v2 - uses: actions/setup-node@v2 with: node-version: "16" - run: npm install - run: npx hardhat compile - run: npx hardhat test - run: npx hardhat coverage - name: Upload coverage to Codecov uses: codecov/codecov-action@v2 ``` ## Resources - **references/hardhat-setup.md**: Hardhat configuration guide - **references/foundry-setup.md**: Foundry testing framework - **references/test-patterns.md**: Testing best practices - **references/mainnet-forking.md**: Fork testing strategies - **references/contract-verification.md**: Etherscan verification - **assets/hardhat-config.js**: Complete Hardhat configuration - **assets/test-suite.js**: Comprehensive test examples - **assets/foundry.toml**: Foundry configuration - **scripts/test-contract.sh**: Automated testing script ## Best Practices 1. **Test Coverage**: Aim for >90% coverage 2. **Edge Cases**: Test boundary conditions 3. **Gas Limits**: Verify functions don't hit block gas limit 4. **Reentrancy**: Test for reentrancy vulnerabilities 5. **Access Control**: Test unauthorized access attempts 6. **Events**: Verify event emissions 7. **Fixtures**: Use fixtures to avoid code duplication 8. **Mainnet Fork**: Test with real contracts 9. **Fuzzing**: Use property-based testing 10. **CI/CD**: Automate testing on every commit
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šŸ¤– Auto-discovered
šŸ¤–system prompt•7 months ago

defi-protocol-templates

Implement DeFi protocols with production-ready templates for

coding
⭐1
# DeFi Protocol Templates Production-ready templates for common DeFi protocols including staking, AMMs, governance, lending, and flash loans. ## When to Use This Skill - Building staking platforms with reward distribution - Implementing AMM (Automated Market Maker) protocols - Creating governance token systems - Developing lending/borrowing protocols - Integrating flash loan functionality - Launching yield farming platforms ## Staking Contract ```solidity // SPDX-License-Identifier: MIT pragma solidity ^0.8.0; import "@openzeppelin/contracts/token/ERC20/IERC20.sol"; import "@openzeppelin/contracts/security/ReentrancyGuard.sol"; import "@openzeppelin/contracts/access/Ownable.sol"; contract StakingRewards is ReentrancyGuard, Ownable { IERC20 public stakingToken; IERC20 public rewardsToken; uint256 public rewardRate = 100; // Rewards per second uint256 public lastUpdateTime; uint256 public rewardPerTokenStored; mapping(address => uint256) public userRewardPerTokenPaid; mapping(address => uint256) public rewards; mapping(address => uint256) public balances; uint256 private _totalSupply; event Staked(address indexed user, uint256 amount); event Withdrawn(address indexed user, uint256 amount); event RewardPaid(address indexed user, uint256 reward); constructor(address _stakingToken, address _rewardsToken) { stakingToken = IERC20(_stakingToken); rewardsToken = IERC20(_rewardsToken); } modifier updateReward(address account) { rewardPerTokenStored = rewardPerToken(); lastUpdateTime = block.timestamp; if (account != address(0)) { rewards[account] = earned(account); userRewardPerTokenPaid[account] = rewardPerTokenStored; } _; } function rewardPerToken() public view returns (uint256) { if (_totalSupply == 0) { return rewardPerTokenStored; } return rewardPerTokenStored + ((block.timestamp - lastUpdateTime) * rewardRate * 1e18) / _totalSupply; } function earned(address account) public view returns (uint256) { return (balances[account] * (rewardPerToken() - userRewardPerTokenPaid[account])) / 1e18 + rewards[account]; } function stake(uint256 amount) external nonReentrant updateReward(msg.sender) { require(amount > 0, "Cannot stake 0"); _totalSupply += amount; balances[msg.sender] += amount; stakingToken.transferFrom(msg.sender, address(this), amount); emit Staked(msg.sender, amount); } function withdraw(uint256 amount) public nonReentrant updateReward(msg.sender) { require(amount > 0, "Cannot withdraw 0"); _totalSupply -= amount; balances[msg.sender] -= amount; stakingToken.transfer(msg.sender, amount); emit Withdrawn(msg.sender, amount); } function getReward() public nonReentrant updateReward(msg.sender) { uint256 reward = rewards[msg.sender]; if (reward > 0) { rewards[msg.sender] = 0; rewardsToken.transfer(msg.sender, reward); emit RewardPaid(msg.sender, reward); } } function exit() external { withdraw(balances[msg.sender]); getReward(); } } ``` ## AMM (Automated Market Maker) ```solidity // SPDX-License-Identifier: MIT pragma solidity ^0.8.0; import "@openzeppelin/contracts/token/ERC20/IERC20.sol"; contract SimpleAMM { IERC20 public token0; IERC20 public token1; uint256 public reserve0; uint256 public reserve1; uint256 public totalSupply; mapping(address => uint256) public balanceOf; event Mint(address indexed to, uint256 amount); event Burn(address indexed from, uint256 amount); event Swap(address indexed trader, uint256 amount0In, uint256 amount1In, uint256 amount0Out, uint256 amount1Out); constructor(address _token0, address _token1) { token0 = IERC20(_token0); token1 = IERC20(_token1); } function addLiquidity(uint256 amount0, uint256 amount1) external returns (uint256 shares) { token0.transferFrom(msg.sender, address(this), amount0); token1.transferFrom(msg.sender, address(this), amount1); if (totalSupply == 0) { shares = sqrt(amount0 * amount1); } else { shares = min( (amount0 * totalSupply) / reserve0, (amount1 * totalSupply) / reserve1 ); } require(shares > 0, "Shares = 0"); _mint(msg.sender, shares); _update( token0.balanceOf(address(this)), token1.balanceOf(address(this)) ); emit Mint(msg.sender, shares); } function removeLiquidity(uint256 shares) external returns (uint256 amount0, uint256 amount1) { uint256 bal0 = token0.balanceOf(address(this)); uint256 bal1 = token1.balanceOf(address(this)); amount0 = (shares * bal0) / totalSupply; amount1 = (shares * bal1) / totalSupply; require(amount0 > 0 && amount1 > 0, "Amount0 or amount1 = 0"); _burn(msg.sender, shares); _update(bal0 - amount0, bal1 - amount1); token0.transfer(msg.sender, amount0); token1.transfer(msg.sender, amount1); emit Burn(msg.sender, shares); } function swap(address tokenIn, uint256 amountIn) external returns (uint256 amountOut) { require(tokenIn == address(token0) || tokenIn == address(token1), "Invalid token"); bool isToken0 = tokenIn == address(token0); (IERC20 tokenIn_, IERC20 tokenOut, uint256 resIn, uint256 resOut) = isToken0 ? (token0, token1, reserve0, reserve1) : (token1, token0, reserve1, reserve0); tokenIn_.transferFrom(msg.sender, address(this), amountIn); // 0.3% fee uint256 amountInWithFee = (amountIn * 997) / 1000; amountOut = (resOut * amountInWithFee) / (resIn + amountInWithFee); tokenOut.transfer(msg.sender, amountOut); _update( token0.balanceOf(address(this)), token1.balanceOf(address(this)) ); emit Swap(msg.sender, isToken0 ? amountIn : 0, isToken0 ? 0 : amountIn, isToken0 ? 0 : amountOut, isToken0 ? amountOut : 0); } function _mint(address to, uint256 amount) private { balanceOf[to] += amount; totalSupply += amount; } function _burn(address from, uint256 amount) private { balanceOf[from] -= amount; totalSupply -= amount; } function _update(uint256 res0, uint256 res1) private { reserve0 = res0; reserve1 = res1; } function sqrt(uint256 y) private pure returns (uint256 z) { if (y > 3) { z = y; uint256 x = y / 2 + 1; while (x < z) { z = x; x = (y / x + x) / 2; } } else if (y != 0) { z = 1; } } function min(uint256 x, uint256 y) private pure returns (uint256) { return x <= y ? x : y; } } ``` ## Governance Token ```solidity // SPDX-License-Identifier: MIT pragma solidity ^0.8.0; import "@openzeppelin/contracts/token/ERC20/extensions/ERC20Votes.sol"; import "@openzeppelin/contracts/access/Ownable.sol"; contract GovernanceToken is ERC20Votes, Ownable { constructor() ERC20("Governance Token", "GOV") ERC20Permit("Governance Token") { _mint(msg.sender, 1000000 * 10**decimals()); } function _afterTokenTransfer( address from, address to, uint256 amount ) internal override(ERC20Votes) { super._afterTokenTransfer(from, to, amount); } function _mint(address to, uint256 amount) internal override(ERC20Votes) { super._mint(to, amount); } function _burn(address account, uint256 amount) internal override(ERC20Votes) { super._burn(account, amount); } } contract Governor is Ownable { GovernanceToken public governanceToken; struct Proposal { uint256 id; address proposer; string description; uint256 forVotes; uint256 againstVotes; uint256 startBlock; uint256 endBlock; bool executed; mapping(address => bool) hasVoted; } uint256 public proposalCount; mapping(uint256 => Proposal) public proposals; uint256 public votingPeriod = 17280; // ~3 days in blocks uint256 public proposalThreshold = 100000 * 10**18; event ProposalCreated(uint256 indexed proposalId, address proposer, string description); event VoteCast(address indexed voter, uint256 indexed proposalId, bool support, uint256 weight); event ProposalExecuted(uint256 indexed proposalId); constructor(address _governanceToken) { governanceToken = GovernanceToken(_governanceToken); } function propose(string memory description) external returns (uint256) { require( governanceToken.getPastVotes(msg.sender, block.number - 1) >= proposalThreshold, "Proposer votes below threshold" ); proposalCount++; Proposal storage newProposal = proposals[proposalCount]; newProposal.id = proposalCount; newProposal.proposer = msg.sender; newProposal.description = description; newProposal.startBlock = block.number; newProposal.endBlock = block.number + votingPeriod; emit ProposalCreated(proposalCount, msg.sender, description); return proposalCount; } function vote(uint256 proposalId, bool support) external { Proposal storage proposal = proposals[proposalId]; require(block.number >= proposal.startBlock, "Voting not started"); require(block.number <= proposal.endBlock, "Voting ended"); require(!proposal.hasVoted[msg.sender], "Already voted"); uint256 weight = governanceToken.getPastVotes(msg.sender, proposal.startBlock); require(weight > 0, "No voting power"); proposal.hasVoted[msg.sender] = true; if (support) { proposal.forVotes += weight; } else { proposal.againstVotes += weight; } emit VoteCast(msg.sender, proposalId, support, weight); } function execute(uint256 proposalId) external { Proposal storage proposal = proposals[proposalId]; require(block.number > proposal.endBlock, "Voting not ended"); require(!proposal.executed, "Already executed"); require(proposal.forVotes > proposal.againstVotes, "Proposal failed"); proposal.executed = true; // Execute proposal logic here emit ProposalExecuted(proposalId); } } ``` ## Flash Loan ```solidity // SPDX-License-Identifier: MIT pragma solidity ^0.8.0; import "@openzeppelin/contracts/token/ERC20/IERC20.sol"; interface IFlashLoanReceiver { function executeOperation( address asset, uint256 amount, uint256 fee, bytes calldata params ) external returns (bool); } contract FlashLoanProvider { IERC20 public token; uint256 public feePercentage = 9; // 0.09% fee event FlashLoan(address indexed borrower, uint256 amount, uint256 fee); constructor(address _token) { token = IERC20(_token); } function flashLoan( address receiver, uint256 amount, bytes calldata params ) external { uint256 balanceBefore = token.balanceOf(address(this)); require(balanceBefore >= amount, "Insufficient liquidity"); uint256 fee = (amount * feePercentage) / 10000; // Send tokens to receiver token.transfer(receiver, amount); // Execute callback require( IFlashLoanReceiver(receiver).executeOperation( address(token), amount, fee, params ), "Flash loan failed" ); // Verify repayment uint256 balanceAfter = token.balanceOf(address(this)); require(balanceAfter >= balanceBefore + fee, "Flash loan not repaid"); emit FlashLoan(receiver, amount, fee); } } // Example flash loan receiver contract FlashLoanReceiver is IFlashLoanReceiver { function executeOperation( address asset, uint256 amount, uint256 fee, bytes calldata params ) external override returns (bool) { // Decode params and execute arbitrage, liquidation, etc. // ... // Approve repayment IERC20(asset).approve(msg.sender, amount + fee); return true; } } ``` ## Resources - **references/staking.md**: Staking mechanics and reward distribution - **references/liquidity-pools.md**: AMM mathematics and pricing - **references/governance-tokens.md**: Governance and voting systems - **references/lending-protocols.md**: Lending/borrowing implementation - **references/flash-loans.md**: Flash loan security and use cases - **assets/staking-contract.sol**: Production staking template - **assets/amm-contract.sol**: Full AMM implementation - **assets/governance-token.sol**: Governance system - **assets/lending-protocol.sol**: Lending platform template ## Best Practices 1. **Use Established Libraries**: OpenZeppelin, Solmate 2. **Test Thoroughly**: Unit tests, integration tests, fuzzing 3. **Audit Before Launch**: Professional security audits 4. **Start Simple**: MVP first, add features incrementally 5. **Monitor**: Track contract health and user activity 6. **Upgradability**: Consider proxy patterns for upgrades 7. **Emergency Controls**: Pause mechanisms for critical issues ## Common DeFi Patterns - **Time-Weighted Average Price (TWAP)**: Price oracle resistance - **Liquidity Mining**: Incentivize liquidity provision - **Vesting**: Lock tokens with gradual release - **Multisig**: Require multiple signatures for critical operations - **Timelocks**: Delay execution of governance decisions
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šŸ¤– Auto-discovered
šŸ¤–system prompt•7 months ago

architecture-patterns

Implement proven backend architecture patterns including Clean

coding
⭐1
# Architecture Patterns Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems. ## When to Use This Skill - Designing new backend systems from scratch - Refactoring monolithic applications for better maintainability - Establishing architecture standards for your team - Migrating from tightly coupled to loosely coupled architectures - Implementing domain-driven design principles - Creating testable and mockable codebases - Planning microservices decomposition ## Core Concepts ### 1. Clean Architecture (Uncle Bob) **Layers (dependency flows inward):** - **Entities**: Core business models - **Use Cases**: Application business rules - **Interface Adapters**: Controllers, presenters, gateways - **Frameworks & Drivers**: UI, database, external services **Key Principles:** - Dependencies point inward - Inner layers know nothing about outer layers - Business logic independent of frameworks - Testable without UI, database, or external services ### 2. Hexagonal Architecture (Ports and Adapters) **Components:** - **Domain Core**: Business logic - **Ports**: Interfaces defining interactions - **Adapters**: Implementations of ports (database, REST, message queue) **Benefits:** - Swap implementations easily (mock for testing) - Technology-agnostic core - Clear separation of concerns ### 3. Domain-Driven Design (DDD) **Strategic Patterns:** - **Bounded Contexts**: Separate models for different domains - **Context Mapping**: How contexts relate - **Ubiquitous Language**: Shared terminology **Tactical Patterns:** - **Entities**: Objects with identity - **Value Objects**: Immutable objects defined by attributes - **Aggregates**: Consistency boundaries - **Repositories**: Data access abstraction - **Domain Events**: Things that happened ## Clean Architecture Pattern ### Directory Structure ``` app/ ā”œā”€ā”€ domain/ # Entities & business rules │ ā”œā”€ā”€ entities/ │ │ ā”œā”€ā”€ user.py │ │ └── order.py │ ā”œā”€ā”€ value_objects/ │ │ ā”œā”€ā”€ email.py │ │ └── money.py │ └── interfaces/ # Abstract interfaces │ ā”œā”€ā”€ user_repository.py │ └── payment_gateway.py ā”œā”€ā”€ use_cases/ # Application business rules │ ā”œā”€ā”€ create_user.py │ ā”œā”€ā”€ process_order.py │ └── send_notification.py ā”œā”€ā”€ adapters/ # Interface implementations │ ā”œā”€ā”€ repositories/ │ │ ā”œā”€ā”€ postgres_user_repository.py │ │ └── redis_cache_repository.py │ ā”œā”€ā”€ controllers/ │ │ └── user_controller.py │ └── gateways/ │ ā”œā”€ā”€ stripe_payment_gateway.py │ └── sendgrid_email_gateway.py └── infrastructure/ # Framework & external concerns ā”œā”€ā”€ database.py ā”œā”€ā”€ config.py └── logging.py ``` ### Implementation Example ```python # domain/entities/user.py from dataclasses import dataclass from datetime import datetime from typing import Optional @dataclass class User: """Core user entity - no framework dependencies.""" id: str email: str name: str created_at: datetime is_active: bool = True def deactivate(self): """Business rule: deactivating user.""" self.is_active = False def can_place_order(self) -> bool: """Business rule: active users can order.""" return self.is_active # domain/interfaces/user_repository.py from abc import ABC, abstractmethod from typing import Optional, List from domain.entities.user import User class IUserRepository(ABC): """Port: defines contract, no implementation.""" @abstractmethod async def find_by_id(self, user_id: str) -> Optional[User]: pass @abstractmethod async def find_by_email(self, email: str) -> Optional[User]: pass @abstractmethod async def save(self, user: User) -> User: pass @abstractmethod async def delete(self, user_id: str) -> bool: pass # use_cases/create_user.py from domain.entities.user import User from domain.interfaces.user_repository import IUserRepository from dataclasses import dataclass from datetime import datetime import uuid @dataclass class CreateUserRequest: email: str name: str @dataclass class CreateUserResponse: user: User success: bool error: Optional[str] = None class CreateUserUseCase: """Use case: orchestrates business logic.""" def __init__(self, user_repository: IUserRepository): self.user_repository = user_repository async def execute(self, request: CreateUserRequest) -> CreateUserResponse: # Business validation existing = await self.user_repository.find_by_email(request.email) if existing: return CreateUserResponse( user=None, success=False, error="Email already exists" ) # Create entity user = User( id=str(uuid.uuid4()), email=request.email, name=request.name, created_at=datetime.now(), is_active=True ) # Persist saved_user = await self.user_repository.save(user) return CreateUserResponse( user=saved_user, success=True ) # adapters/repositories/postgres_user_repository.py from domain.interfaces.user_repository import IUserRepository from domain.entities.user import User from typing import Optional import asyncpg class PostgresUserRepository(IUserRepository): """Adapter: PostgreSQL implementation.""" def __init__(self, pool: asyncpg.Pool): self.pool = pool async def find_by_id(self, user_id: str) -> Optional[User]: async with self.pool.acquire() as conn: row = await conn.fetchrow( "SELECT * FROM users WHERE id = $1", user_id ) return self._to_entity(row) if row else None async def find_by_email(self, email: str) -> Optional[User]: async with self.pool.acquire() as conn: row = await conn.fetchrow( "SELECT * FROM users WHERE email = $1", email ) return self._to_entity(row) if row else None async def save(self, user: User) -> User: async with self.pool.acquire() as conn: await conn.execute( """ INSERT INTO users (id, email, name, created_at, is_active) VALUES ($1, $2, $3, $4, $5) ON CONFLICT (id) DO UPDATE SET email = $2, name = $3, is_active = $5 """, user.id, user.email, user.name, user.created_at, user.is_active ) return user async def delete(self, user_id: str) -> bool: async with self.pool.acquire() as conn: result = await conn.execute( "DELETE FROM users WHERE id = $1", user_id ) return result == "DELETE 1" def _to_entity(self, row) -> User: """Map database row to entity.""" return User( id=row["id"], email=row["email"], name=row["name"], created_at=row["created_at"], is_active=row["is_active"] ) # adapters/controllers/user_controller.py from fastapi import APIRouter, Depends, HTTPException from use_cases.create_user import CreateUserUseCase, CreateUserRequest from pydantic import BaseModel router = APIRouter() class CreateUserDTO(BaseModel): email: str name: str @router.post("/users") async def create_user( dto: CreateUserDTO, use_case: CreateUserUseCase = Depends(get_create_user_use_case) ): """Controller: handles HTTP concerns only.""" request = CreateUserRequest(email=dto.email, name=dto.name) response = await use_case.execute(request) if not response.success: raise HTTPException(status_code=400, detail=response.error) return {"user": response.user} ``` ## Hexagonal Architecture Pattern ```python # Core domain (hexagon center) class OrderService: """Domain service - no infrastructure dependencies.""" def __init__( self, order_repository: OrderRepositoryPort, payment_gateway: PaymentGatewayPort, notification_service: NotificationPort ): self.orders = order_repository self.payments = payment_gateway self.notifications = notification_service async def place_order(self, order: Order) -> OrderResult: # Business logic if not order.is_valid(): return OrderResult(success=False, error="Invalid order") # Use ports (interfaces) payment = await self.payments.charge( amount=order.total, customer=order.customer_id ) if not payment.success: return OrderResult(success=False, error="Payment failed") order.mark_as_paid() saved_order = await self.orders.save(order) await self.notifications.send( to=order.customer_email, subject="Order confirmed", body=f"Order {order.id} confirmed" ) return OrderResult(success=True, order=saved_order) # Ports (interfaces) class OrderRepositoryPort(ABC): @abstractmethod async def save(self, order: Order) -> Order: pass class PaymentGatewayPort(ABC): @abstractmethod async def charge(self, amount: Money, customer: str) -> PaymentResult: pass class NotificationPort(ABC): @abstractmethod async def send(self, to: str, subject: str, body: str): pass # Adapters (implementations) class StripePaymentAdapter(PaymentGatewayPort): """Primary adapter: connects to Stripe API.""" def __init__(self, api_key: str): self.stripe = stripe self.stripe.api_key = api_key async def charge(self, amount: Money, customer: str) -> PaymentResult: try: charge = self.stripe.Charge.create( amount=amount.cents, currency=amount.currency, customer=customer ) return PaymentResult(success=True, transaction_id=charge.id) except stripe.error.CardError as e: return PaymentResult(success=False, error=str(e)) class MockPaymentAdapter(PaymentGatewayPort): """Test adapter: no external dependencies.""" async def charge(self, amount: Money, customer: str) -> PaymentResult: return PaymentResult(success=True, transaction_id="mock-123") ``` ## Domain-Driven Design Pattern ```python # Value Objects (immutable) from dataclasses import dataclass from typing import Optional @dataclass(frozen=True) class Email: """Value object: validated email.""" value: str def __post_init__(self): if "@" not in self.value: raise ValueError("Invalid email") @dataclass(frozen=True) class Money: """Value object: amount with currency.""" amount: int # cents currency: str def add(self, other: "Money") -> "Money": if self.currency != other.currency: raise ValueError("Currency mismatch") return Money(self.amount + other.amount, self.currency) # Entities (with identity) class Order: """Entity: has identity, mutable state.""" def __init__(self, id: str, customer: Customer): self.id = id self.customer = customer self.items: List[OrderItem] = [] self.status = OrderStatus.PENDING self._events: List[DomainEvent] = [] def add_item(self, product: Product, quantity: int): """Business logic in entity.""" item = OrderItem(product, quantity) self.items.append(item) self._events.append(ItemAddedEvent(self.id, item)) def total(self) -> Money: """Calculated property.""" return sum(item.subtotal() for item in self.items) def submit(self): """State transition with business rules.""" if not self.items: raise ValueError("Cannot submit empty order") if self.status != OrderStatus.PENDING: raise ValueError("Order already submitted") self.status = OrderStatus.SUBMITTED self._events.append(OrderSubmittedEvent(self.id)) # Aggregates (consistency boundary) class Customer: """Aggregate root: controls access to entities.""" def __init__(self, id: str, email: Email): self.id = id self.email = email self._addresses: List[Address] = [] self._orders: List[str] = [] # Order IDs, not full objects def add_address(self, address: Address): """Aggregate enforces invariants.""" if len(self._addresses) >= 5: raise ValueError("Maximum 5 addresses allowed") self._addresses.append(address) @property def primary_address(self) -> Optional[Address]: return next((a for a in self._addresses if a.is_primary), None) # Domain Events @dataclass class OrderSubmittedEvent: order_id: str occurred_at: datetime = field(default_factory=datetime.now) # Repository (aggregate persistence) class OrderRepository: """Repository: persist/retrieve aggregates.""" async def find_by_id(self, order_id: str) -> Optional[Order]: """Reconstitute aggregate from storage.""" pass async def save(self, order: Order): """Persist aggregate and publish events.""" await self._persist(order) await self._publish_events(order._events) order._events.clear() ``` ## Resources - **references/clean-architecture-guide.md**: Detailed layer breakdown - **references/hexagonal-architecture-guide.md**: Ports and adapters patterns - **references/ddd-tactical-patterns.md**: Entities, value objects, aggregates - **assets/clean-architecture-template/**: Complete project structure - **assets/ddd-examples/**: Domain modeling examples ## Best Practices 1. **Dependency Rule**: Dependencies always point inward 2. **Interface Segregation**: Small, focused interfaces 3. **Business Logic in Domain**: Keep frameworks out of core 4. **Test Independence**: Core testable without infrastructure 5. **Bounded Contexts**: Clear domain boundaries 6. **Ubiquitous Language**: Consistent terminology 7. **Thin Controllers**: Delegate to use cases 8. **Rich Domain Models**: Behavior with data ## Common Pitfalls - **Anemic Domain**: Entities with only data, no behavior - **Framework Coupling**: Business logic depends on frameworks - **Fat Controllers**: Business logic in controllers - **Repository Leakage**: Exposing ORM objects - **Missing Abstractions**: Concrete dependencies in core - **Over-Engineering**: Clean architecture for simple CRUD
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šŸ¤– Auto-discovered
šŸ¤–system prompt•7 months ago

multi-reviewer-patterns

Coordinate parallel code reviews across multiple quality dimensions

coding
⭐1
# Multi-Reviewer Patterns Patterns for coordinating parallel code reviews across multiple quality dimensions, deduplicating findings, calibrating severity, and producing consolidated reports. ## When to Use This Skill - Organizing a multi-dimensional code review - Deciding which review dimensions to assign - Deduplicating findings from multiple reviewers - Calibrating severity ratings consistently - Producing a consolidated review report ## Review Dimension Allocation ### Available Dimensions | Dimension | Focus | When to Include | | ----------------- | --------------------------------------- | ------------------------------------------- | | **Security** | Vulnerabilities, auth, input validation | Always for code handling user input or auth | | **Performance** | Query efficiency, memory, caching | When changing data access or hot paths | | **Architecture** | SOLID, coupling, patterns | For structural changes or new modules | | **Testing** | Coverage, quality, edge cases | When adding new functionality | | **Accessibility** | WCAG, ARIA, keyboard nav | For UI/frontend changes | ### Recommended Combinations | Scenario | Dimensions | | ---------------------- | -------------------------------------------- | | API endpoint changes | Security, Performance, Architecture | | Frontend component | Architecture, Testing, Accessibility | | Database migration | Performance, Architecture | | Authentication changes | Security, Testing | | Full feature review | Security, Performance, Architecture, Testing | ## Finding Deduplication When multiple reviewers report issues at the same location: ### Merge Rules 1. **Same file:line, same issue** — Merge into one finding, credit all reviewers 2. **Same file:line, different issues** — Keep as separate findings 3. **Same issue, different locations** — Keep separate but cross-reference 4. **Conflicting severity** — Use the higher severity rating 5. **Conflicting recommendations** — Include both with reviewer attribution ### Deduplication Process ``` For each finding in all reviewer reports: 1. Check if another finding references the same file:line 2. If yes, check if they describe the same issue 3. If same issue: merge, keeping the more detailed description 4. If different issue: keep both, tag as "co-located" 5. Use highest severity among merged findings ``` ## Severity Calibration ### Severity Criteria | Severity | Impact | Likelihood | Examples | | ------------ | --------------------------------------------- | ---------------------- | -------------------------------------------- | | **Critical** | Data loss, security breach, complete failure | Certain or very likely | SQL injection, auth bypass, data corruption | | **High** | Significant functionality impact, degradation | Likely | Memory leak, missing validation, broken flow | | **Medium** | Partial impact, workaround exists | Possible | N+1 query, missing edge case, unclear error | | **Low** | Minimal impact, cosmetic | Unlikely | Style issue, minor optimization, naming | ### Calibration Rules - Security vulnerabilities exploitable by external users: always Critical or High - Performance issues in hot paths: at least Medium - Missing tests for critical paths: at least Medium - Accessibility violations for core functionality: at least Medium - Code style issues with no functional impact: Low ## Consolidated Report Template ```markdown ## Code Review Report **Target**: {files/PR/directory} **Reviewers**: {dimension-1}, {dimension-2}, {dimension-3} **Date**: {date} **Files Reviewed**: {count} ### Critical Findings ({count}) #### [CR-001] {Title} **Location**: `{file}:{line}` **Dimension**: {Security/Performance/etc.} **Description**: {what was found} **Impact**: {what could happen} **Fix**: {recommended remediation} ### High Findings ({count}) ... ### Medium Findings ({count}) ... ### Low Findings ({count}) ... ### Summary | Dimension | Critical | High | Medium | Low | Total | | ------------ | -------- | ----- | ------ | ----- | ------ | | Security | 1 | 2 | 3 | 0 | 6 | | Performance | 0 | 1 | 4 | 2 | 7 | | Architecture | 0 | 0 | 2 | 3 | 5 | | **Total** | **1** | **3** | **9** | **5** | **18** | ### Recommendation {Overall assessment and prioritized action items} ```
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šŸ‘ļø1
šŸ¤– Auto-discovered
šŸ¤–system prompt•7 months ago

screen-reader-testing

Test web applications with screen readers including VoiceOver,

coding
⭐1
# Screen Reader Testing Practical guide to testing web applications with screen readers for comprehensive accessibility validation. ## When to Use This Skill - Validating screen reader compatibility - Testing ARIA implementations - Debugging assistive technology issues - Verifying form accessibility - Testing dynamic content announcements - Ensuring navigation accessibility ## Core Concepts ### 1. Major Screen Readers | Screen Reader | Platform | Browser | Usage | | ------------- | --------- | -------------- | ----- | | **VoiceOver** | macOS/iOS | Safari | ~15% | | **NVDA** | Windows | Firefox/Chrome | ~31% | | **JAWS** | Windows | Chrome/IE | ~40% | | **TalkBack** | Android | Chrome | ~10% | | **Narrator** | Windows | Edge | ~4% | ### 2. Testing Priority ``` Minimum Coverage: 1. NVDA + Firefox (Windows) 2. VoiceOver + Safari (macOS) 3. VoiceOver + Safari (iOS) Comprehensive Coverage: + JAWS + Chrome (Windows) + TalkBack + Chrome (Android) + Narrator + Edge (Windows) ``` ### 3. Screen Reader Modes | Mode | Purpose | When Used | | ------------------ | ---------------------- | ----------------- | | **Browse/Virtual** | Read content | Default reading | | **Focus/Forms** | Interact with controls | Filling forms | | **Application** | Custom widgets | ARIA applications | ## VoiceOver (macOS) ### Setup ``` Enable: System Preferences → Accessibility → VoiceOver Toggle: Cmd + F5 Quick Toggle: Triple-press Touch ID ``` ### Essential Commands ``` Navigation: VO = Ctrl + Option (VoiceOver modifier) VO + Right Arrow Next element VO + Left Arrow Previous element VO + Shift + Down Enter group VO + Shift + Up Exit group Reading: VO + A Read all from cursor Ctrl Stop speaking VO + B Read current paragraph Interaction: VO + Space Activate element VO + Shift + M Open menu Tab Next focusable element Shift + Tab Previous focusable element Rotor (VO + U): Navigate by: Headings, Links, Forms, Landmarks Left/Right Arrow Change rotor category Up/Down Arrow Navigate within category Enter Go to item Web Specific: VO + Cmd + H Next heading VO + Cmd + J Next form control VO + Cmd + L Next link VO + Cmd + T Next table ``` ### Testing Checklist ```markdown ## VoiceOver Testing Checklist ### Page Load - [ ] Page title announced - [ ] Main landmark found - [ ] Skip link works ### Navigation - [ ] All headings discoverable via rotor - [ ] Heading levels logical (H1 → H2 → H3) - [ ] Landmarks properly labeled - [ ] Skip links functional ### Links & Buttons - [ ] Link purpose clear - [ ] Button actions described - [ ] New window/tab announced ### Forms - [ ] All labels read with inputs - [ ] Required fields announced - [ ] Error messages read - [ ] Instructions available - [ ] Focus moves to errors ### Dynamic Content - [ ] Alerts announced immediately - [ ] Loading states communicated - [ ] Content updates announced - [ ] Modals trap focus correctly ### Tables - [ ] Headers associated with cells - [ ] Table navigation works - [ ] Complex tables have captions ``` ### Common Issues & Fixes ```html <!-- Issue: Button not announcing purpose --> <button><svg>...</svg></button> <!-- Fix --> <button aria-label="Close dialog"><svg aria-hidden="true">...</svg></button> <!-- Issue: Dynamic content not announced --> <div id="results">New results loaded</div> <!-- Fix --> <div id="results" role="status" aria-live="polite">New results loaded</div> <!-- Issue: Form error not read --> <input type="email" /> <span class="error">Invalid email</span> <!-- Fix --> <input type="email" aria-invalid="true" aria-describedby="email-error" /> <span id="email-error" role="alert">Invalid email</span> ``` ## NVDA (Windows) ### Setup ``` Download: nvaccess.org Start: Ctrl + Alt + N Stop: Insert + Q ``` ### Essential Commands ``` Navigation: Insert = NVDA modifier Down Arrow Next line Up Arrow Previous line Tab Next focusable Shift + Tab Previous focusable Reading: NVDA + Down Arrow Say all Ctrl Stop speech NVDA + Up Arrow Current line Headings: H Next heading Shift + H Previous heading 1-6 Heading level 1-6 Forms: F Next form field B Next button E Next edit field X Next checkbox C Next combo box Links: K Next link U Next unvisited link V Next visited link Landmarks: D Next landmark Shift + D Previous landmark Tables: T Next table Ctrl + Alt + Arrows Navigate cells Elements List (NVDA + F7): Shows all links, headings, form fields, landmarks ``` ### Browse vs Focus Mode ``` NVDA automatically switches modes: - Browse Mode: Arrow keys navigate content - Focus Mode: Arrow keys control interactive elements Manual switch: NVDA + Space Watch for: - "Browse mode" announcement when navigating - "Focus mode" when entering form fields - Application role forces forms mode ``` ### Testing Script ```markdown ## NVDA Test Script ### Initial Load 1. Navigate to page 2. Let page finish loading 3. Press Insert + Down to read all 4. Note: Page title, main content identified? ### Landmark Navigation 1. Press D repeatedly 2. Check: All main areas reachable? 3. Check: Landmarks properly labeled? ### Heading Navigation 1. Press Insert + F7 → Headings 2. Check: Logical heading structure? 3. Press H to navigate headings 4. Check: All sections discoverable? ### Form Testing 1. Press F to find first form field 2. Check: Label read? 3. Fill in invalid data 4. Submit form 5. Check: Errors announced? 6. Check: Focus moved to error? ### Interactive Elements 1. Tab through all interactive elements 2. Check: Each announces role and state 3. Activate buttons with Enter/Space 4. Check: Result announced? ### Dynamic Content 1. Trigger content update 2. Check: Change announced? 3. Open modal 4. Check: Focus trapped? 5. Close modal 6. Check: Focus returns? ``` ## JAWS (Windows) ### Essential Commands ``` Start: Desktop shortcut or Ctrl + Alt + J Virtual Cursor: Auto-enabled in browsers Navigation: Arrow keys Navigate content Tab Next focusable Insert + Down Read all Ctrl Stop speech Quick Keys: H Next heading T Next table F Next form field B Next button G Next graphic L Next list ; Next landmark Forms Mode: Enter Enter forms mode Numpad + Exit forms mode F5 List form fields Lists: Insert + F7 Link list Insert + F6 Heading list Insert + F5 Form field list Tables: Ctrl + Alt + Arrows Table navigation ``` ## TalkBack (Android) ### Setup ``` Enable: Settings → Accessibility → TalkBack Toggle: Hold both volume buttons 3 seconds ``` ### Gestures ``` Explore: Drag finger across screen Next: Swipe right Previous: Swipe left Activate: Double tap Scroll: Two finger swipe Reading Controls (swipe up then right): - Headings - Links - Controls - Characters - Words - Lines - Paragraphs ``` ## Common Test Scenarios ### 1. Modal Dialog ```html <!-- Accessible modal structure --> <div role="dialog" aria-modal="true" aria-labelledby="dialog-title" aria-describedby="dialog-desc" > <h2 id="dialog-title">Confirm Delete</h2> <p id="dialog-desc">This action cannot be undone.</p> <button>Cancel</button> <button>Delete</button> </div> ``` ```javascript // Focus management function openModal(modal) { // Store last focused element lastFocus = document.activeElement; // Move focus to modal modal.querySelector("h2").focus(); // Trap focus modal.addEventListener("keydown", trapFocus); } function closeModal(modal) { // Return focus lastFocus.focus(); } function trapFocus(e) { if (e.key === "Tab") { const focusable = modal.querySelectorAll( 'button, [href], input, select, textarea, [tabindex]:not([tabindex="-1"])', ); const first = focusable[0]; const last = focusable[focusable.length - 1]; if (e.shiftKey && document.activeElement === first) { last.focus(); e.preventDefault(); } else if (!e.shiftKey && document.activeElement === last) { first.focus(); e.preventDefault(); } } if (e.key === "Escape") { closeModal(modal); } } ``` ### 2. Live Regions ```html <!-- Status messages (polite) --> <div role="status" aria-live="polite" aria-atomic="true"> <!-- Content updates will be announced after current speech --> </div> <!-- Alerts (assertive) --> <div role="alert" aria-live="assertive"> <!-- Content updates interrupt current speech --> </div> <!-- Progress updates --> <div role="progressbar" aria-valuenow="75" aria-valuemin="0" aria-valuemax="100" aria-label="Upload progress" ></div> <!-- Log (additions only) --> <div role="log" aria-live="polite" aria-relevant="additions"> <!-- New messages announced, removals not --> </div> ``` ### 3. Tab Interface ```html <div role="tablist" aria-label="Product information"> <button role="tab" id="tab-1" aria-selected="true" aria-controls="panel-1"> Description </button> <button role="tab" id="tab-2" aria-selected="false" aria-controls="panel-2" tabindex="-1" > Reviews </button> </div> <div role="tabpanel" id="panel-1" aria-labelledby="tab-1"> Product description content... </div> <div role="tabpanel" id="panel-2" aria-labelledby="tab-2" hidden> Reviews content... </div> ``` ```javascript // Tab keyboard navigation tablist.addEventListener("keydown", (e) => { const tabs = [...tablist.querySelectorAll('[role="tab"]')]; const index = tabs.indexOf(document.activeElement); let newIndex; switch (e.key) { case "ArrowRight": newIndex = (index + 1) % tabs.length; break; case "ArrowLeft": newIndex = (index - 1 + tabs.length) % tabs.length; break; case "Home": newIndex = 0; break; case "End": newIndex = tabs.length - 1; break; default: return; } tabs[newIndex].focus(); activateTab(tabs[newIndex]); e.preventDefault(); }); ``` ## Debugging Tips ```javascript // Log what screen reader sees function logAccessibleName(element) { const computed = window.getComputedStyle(element); console.log({ role: element.getAttribute("role") || element.tagName, name: element.getAttribute("aria-label") || element.getAttribute("aria-labelledby") || element.textContent, state: { expanded: element.getAttribute("aria-expanded"), selected: element.getAttribute("aria-selected"), checked: element.getAttribute("aria-checked"), disabled: element.disabled, }, visible: computed.display !== "none" && computed.visibility !== "hidden", }); } ``` ## Best Practices ### Do's - **Test with actual screen readers** - Not just simulators - **Use semantic HTML first** - ARIA is supplemental - **Test in browse and focus modes** - Different experiences - **Verify focus management** - Especially for SPAs - **Test keyboard only first** - Foundation for SR testing ### Don'ts - **Don't assume one SR is enough** - Test multiple - **Don't ignore mobile** - Growing user base - **Don't test only happy path** - Test error states - **Don't skip dynamic content** - Most common issues - **Don't rely on visual testing** - Different experience ## Resources - [VoiceOver User Guide](https://support.apple.com/guide/voiceover/welcome/mac) - [NVDA User Guide](https://www.nvaccess.org/files/nvda/documentation/userGuide.html) - [JAWS Documentation](https://support.freedomscientific.com/Products/Blindness/JAWS) - [WebAIM Screen Reader Survey](https://webaim.org/projects/screenreadersurvey/)
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šŸ‘ļø1
šŸ¤– Auto-discovered
šŸ¤–system prompt•7 months ago

multi-cloud-architecture

Design multi-cloud architectures using a decision framework to

architecture
⭐1
# Multi-Cloud Architecture Decision framework and patterns for architecting applications across AWS, Azure, and GCP. ## Purpose Design cloud-agnostic architectures and make informed decisions about service selection across cloud providers. ## When to Use - Design multi-cloud strategies - Migrate between cloud providers - Select cloud services for specific workloads - Implement cloud-agnostic architectures - Optimize costs across providers ## Cloud Service Comparison ### Compute Services | AWS | Azure | GCP | Use Case | | ------- | ------------------- | --------------- | ------------------ | | EC2 | Virtual Machines | Compute Engine | IaaS VMs | | ECS | Container Instances | Cloud Run | Containers | | EKS | AKS | GKE | Kubernetes | | Lambda | Functions | Cloud Functions | Serverless | | Fargate | Container Apps | Cloud Run | Managed containers | ### Storage Services | AWS | Azure | GCP | Use Case | | ------- | --------------- | --------------- | -------------- | | S3 | Blob Storage | Cloud Storage | Object storage | | EBS | Managed Disks | Persistent Disk | Block storage | | EFS | Azure Files | Filestore | File storage | | Glacier | Archive Storage | Archive Storage | Cold storage | ### Database Services | AWS | Azure | GCP | Use Case | | ----------- | ---------------- | ------------- | --------------- | | RDS | SQL Database | Cloud SQL | Managed SQL | | DynamoDB | Cosmos DB | Firestore | NoSQL | | Aurora | PostgreSQL/MySQL | Cloud Spanner | Distributed SQL | | ElastiCache | Cache for Redis | Memorystore | Caching | **Reference:** See `references/service-comparison.md` for complete comparison ## Multi-Cloud Patterns ### Pattern 1: Single Provider with DR - Primary workload in one cloud - Disaster recovery in another - Database replication across clouds - Automated failover ### Pattern 2: Best-of-Breed - Use best service from each provider - AI/ML on GCP - Enterprise apps on Azure - General compute on AWS ### Pattern 3: Geographic Distribution - Serve users from nearest cloud region - Data sovereignty compliance - Global load balancing - Regional failover ### Pattern 4: Cloud-Agnostic Abstraction - Kubernetes for compute - PostgreSQL for database - S3-compatible storage (MinIO) - Open source tools ## Cloud-Agnostic Architecture ### Use Cloud-Native Alternatives - **Compute:** Kubernetes (EKS/AKS/GKE) - **Database:** PostgreSQL/MySQL (RDS/SQL Database/Cloud SQL) - **Message Queue:** Apache Kafka (MSK/Event Hubs/Confluent) - **Cache:** Redis (ElastiCache/Azure Cache/Memorystore) - **Object Storage:** S3-compatible API - **Monitoring:** Prometheus/Grafana - **Service Mesh:** Istio/Linkerd ### Abstraction Layers ``` Application Layer ↓ Infrastructure Abstraction (Terraform) ↓ Cloud Provider APIs ↓ AWS / Azure / GCP ``` ## Cost Comparison ### Compute Pricing Factors - **AWS:** On-demand, Reserved, Spot, Savings Plans - **Azure:** Pay-as-you-go, Reserved, Spot - **GCP:** On-demand, Committed use, Preemptible ### Cost Optimization Strategies 1. Use reserved/committed capacity (30-70% savings) 2. Leverage spot/preemptible instances 3. Right-size resources 4. Use serverless for variable workloads 5. Optimize data transfer costs 6. Implement lifecycle policies 7. Use cost allocation tags 8. Monitor with cloud cost tools **Reference:** See `references/multi-cloud-patterns.md` ## Migration Strategy ### Phase 1: Assessment - Inventory current infrastructure - Identify dependencies - Assess cloud compatibility - Estimate costs ### Phase 2: Pilot - Select pilot workload - Implement in target cloud - Test thoroughly - Document learnings ### Phase 3: Migration - Migrate workloads incrementally - Maintain dual-run period - Monitor performance - Validate functionality ### Phase 4: Optimization - Right-size resources - Implement cloud-native services - Optimize costs - Enhance security ## Best Practices 1. **Use infrastructure as code** (Terraform/OpenTofu) 2. **Implement CI/CD pipelines** for deployments 3. **Design for failure** across clouds 4. **Use managed services** when possible 5. **Implement comprehensive monitoring** 6. **Automate cost optimization** 7. **Follow security best practices** 8. **Document cloud-specific configurations** 9. **Test disaster recovery** procedures 10. **Train teams** on multiple clouds ## Reference Files - `references/service-comparison.md` - Complete service comparison - `references/multi-cloud-patterns.md` - Architecture patterns ## Related Skills - `terraform-module-library` - For IaC implementation - `cost-optimization` - For cost management - `hybrid-cloud-networking` - For connectivity
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šŸ‘ļø0
šŸ¤– Auto-discovered
šŸ¤–system prompt•7 months ago

track-management

Use this skill when creating, managing, or working with Conductor

coding
⭐1
# Track Management Guide for creating, managing, and completing Conductor tracks - the logical work units that organize features, bugs, and refactors through specification, planning, and implementation phases. ## When to Use This Skill - Creating new feature, bug, or refactor tracks - Writing or reviewing spec.md files - Creating or updating plan.md files - Managing track lifecycle from creation to completion - Understanding track status markers and conventions - Working with the tracks.md registry - Interpreting or updating track metadata ## Track Concept A track is a logical work unit that encapsulates a complete piece of work. Each track has: - A unique identifier - A specification defining requirements - A phased plan breaking work into tasks - Metadata tracking status and progress Tracks provide semantic organization for work, enabling: - Clear scope boundaries - Progress tracking - Git-aware operations (revert by track) - Team coordination ## Track Types ### feature New functionality or capabilities. Use for: - New user-facing features - New API endpoints - New integrations - Significant enhancements ### bug Defect fixes. Use for: - Incorrect behavior - Error conditions - Performance regressions - Security vulnerabilities ### chore Maintenance and housekeeping. Use for: - Dependency updates - Configuration changes - Documentation updates - Cleanup tasks ### refactor Code improvement without behavior change. Use for: - Code restructuring - Pattern adoption - Technical debt reduction - Performance optimization (same behavior, better performance) ## Track ID Format Track IDs follow the pattern: `{shortname}_{YYYYMMDD}` - **shortname**: 2-4 word kebab-case description (e.g., `user-auth`, `api-rate-limit`) - **YYYYMMDD**: Creation date in ISO format Examples: - `user-auth_20250115` - `fix-login-error_20250115` - `upgrade-deps_20250115` - `refactor-api-client_20250115` ## Track Lifecycle ### 1. Creation (newTrack) **Define Requirements** 1. Gather requirements through interactive Q&A 2. Identify acceptance criteria 3. Determine scope boundaries 4. Identify dependencies **Generate Specification** 1. Create `spec.md` with structured requirements 2. Document functional and non-functional requirements 3. Define acceptance criteria 4. List dependencies and constraints **Generate Plan** 1. Create `plan.md` with phased task breakdown 2. Organize tasks into logical phases 3. Add verification tasks after phases 4. Estimate effort and complexity **Register Track** 1. Add entry to `tracks.md` registry 2. Create track directory structure 3. Generate `metadata.json` 4. Create track `index.md` ### 2. Implementation **Execute Tasks** 1. Select next pending task from plan 2. Mark task as in-progress 3. Implement following workflow (TDD) 4. Mark task complete with commit SHA **Update Status** 1. Update task markers in plan.md 2. Record commit SHAs for traceability 3. Update phase progress 4. Update track status in tracks.md **Verify Progress** 1. Complete verification tasks 2. Wait for checkpoint approval 3. Record checkpoint commits ### 3. Completion **Sync Documentation** 1. Update product.md if features added 2. Update tech-stack.md if dependencies changed 3. Verify all acceptance criteria met **Archive or Delete** 1. Mark track as completed in tracks.md 2. Record completion date 3. Archive or retain track directory ## Specification (spec.md) Structure ```markdown # {Track Title} ## Overview Brief description of what this track accomplishes and why. ## Functional Requirements ### FR-1: {Requirement Name} Description of the functional requirement. - Acceptance: How to verify this requirement is met ### FR-2: {Requirement Name} ... ## Non-Functional Requirements ### NFR-1: {Requirement Name} Description of the non-functional requirement (performance, security, etc.) - Target: Specific measurable target - Verification: How to test ## Acceptance Criteria - [ ] Criterion 1: Specific, testable condition - [ ] Criterion 2: Specific, testable condition - [ ] Criterion 3: Specific, testable condition ## Scope ### In Scope - Explicitly included items - Features to implement - Components to modify ### Out of Scope - Explicitly excluded items - Future considerations - Related but separate work ## Dependencies ### Internal - Other tracks or components this depends on - Required context artifacts ### External - Third-party services or APIs - External dependencies ## Risks and Mitigations | Risk | Impact | Mitigation | | ---------------- | --------------- | ------------------- | | Risk description | High/Medium/Low | Mitigation strategy | ## Open Questions - [ ] Question that needs resolution - [x] Resolved question - Answer ``` ## Plan (plan.md) Structure ```markdown # Implementation Plan: {Track Title} Track ID: `{track-id}` Created: YYYY-MM-DD Status: pending | in-progress | completed ## Overview Brief description of implementation approach. ## Phase 1: {Phase Name} ### Tasks - [ ] **Task 1.1**: Task description - Sub-task or detail - Sub-task or detail - [ ] **Task 1.2**: Task description - [ ] **Task 1.3**: Task description ### Verification - [ ] **Verify 1.1**: Verification step for phase ## Phase 2: {Phase Name} ### Tasks - [ ] **Task 2.1**: Task description - [ ] **Task 2.2**: Task description ### Verification - [ ] **Verify 2.1**: Verification step for phase ## Phase 3: Finalization ### Tasks - [ ] **Task 3.1**: Update documentation - [ ] **Task 3.2**: Final integration test ### Verification - [ ] **Verify 3.1**: All acceptance criteria met ## Checkpoints | Phase | Checkpoint SHA | Date | Status | | ------- | -------------- | ---- | ------- | | Phase 1 | | | pending | | Phase 2 | | | pending | | Phase 3 | | | pending | ``` ## Status Marker Conventions Use consistent markers in plan.md: | Marker | Meaning | Usage | | ------ | ----------- | --------------------------- | | `[ ]` | Pending | Task not started | | `[~]` | In Progress | Currently being worked | | `[x]` | Complete | Task finished (include SHA) | | `[-]` | Skipped | Intentionally not done | | `[!]` | Blocked | Waiting on dependency | Example: ```markdown - [x] **Task 1.1**: Set up database schema `abc1234` - [~] **Task 1.2**: Implement user model - [ ] **Task 1.3**: Add validation logic - [!] **Task 1.4**: Integrate auth service (blocked: waiting for API key) - [-] **Task 1.5**: Legacy migration (skipped: not needed) ``` ## Track Registry (tracks.md) Format ```markdown # Track Registry ## Active Tracks | Track ID | Type | Status | Phase | Started | Assignee | | ------------------------------------------------ | ------- | ----------- | ----- | ---------- | ---------- | | [user-auth_20250115](tracks/user-auth_20250115/) | feature | in-progress | 2/3 | 2025-01-15 | @developer | | [fix-login_20250114](tracks/fix-login_20250114/) | bug | pending | 0/2 | 2025-01-14 | - | ## Completed Tracks | Track ID | Type | Completed | Duration | | ---------------------------------------------- | ----- | ---------- | -------- | | [setup-ci_20250110](tracks/setup-ci_20250110/) | chore | 2025-01-12 | 2 days | ## Archived Tracks | Track ID | Reason | Archived | | ---------------------------------------------------- | ---------- | ---------- | | [old-feature_20241201](tracks/old-feature_20241201/) | Superseded | 2025-01-05 | ``` ## Metadata (metadata.json) Fields ```json { "id": "user-auth_20250115", "title": "User Authentication System", "type": "feature", "status": "in-progress", "priority": "high", "created": "2025-01-15T10:30:00Z", "updated": "2025-01-15T14:45:00Z", "started": "2025-01-15T11:00:00Z", "completed": null, "assignee": "@developer", "phases": { "total": 3, "current": 2, "completed": 1 }, "tasks": { "total": 12, "completed": 5, "in_progress": 1, "pending": 6 }, "checkpoints": [ { "phase": 1, "sha": "abc1234", "date": "2025-01-15T13:00:00Z" } ], "dependencies": [], "tags": ["auth", "security"] } ``` ## Track Operations ### Creating a Track 1. Run `/conductor:new-track` 2. Answer interactive questions 3. Review generated spec.md 4. Review generated plan.md 5. Confirm track creation ### Starting Implementation 1. Read spec.md and plan.md 2. Verify context artifacts are current 3. Mark first task as `[~]` 4. Begin TDD workflow ### Completing a Phase 1. Ensure all phase tasks are `[x]` 2. Complete verification tasks 3. Wait for checkpoint approval 4. Record checkpoint SHA 5. Proceed to next phase ### Completing a Track 1. Verify all phases complete 2. Verify all acceptance criteria met 3. Update product.md if needed 4. Mark track completed in tracks.md 5. Update metadata.json ### Reverting a Track 1. Run `/conductor:revert` 2. Select track to revert 3. Choose granularity (track/phase/task) 4. Confirm revert operation 5. Update status markers ## Handling Track Dependencies ### Identifying Dependencies During track creation, identify: - **Hard dependencies**: Must complete before this track can start - **Soft dependencies**: Can proceed in parallel but may affect integration - **External dependencies**: Third-party services, APIs, or team decisions ### Documenting Dependencies In spec.md, list dependencies with: - Dependency type (hard/soft/external) - Current status (available/pending/blocked) - Resolution path (what needs to happen) ### Managing Blocked Tracks When a track is blocked: 1. Mark blocked tasks with `[!]` and reason 2. Update tracks.md status 3. Document blocker in metadata.json 4. Consider creating dependency track if needed ## Track Sizing Guidelines ### Right-Sized Tracks Aim for tracks that: - Complete in 1-5 days of work - Have 2-4 phases - Contain 8-20 tasks total - Deliver a coherent, testable unit ### Too Large Signs a track is too large: - More than 5 phases - More than 25 tasks - Multiple unrelated features - Estimated duration > 1 week Solution: Split into multiple tracks with clear boundaries. ### Too Small Signs a track is too small: - Single phase with 1-2 tasks - No meaningful verification needed - Could be a sub-task of another track - Less than a few hours of work Solution: Combine with related work or handle as part of existing track. ## Specification Quality Checklist Before finalizing spec.md, verify: ### Requirements Quality - [ ] Each requirement has clear acceptance criteria - [ ] Requirements are testable - [ ] Requirements are independent (can verify separately) - [ ] No ambiguous language ("should be fast" → "response < 200ms") ### Scope Clarity - [ ] In-scope items are specific - [ ] Out-of-scope items prevent scope creep - [ ] Boundaries are clear to implementer ### Dependencies Identified - [ ] All internal dependencies listed - [ ] External dependencies have owners/contacts - [ ] Dependency status is current ### Risks Addressed - [ ] Major risks identified - [ ] Impact assessment realistic - [ ] Mitigations are actionable ## Plan Quality Checklist Before starting implementation, verify plan.md: ### Task Quality - [ ] Tasks are atomic (one logical action) - [ ] Tasks are independently verifiable - [ ] Task descriptions are clear - [ ] Sub-tasks provide helpful detail ### Phase Organization - [ ] Phases group related tasks - [ ] Each phase delivers something testable - [ ] Verification tasks after each phase - [ ] Phases build on each other logically ### Completeness - [ ] All spec requirements have corresponding tasks - [ ] Documentation tasks included - [ ] Testing tasks included - [ ] Integration tasks included ## Common Track Patterns ### Feature Track Pattern ``` Phase 1: Foundation - Data models - Database migrations - Basic API structure Phase 2: Core Logic - Business logic implementation - Input validation - Error handling Phase 3: Integration - UI integration - API documentation - End-to-end tests ``` ### Bug Fix Track Pattern ``` Phase 1: Reproduction - Write failing test capturing bug - Document reproduction steps Phase 2: Fix - Implement fix - Verify test passes - Check for regressions Phase 3: Verification - Manual verification - Update documentation if needed ``` ### Refactor Track Pattern ``` Phase 1: Preparation - Add characterization tests - Document current behavior Phase 2: Refactoring - Apply changes incrementally - Maintain green tests throughout Phase 3: Cleanup - Remove dead code - Update documentation ``` ## Best Practices 1. **One track, one concern**: Keep tracks focused on a single logical change 2. **Small phases**: Break work into phases of 3-5 tasks maximum 3. **Verification after phases**: Always include verification tasks 4. **Update markers immediately**: Mark task status as you work 5. **Record SHAs**: Always note commit SHAs for completed tasks 6. **Review specs before planning**: Ensure spec is complete before creating plan 7. **Link dependencies**: Explicitly note track dependencies 8. **Archive, don't delete**: Preserve completed tracks for reference 9. **Size appropriately**: Keep tracks between 1-5 days of work 10. **Clear acceptance criteria**: Every requirement must be testable
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šŸ‘ļø0
šŸ¤– Auto-discovered
šŸ¤–system prompt•7 months ago

workflow-patterns

Use this skill when implementing tasks according to Conductor's TDD

coding
⭐1
# Workflow Patterns Guide for implementing tasks using Conductor's TDD workflow, managing phase checkpoints, handling git commits, and executing the verification protocol that ensures quality throughout implementation. ## When to Use This Skill - Implementing tasks from a track's plan.md - Following TDD red-green-refactor cycle - Completing phase checkpoints - Managing git commits and notes - Understanding quality assurance gates - Handling verification protocols - Recording progress in plan files ## TDD Task Lifecycle Follow these 11 steps for each task: ### Step 1: Select Next Task Read plan.md and identify the next pending `[ ]` task. Select tasks in order within the current phase. Do not skip ahead to later phases. ### Step 2: Mark as In Progress Update plan.md to mark the task as `[~]`: ```markdown - [~] **Task 2.1**: Implement user validation ``` Commit this status change separately from implementation. ### Step 3: RED - Write Failing Tests Write tests that define the expected behavior before writing implementation: - Create test file if needed - Write test cases covering happy path - Write test cases covering edge cases - Write test cases covering error conditions - Run tests - they should FAIL Example: ```python def test_validate_user_email_valid(): user = User(email="test@example.com") assert user.validate_email() is True def test_validate_user_email_invalid(): user = User(email="invalid") assert user.validate_email() is False ``` ### Step 4: GREEN - Implement Minimum Code Write the minimum code necessary to make tests pass: - Focus on making tests green, not perfection - Avoid premature optimization - Keep implementation simple - Run tests - they should PASS ### Step 5: REFACTOR - Improve Clarity With green tests, improve the code: - Extract common patterns - Improve naming - Remove duplication - Simplify logic - Run tests after each change - they should remain GREEN ### Step 6: Verify Coverage Check test coverage meets the 80% target: ```bash pytest --cov=module --cov-report=term-missing ``` If coverage is below 80%: - Identify uncovered lines - Add tests for missing paths - Re-run coverage check ### Step 7: Document Deviations If implementation deviated from plan or introduced new dependencies: - Update tech-stack.md with new dependencies - Note deviations in plan.md task comments - Update spec.md if requirements changed ### Step 8: Commit Implementation Create a focused commit for the task: ```bash git add -A git commit -m "feat(user): implement email validation - Add validate_email method to User class - Handle empty and malformed emails - Add comprehensive test coverage Task: 2.1 Track: user-auth_20250115" ``` Commit message format: - Type: feat, fix, refactor, test, docs, chore - Scope: affected module or component - Summary: imperative, present tense - Body: bullet points of changes - Footer: task and track references ### Step 9: Attach Git Notes Add rich task summary as git note: ```bash git notes add -m "Task 2.1: Implement user validation Summary: - Added email validation using regex pattern - Handles edge cases: empty, no @, no domain - Coverage: 94% on validation module Files changed: - src/models/user.py (modified) - tests/test_user.py (modified) Decisions: - Used simple regex over email-validator library - Reason: No external dependency for basic validation" ``` ### Step 10: Update Plan with SHA Update plan.md to mark task complete with commit SHA: ```markdown - [x] **Task 2.1**: Implement user validation `abc1234` ``` ### Step 11: Commit Plan Update Commit the plan status update: ```bash git add conductor/tracks/*/plan.md git commit -m "docs: update plan - task 2.1 complete Track: user-auth_20250115" ``` ## Phase Completion Protocol When all tasks in a phase are complete, execute the verification protocol: ### Identify Changed Files List all files modified since the last checkpoint: ```bash git diff --name-only <last-checkpoint-sha>..HEAD ``` ### Ensure Test Coverage For each modified file: 1. Identify corresponding test file 2. Verify tests exist for new/changed code 3. Run coverage for modified modules 4. Add tests if coverage < 80% ### Run Full Test Suite Execute complete test suite: ```bash pytest -v --tb=short ``` All tests must pass before proceeding. ### Generate Manual Verification Steps Create checklist of manual verifications: ```markdown ## Phase 1 Verification Checklist - [ ] User can register with valid email - [ ] Invalid email shows appropriate error - [ ] Database stores user correctly - [ ] API returns expected response codes ``` ### WAIT for User Approval Present verification checklist to user: ``` Phase 1 complete. Please verify: 1. [ ] Test suite passes (automated) 2. [ ] Coverage meets target (automated) 3. [ ] Manual verification items (requires human) Respond with 'approved' to continue, or note issues. ``` Do NOT proceed without explicit approval. ### Create Checkpoint Commit After approval, create checkpoint commit: ```bash git add -A git commit -m "checkpoint: phase 1 complete - user-auth_20250115 Verified: - All tests passing - Coverage: 87% - Manual verification approved Phase 1 tasks: - [x] Task 1.1: Setup database schema - [x] Task 1.2: Implement user model - [x] Task 1.3: Add validation logic" ``` ### Record Checkpoint SHA Update plan.md checkpoints table: ```markdown ## Checkpoints | Phase | Checkpoint SHA | Date | Status | | ------- | -------------- | ---------- | -------- | | Phase 1 | def5678 | 2025-01-15 | verified | | Phase 2 | | | pending | ``` ## Quality Assurance Gates Before marking any task complete, verify these gates: ### Passing Tests - All existing tests pass - New tests pass - No test regressions ### Coverage >= 80% - New code has 80%+ coverage - Overall project coverage maintained - Critical paths fully covered ### Style Compliance - Code follows style guides - Linting passes - Formatting correct ### Documentation - Public APIs documented - Complex logic explained - README updated if needed ### Type Safety - Type hints present (if applicable) - Type checker passes - No type: ignore without reason ### No Linting Errors - Zero linter errors - Warnings addressed or justified - Static analysis clean ### Mobile Compatibility If applicable: - Responsive design verified - Touch interactions work - Performance acceptable ### Security Audit - No secrets in code - Input validation present - Authentication/authorization correct - Dependencies vulnerability-free ## Git Integration ### Commit Message Format ``` <type>(<scope>): <subject> <body> <footer> ``` Types: - `feat`: New feature - `fix`: Bug fix - `refactor`: Code change without feature/fix - `test`: Adding tests - `docs`: Documentation - `chore`: Maintenance ### Git Notes for Rich Summaries Attach detailed notes to commits: ```bash git notes add -m "<detailed summary>" ``` View notes: ```bash git log --show-notes ``` Benefits: - Preserves context without cluttering commit message - Enables semantic queries across commits - Supports track-based operations ### SHA Recording in plan.md Always record the commit SHA when completing tasks: ```markdown - [x] **Task 1.1**: Setup schema `abc1234` - [x] **Task 1.2**: Add model `def5678` ``` This enables: - Traceability from plan to code - Semantic revert operations - Progress auditing ## Verification Checkpoints ### Why Checkpoints Matter Checkpoints create restore points for semantic reversion: - Revert to end of any phase - Maintain logical code state - Enable safe experimentation ### When to Create Checkpoints Create checkpoint after: - All phase tasks complete - All phase verifications pass - User approval received ### Checkpoint Commit Content Include in checkpoint commit: - All uncommitted changes - Updated plan.md - Updated metadata.json - Any documentation updates ### How to Use Checkpoints For reverting: ```bash # Revert to end of Phase 1 git revert --no-commit <phase-2-commits>... git commit -m "revert: rollback to phase 1 checkpoint" ``` For review: ```bash # See what changed in Phase 2 git diff <phase-1-sha>..<phase-2-sha> ``` ## Handling Deviations During implementation, deviations from the plan may occur. Handle them systematically: ### Types of Deviations **Scope Addition** Discovered requirement not in original spec. - Document in spec.md as new requirement - Add tasks to plan.md - Note addition in task comments **Scope Reduction** Feature deemed unnecessary during implementation. - Mark tasks as `[-]` (skipped) with reason - Update spec.md scope section - Document decision rationale **Technical Deviation** Different implementation approach than planned. - Note deviation in task completion comment - Update tech-stack.md if dependencies changed - Document why original approach was unsuitable **Requirement Change** Understanding of requirement changes during work. - Update spec.md with corrected requirement - Adjust plan.md tasks if needed - Re-verify acceptance criteria ### Deviation Documentation Format When completing a task with deviation: ```markdown - [x] **Task 2.1**: Implement validation `abc1234` - DEVIATION: Used library instead of custom code - Reason: Better edge case handling - Impact: Added email-validator to dependencies ``` ## Error Recovery ### Failed Tests After GREEN If tests fail after reaching GREEN: 1. Do NOT proceed to REFACTOR 2. Identify which test started failing 3. Check if refactoring broke something 4. Revert to last known GREEN state 5. Re-approach the implementation ### Checkpoint Rejection If user rejects a checkpoint: 1. Note rejection reason in plan.md 2. Create tasks to address issues 3. Complete remediation tasks 4. Request checkpoint approval again ### Blocked by Dependency If task cannot proceed: 1. Mark task as `[!]` with blocker description 2. Check if other tasks can proceed 3. Document expected resolution timeline 4. Consider creating dependency resolution track ## TDD Variations by Task Type ### Data Model Tasks ``` RED: Write test for model creation and validation GREEN: Implement model class with fields REFACTOR: Add computed properties, improve types ``` ### API Endpoint Tasks ``` RED: Write test for request/response contract GREEN: Implement endpoint handler REFACTOR: Extract validation, improve error handling ``` ### Integration Tasks ``` RED: Write test for component interaction GREEN: Wire components together REFACTOR: Improve error propagation, add logging ``` ### Refactoring Tasks ``` RED: Add characterization tests for current behavior GREEN: Apply refactoring (tests should stay green) REFACTOR: Clean up any introduced complexity ``` ## Working with Existing Tests When modifying code with existing tests: ### Extend, Don't Replace - Keep existing tests passing - Add new tests for new behavior - Update tests only when requirements change ### Test Migration When refactoring changes test structure: 1. Run existing tests (should pass) 2. Add new tests for refactored code 3. Migrate test cases to new structure 4. Remove old tests only after new tests pass ### Regression Prevention After any change: 1. Run full test suite 2. Check for unexpected failures 3. Investigate any new failures 4. Fix regressions before proceeding ## Checkpoint Verification Details ### Automated Verification Run before requesting approval: ```bash # Test suite pytest -v --tb=short # Coverage pytest --cov=src --cov-report=term-missing # Linting ruff check src/ tests/ # Type checking (if applicable) mypy src/ ``` ### Manual Verification Guidance For manual items, provide specific instructions: ```markdown ## Manual Verification Steps ### User Registration 1. Navigate to /register 2. Enter valid email: test@example.com 3. Enter password meeting requirements 4. Click Submit 5. Verify success message appears 6. Verify user appears in database ### Error Handling 1. Enter invalid email: "notanemail" 2. Verify error message shows 3. Verify form retains other entered data ``` ## Performance Considerations ### Test Suite Performance Keep test suite fast: - Use fixtures to avoid redundant setup - Mock slow external calls - Run subset during development, full suite at checkpoints ### Commit Performance Keep commits atomic: - One logical change per commit - Complete thought, not work-in-progress - Tests should pass after every commit ## Best Practices 1. **Never skip RED**: Always write failing tests first 2. **Small commits**: One logical change per commit 3. **Immediate updates**: Update plan.md right after task completion 4. **Wait for approval**: Never skip checkpoint verification 5. **Rich git notes**: Include context that helps future understanding 6. **Coverage discipline**: Don't accept coverage below target 7. **Quality gates**: Check all gates before marking complete 8. **Sequential phases**: Complete phases in order 9. **Document deviations**: Note any changes from original plan 10. **Clean state**: Each commit should leave code in working state 11. **Fast feedback**: Run relevant tests frequently during development 12. **Clear blockers**: Address blockers promptly, don't work around them
šŸ‘0
šŸ‘ļø0
šŸ¤– Auto-discovered
šŸ¤–system prompt•7 months ago

dbt-transformation-patterns

Master dbt (data build tool) for analytics engineering with model

data
⭐1
# dbt Transformation Patterns Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing. ## When to Use This Skill - Building data transformation pipelines with dbt - Organizing models into staging, intermediate, and marts layers - Implementing data quality tests - Creating incremental models for large datasets - Documenting data models and lineage - Setting up dbt project structure ## Core Concepts ### 1. Model Layers (Medallion Architecture) ``` sources/ Raw data definitions ↓ staging/ 1:1 with source, light cleaning ↓ intermediate/ Business logic, joins, aggregations ↓ marts/ Final analytics tables ``` ### 2. Naming Conventions | Layer | Prefix | Example | | ------------ | -------------- | ----------------------------- | | Staging | `stg_` | `stg_stripe__payments` | | Intermediate | `int_` | `int_payments_pivoted` | | Marts | `dim_`, `fct_` | `dim_customers`, `fct_orders` | ## Quick Start ```yaml # dbt_project.yml name: "analytics" version: "1.0.0" profile: "analytics" model-paths: ["models"] analysis-paths: ["analyses"] test-paths: ["tests"] seed-paths: ["seeds"] macro-paths: ["macros"] vars: start_date: "2020-01-01" models: analytics: staging: +materialized: view +schema: staging intermediate: +materialized: ephemeral marts: +materialized: table +schema: analytics ``` ``` # Project structure models/ ā”œā”€ā”€ staging/ │ ā”œā”€ā”€ stripe/ │ │ ā”œā”€ā”€ _stripe__sources.yml │ │ ā”œā”€ā”€ _stripe__models.yml │ │ ā”œā”€ā”€ stg_stripe__customers.sql │ │ └── stg_stripe__payments.sql │ └── shopify/ │ ā”œā”€ā”€ _shopify__sources.yml │ └── stg_shopify__orders.sql ā”œā”€ā”€ intermediate/ │ └── finance/ │ └── int_payments_pivoted.sql └── marts/ ā”œā”€ā”€ core/ │ ā”œā”€ā”€ _core__models.yml │ ā”œā”€ā”€ dim_customers.sql │ └── fct_orders.sql └── finance/ └── fct_revenue.sql ``` ## Patterns ### Pattern 1: Source Definitions ```yaml # models/staging/stripe/_stripe__sources.yml version: 2 sources: - name: stripe description: Raw Stripe data loaded via Fivetran database: raw schema: stripe loader: fivetran loaded_at_field: _fivetran_synced freshness: warn_after: { count: 12, period: hour } error_after: { count: 24, period: hour } tables: - name: customers description: Stripe customer records columns: - name: id description: Primary key tests: - unique - not_null - name: email description: Customer email - name: created description: Account creation timestamp - name: payments description: Stripe payment transactions columns: - name: id tests: - unique - not_null - name: customer_id tests: - not_null - relationships: to: source('stripe', 'customers') field: id ``` ### Pattern 2: Staging Models ```sql -- models/staging/stripe/stg_stripe__customers.sql with source as ( select * from {{ source('stripe', 'customers') }} ), renamed as ( select -- ids id as customer_id, -- strings lower(email) as email, name as customer_name, -- timestamps created as created_at, -- metadata _fivetran_synced as _loaded_at from source ) select * from renamed ``` ```sql -- models/staging/stripe/stg_stripe__payments.sql {{ config( materialized='incremental', unique_key='payment_id', on_schema_change='append_new_columns' ) }} with source as ( select * from {{ source('stripe', 'payments') }} {% if is_incremental() %} where _fivetran_synced > (select max(_loaded_at) from {{ this }}) {% endif %} ), renamed as ( select -- ids id as payment_id, customer_id, invoice_id, -- amounts (convert cents to dollars) amount / 100.0 as amount, amount_refunded / 100.0 as amount_refunded, -- status status as payment_status, -- timestamps created as created_at, -- metadata _fivetran_synced as _loaded_at from source ) select * from renamed ``` ### Pattern 3: Intermediate Models ```sql -- models/intermediate/finance/int_payments_pivoted_to_customer.sql with payments as ( select * from {{ ref('stg_stripe__payments') }} ), customers as ( select * from {{ ref('stg_stripe__customers') }} ), payment_summary as ( select customer_id, count(*) as total_payments, count(case when payment_status = 'succeeded' then 1 end) as successful_payments, sum(case when payment_status = 'succeeded' then amount else 0 end) as total_amount_paid, min(created_at) as first_payment_at, max(created_at) as last_payment_at from payments group by customer_id ) select customers.customer_id, customers.email, customers.created_at as customer_created_at, coalesce(payment_summary.total_payments, 0) as total_payments, coalesce(payment_summary.successful_payments, 0) as successful_payments, coalesce(payment_summary.total_amount_paid, 0) as lifetime_value, payment_summary.first_payment_at, payment_summary.last_payment_at from customers left join payment_summary using (customer_id) ``` ### Pattern 4: Mart Models (Dimensions and Facts) ```sql -- models/marts/core/dim_customers.sql {{ config( materialized='table', unique_key='customer_id' ) }} with customers as ( select * from {{ ref('int_payments_pivoted_to_customer') }} ), orders as ( select * from {{ ref('stg_shopify__orders') }} ), order_summary as ( select customer_id, count(*) as total_orders, sum(total_price) as total_order_value, min(created_at) as first_order_at, max(created_at) as last_order_at from orders group by customer_id ), final as ( select -- surrogate key {{ dbt_utils.generate_surrogate_key(['customers.customer_id']) }} as customer_key, -- natural key customers.customer_id, -- attributes customers.email, customers.customer_created_at, -- payment metrics customers.total_payments, customers.successful_payments, customers.lifetime_value, customers.first_payment_at, customers.last_payment_at, -- order metrics coalesce(order_summary.total_orders, 0) as total_orders, coalesce(order_summary.total_order_value, 0) as total_order_value, order_summary.first_order_at, order_summary.last_order_at, -- calculated fields case when customers.lifetime_value >= 1000 then 'high' when customers.lifetime_value >= 100 then 'medium' else 'low' end as customer_tier, -- timestamps current_timestamp as _loaded_at from customers left join order_summary using (customer_id) ) select * from final ``` ```sql -- models/marts/core/fct_orders.sql {{ config( materialized='incremental', unique_key='order_id', incremental_strategy='merge' ) }} with orders as ( select * from {{ ref('stg_shopify__orders') }} {% if is_incremental() %} where updated_at > (select max(updated_at) from {{ this }}) {% endif %} ), customers as ( select * from {{ ref('dim_customers') }} ), final as ( select -- keys orders.order_id, customers.customer_key, orders.customer_id, -- dimensions orders.order_status, orders.fulfillment_status, orders.payment_status, -- measures orders.subtotal, orders.tax, orders.shipping, orders.total_price, orders.total_discount, orders.item_count, -- timestamps orders.created_at, orders.updated_at, orders.fulfilled_at, -- metadata current_timestamp as _loaded_at from orders left join customers on orders.customer_id = customers.customer_id ) select * from final ``` ### Pattern 5: Testing and Documentation ```yaml # models/marts/core/_core__models.yml version: 2 models: - name: dim_customers description: Customer dimension with payment and order metrics columns: - name: customer_key description: Surrogate key for the customer dimension tests: - unique - not_null - name: customer_id description: Natural key from source system tests: - unique - not_null - name: email description: Customer email address tests: - not_null - name: customer_tier description: Customer value tier based on lifetime value tests: - accepted_values: values: ["high", "medium", "low"] - name: lifetime_value description: Total amount paid by customer tests: - dbt_utils.expression_is_true: expression: ">= 0" - name: fct_orders description: Order fact table with all order transactions tests: - dbt_utils.recency: datepart: day field: created_at interval: 1 columns: - name: order_id tests: - unique - not_null - name: customer_key tests: - not_null - relationships: to: ref('dim_customers') field: customer_key ``` ### Pattern 6: Macros and DRY Code ```sql -- macros/cents_to_dollars.sql {% macro cents_to_dollars(column_name, precision=2) %} round({{ column_name }} / 100.0, {{ precision }}) {% endmacro %} -- macros/generate_schema_name.sql {% macro generate_schema_name(custom_schema_name, node) %} {%- set default_schema = target.schema -%} {%- if custom_schema_name is none -%} {{ default_schema }} {%- else -%} {{ default_schema }}_{{ custom_schema_name }} {%- endif -%} {% endmacro %} -- macros/limit_data_in_dev.sql {% macro limit_data_in_dev(column_name, days=3) %} {% if target.name == 'dev' %} where {{ column_name }} >= dateadd(day, -{{ days }}, current_date) {% endif %} {% endmacro %} -- Usage in model select * from {{ ref('stg_orders') }} {{ limit_data_in_dev('created_at') }} ``` ### Pattern 7: Incremental Strategies ```sql -- Delete+Insert (default for most warehouses) {{ config( materialized='incremental', unique_key='id', incremental_strategy='delete+insert' ) }} -- Merge (best for late-arriving data) {{ config( materialized='incremental', unique_key='id', incremental_strategy='merge', merge_update_columns=['status', 'amount', 'updated_at'] ) }} -- Insert Overwrite (partition-based) {{ config( materialized='incremental', incremental_strategy='insert_overwrite', partition_by={ "field": "created_date", "data_type": "date", "granularity": "day" } ) }} select *, date(created_at) as created_date from {{ ref('stg_events') }} {% if is_incremental() %} where created_date >= dateadd(day, -3, current_date) {% endif %} ``` ## dbt Commands ```bash # Development dbt run # Run all models dbt run --select staging # Run staging models only dbt run --select +fct_orders # Run fct_orders and its upstream dbt run --select fct_orders+ # Run fct_orders and its downstream dbt run --full-refresh # Rebuild incremental models # Testing dbt test # Run all tests dbt test --select stg_stripe # Test specific models dbt build # Run + test in DAG order # Documentation dbt docs generate # Generate docs dbt docs serve # Serve docs locally # Debugging dbt compile # Compile SQL without running dbt debug # Test connection dbt ls --select tag:critical # List models by tag ``` ## Best Practices ### Do's - **Use staging layer** - Clean data once, use everywhere - **Test aggressively** - Not null, unique, relationships - **Document everything** - Column descriptions, model descriptions - **Use incremental** - For tables > 1M rows - **Version control** - dbt project in Git ### Don'ts - **Don't skip staging** - Raw → mart is tech debt - **Don't hardcode dates** - Use `{{ var('start_date') }}` - **Don't repeat logic** - Extract to macros - **Don't test in prod** - Use dev target - **Don't ignore freshness** - Monitor source data ## Resources - [dbt Documentation](https://docs.getdbt.com/) - [dbt Best Practices](https://docs.getdbt.com/guides/best-practices) - [dbt-utils Package](https://hub.getdbt.com/dbt-labs/dbt_utils/latest/) - [dbt Discourse](https://discourse.getdbt.com/)
šŸ‘0
šŸ‘ļø0
šŸ¤– Auto-discovered
šŸ¤–system prompt•7 months ago

workflow-orchestration-patterns

Design durable workflows with Temporal for distributed systems.

coding
⭐1
# Workflow Orchestration Patterns Master workflow orchestration architecture with Temporal, covering fundamental design decisions, resilience patterns, and best practices for building reliable distributed systems. ## When to Use Workflow Orchestration ### Ideal Use Cases (Source: docs.temporal.io) - **Multi-step processes** spanning machines/services/databases - **Distributed transactions** requiring all-or-nothing semantics - **Long-running workflows** (hours to years) with automatic state persistence - **Failure recovery** that must resume from last successful step - **Business processes**: bookings, orders, campaigns, approvals - **Entity lifecycle management**: inventory tracking, account management, cart workflows - **Infrastructure automation**: CI/CD pipelines, provisioning, deployments - **Human-in-the-loop** systems requiring timeouts and escalations ### When NOT to Use - Simple CRUD operations (use direct API calls) - Pure data processing pipelines (use Airflow, batch processing) - Stateless request/response (use standard APIs) - Real-time streaming (use Kafka, event processors) ## Critical Design Decision: Workflows vs Activities **The Fundamental Rule** (Source: temporal.io/blog/workflow-engine-principles): - **Workflows** = Orchestration logic and decision-making - **Activities** = External interactions (APIs, databases, network calls) ### Workflows (Orchestration) **Characteristics:** - Contain business logic and coordination - **MUST be deterministic** (same inputs → same outputs) - **Cannot** perform direct external calls - State automatically preserved across failures - Can run for years despite infrastructure failures **Example workflow tasks:** - Decide which steps to execute - Handle compensation logic - Manage timeouts and retries - Coordinate child workflows ### Activities (External Interactions) **Characteristics:** - Handle all external system interactions - Can be non-deterministic (API calls, DB writes) - Include built-in timeouts and retry logic - **Must be idempotent** (calling N times = calling once) - Short-lived (seconds to minutes typically) **Example activity tasks:** - Call payment gateway API - Write to database - Send emails or notifications - Query external services ### Design Decision Framework ``` Does it touch external systems? → Activity Is it orchestration/decision logic? → Workflow ``` ## Core Workflow Patterns ### 1. Saga Pattern with Compensation **Purpose**: Implement distributed transactions with rollback capability **Pattern** (Source: temporal.io/blog/compensating-actions-part-of-a-complete-breakfast-with-sagas): ``` For each step: 1. Register compensation BEFORE executing 2. Execute the step (via activity) 3. On failure, run all compensations in reverse order (LIFO) ``` **Example: Payment Workflow** 1. Reserve inventory (compensation: release inventory) 2. Charge payment (compensation: refund payment) 3. Fulfill order (compensation: cancel fulfillment) **Critical Requirements:** - Compensations must be idempotent - Register compensation BEFORE executing step - Run compensations in reverse order - Handle partial failures gracefully ### 2. Entity Workflows (Actor Model) **Purpose**: Long-lived workflow representing single entity instance **Pattern** (Source: docs.temporal.io/evaluate/use-cases-design-patterns): - One workflow execution = one entity (cart, account, inventory item) - Workflow persists for entity lifetime - Receives signals for state changes - Supports queries for current state **Example Use Cases:** - Shopping cart (add items, checkout, expiration) - Bank account (deposits, withdrawals, balance checks) - Product inventory (stock updates, reservations) **Benefits:** - Encapsulates entity behavior - Guarantees consistency per entity - Natural event sourcing ### 3. Fan-Out/Fan-In (Parallel Execution) **Purpose**: Execute multiple tasks in parallel, aggregate results **Pattern:** - Spawn child workflows or parallel activities - Wait for all to complete - Aggregate results - Handle partial failures **Scaling Rule** (Source: temporal.io/blog/workflow-engine-principles): - Don't scale individual workflows - For 1M tasks: spawn 1K child workflows Ɨ 1K tasks each - Keep each workflow bounded ### 4. Async Callback Pattern **Purpose**: Wait for external event or human approval **Pattern:** - Workflow sends request and waits for signal - External system processes asynchronously - Sends signal to resume workflow - Workflow continues with response **Use Cases:** - Human approval workflows - Webhook callbacks - Long-running external processes ## State Management and Determinism ### Automatic State Preservation **How Temporal Works** (Source: docs.temporal.io/workflows): - Complete program state preserved automatically - Event History records every command and event - Seamless recovery from crashes - Applications restore pre-failure state ### Determinism Constraints **Workflows Execute as State Machines**: - Replay behavior must be consistent - Same inputs → identical outputs every time **Prohibited in Workflows** (Source: docs.temporal.io/workflows): - āŒ Threading, locks, synchronization primitives - āŒ Random number generation (`random()`) - āŒ Global state or static variables - āŒ System time (`datetime.now()`) - āŒ Direct file I/O or network calls - āŒ Non-deterministic libraries **Allowed in Workflows**: - āœ… `workflow.now()` (deterministic time) - āœ… `workflow.random()` (deterministic random) - āœ… Pure functions and calculations - āœ… Calling activities (non-deterministic operations) ### Versioning Strategies **Challenge**: Changing workflow code while old executions still running **Solutions**: 1. **Versioning API**: Use `workflow.get_version()` for safe changes 2. **New Workflow Type**: Create new workflow, route new executions to it 3. **Backward Compatibility**: Ensure old events replay correctly ## Resilience and Error Handling ### Retry Policies **Default Behavior**: Temporal retries activities forever **Configure Retry**: - Initial retry interval - Backoff coefficient (exponential backoff) - Maximum interval (cap retry delay) - Maximum attempts (eventually fail) **Non-Retryable Errors**: - Invalid input (validation failures) - Business rule violations - Permanent failures (resource not found) ### Idempotency Requirements **Why Critical** (Source: docs.temporal.io/activities): - Activities may execute multiple times - Network failures trigger retries - Duplicate execution must be safe **Implementation Strategies**: - Idempotency keys (deduplication) - Check-then-act with unique constraints - Upsert operations instead of insert - Track processed request IDs ### Activity Heartbeats **Purpose**: Detect stalled long-running activities **Pattern**: - Activity sends periodic heartbeat - Includes progress information - Timeout if no heartbeat received - Enables progress-based retry ## Best Practices ### Workflow Design 1. **Keep workflows focused** - Single responsibility per workflow 2. **Small workflows** - Use child workflows for scalability 3. **Clear boundaries** - Workflow orchestrates, activities execute 4. **Test locally** - Use time-skipping test environment ### Activity Design 1. **Idempotent operations** - Safe to retry 2. **Short-lived** - Seconds to minutes, not hours 3. **Timeout configuration** - Always set timeouts 4. **Heartbeat for long tasks** - Report progress 5. **Error handling** - Distinguish retryable vs non-retryable ### Common Pitfalls **Workflow Violations**: - Using `datetime.now()` instead of `workflow.now()` - Threading or async operations in workflow code - Calling external APIs directly from workflow - Non-deterministic logic in workflows **Activity Mistakes**: - Non-idempotent operations (can't handle retries) - Missing timeouts (activities run forever) - No error classification (retry validation errors) - Ignoring payload limits (2MB per argument) ### Operational Considerations **Monitoring**: - Workflow execution duration - Activity failure rates - Retry attempts and backoff - Pending workflow counts **Scalability**: - Horizontal scaling with workers - Task queue partitioning - Child workflow decomposition - Activity batching when appropriate ## Additional Resources **Official Documentation**: - Temporal Core Concepts: docs.temporal.io/workflows - Workflow Patterns: docs.temporal.io/evaluate/use-cases-design-patterns - Best Practices: docs.temporal.io/develop/best-practices - Saga Pattern: temporal.io/blog/saga-pattern-made-easy **Key Principles**: 1. Workflows = orchestration, Activities = external calls 2. Determinism is non-negotiable for workflows 3. Idempotency is critical for activities 4. State preservation is automatic 5. Design for failure and recovery
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šŸ¤– Auto-discovered
šŸ¤–system prompt•7 months ago

architecture-decision-records

Write and maintain Architecture Decision Records (ADRs) following

coding
⭐1
# Architecture Decision Records Comprehensive patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions. ## When to Use This Skill - Making significant architectural decisions - Documenting technology choices - Recording design trade-offs - Onboarding new team members - Reviewing historical decisions - Establishing decision-making processes ## Core Concepts ### 1. What is an ADR? An Architecture Decision Record captures: - **Context**: Why we needed to make a decision - **Decision**: What we decided - **Consequences**: What happens as a result ### 2. When to Write an ADR | Write ADR | Skip ADR | | -------------------------- | ---------------------- | | New framework adoption | Minor version upgrades | | Database technology choice | Bug fixes | | API design patterns | Implementation details | | Security architecture | Routine maintenance | | Integration patterns | Configuration changes | ### 3. ADR Lifecycle ``` Proposed → Accepted → Deprecated → Superseded ↓ Rejected ``` ## Templates ### Template 1: Standard ADR (MADR Format) ```markdown # ADR-0001: Use PostgreSQL as Primary Database ## Status Accepted ## Context We need to select a primary database for our new e-commerce platform. The system will handle: - ~10,000 concurrent users - Complex product catalog with hierarchical categories - Transaction processing for orders and payments - Full-text search for products - Geospatial queries for store locator The team has experience with MySQL, PostgreSQL, and MongoDB. We need ACID compliance for financial transactions. ## Decision Drivers - **Must have ACID compliance** for payment processing - **Must support complex queries** for reporting - **Should support full-text search** to reduce infrastructure complexity - **Should have good JSON support** for flexible product attributes - **Team familiarity** reduces onboarding time ## Considered Options ### Option 1: PostgreSQL - **Pros**: ACID compliant, excellent JSON support (JSONB), built-in full-text search, PostGIS for geospatial, team has experience - **Cons**: Slightly more complex replication setup than MySQL ### Option 2: MySQL - **Pros**: Very familiar to team, simple replication, large community - **Cons**: Weaker JSON support, no built-in full-text search (need Elasticsearch), no geospatial without extensions ### Option 3: MongoDB - **Pros**: Flexible schema, native JSON, horizontal scaling - **Cons**: No ACID for multi-document transactions (at decision time), team has limited experience, requires schema design discipline ## Decision We will use **PostgreSQL 15** as our primary database. ## Rationale PostgreSQL provides the best balance of: 1. **ACID compliance** essential for e-commerce transactions 2. **Built-in capabilities** (full-text search, JSONB, PostGIS) reduce infrastructure complexity 3. **Team familiarity** with SQL databases reduces learning curve 4. **Mature ecosystem** with excellent tooling and community support The slight complexity in replication is outweighed by the reduction in additional services (no separate Elasticsearch needed). ## Consequences ### Positive - Single database handles transactions, search, and geospatial queries - Reduced operational complexity (fewer services to manage) - Strong consistency guarantees for financial data - Team can leverage existing SQL expertise ### Negative - Need to learn PostgreSQL-specific features (JSONB, full-text search syntax) - Vertical scaling limits may require read replicas sooner - Some team members need PostgreSQL-specific training ### Risks - Full-text search may not scale as well as dedicated search engines - Mitigation: Design for potential Elasticsearch addition if needed ## Implementation Notes - Use JSONB for flexible product attributes - Implement connection pooling with PgBouncer - Set up streaming replication for read replicas - Use pg_trgm extension for fuzzy search ## Related Decisions - ADR-0002: Caching Strategy (Redis) - complements database choice - ADR-0005: Search Architecture - may supersede if Elasticsearch needed ## References - [PostgreSQL JSON Documentation](https://www.postgresql.org/docs/current/datatype-json.html) - [PostgreSQL Full Text Search](https://www.postgresql.org/docs/current/textsearch.html) - Internal: Performance benchmarks in `/docs/benchmarks/database-comparison.md` ``` ### Template 2: Lightweight ADR ```markdown # ADR-0012: Adopt TypeScript for Frontend Development **Status**: Accepted **Date**: 2024-01-15 **Deciders**: @alice, @bob, @charlie ## Context Our React codebase has grown to 50+ components with increasing bug reports related to prop type mismatches and undefined errors. PropTypes provide runtime-only checking. ## Decision Adopt TypeScript for all new frontend code. Migrate existing code incrementally. ## Consequences **Good**: Catch type errors at compile time, better IDE support, self-documenting code. **Bad**: Learning curve for team, initial slowdown, build complexity increase. **Mitigations**: TypeScript training sessions, allow gradual adoption with `allowJs: true`. ``` ### Template 3: Y-Statement Format ```markdown # ADR-0015: API Gateway Selection In the context of **building a microservices architecture**, facing **the need for centralized API management, authentication, and rate limiting**, we decided for **Kong Gateway** and against **AWS API Gateway and custom Nginx solution**, to achieve **vendor independence, plugin extensibility, and team familiarity with Lua**, accepting that **we need to manage Kong infrastructure ourselves**. ``` ### Template 4: ADR for Deprecation ```markdown # ADR-0020: Deprecate MongoDB in Favor of PostgreSQL ## Status Accepted (Supersedes ADR-0003) ## Context ADR-0003 (2021) chose MongoDB for user profile storage due to schema flexibility needs. Since then: - MongoDB's multi-document transactions remain problematic for our use case - Our schema has stabilized and rarely changes - We now have PostgreSQL expertise from other services - Maintaining two databases increases operational burden ## Decision Deprecate MongoDB and migrate user profiles to PostgreSQL. ## Migration Plan 1. **Phase 1** (Week 1-2): Create PostgreSQL schema, dual-write enabled 2. **Phase 2** (Week 3-4): Backfill historical data, validate consistency 3. **Phase 3** (Week 5): Switch reads to PostgreSQL, monitor 4. **Phase 4** (Week 6): Remove MongoDB writes, decommission ## Consequences ### Positive - Single database technology reduces operational complexity - ACID transactions for user data - Team can focus PostgreSQL expertise ### Negative - Migration effort (~4 weeks) - Risk of data issues during migration - Lose some schema flexibility ## Lessons Learned Document from ADR-0003 experience: - Schema flexibility benefits were overestimated - Operational cost of multiple databases was underestimated - Consider long-term maintenance in technology decisions ``` ### Template 5: Request for Comments (RFC) Style ```markdown # RFC-0025: Adopt Event Sourcing for Order Management ## Summary Propose adopting event sourcing pattern for the order management domain to improve auditability, enable temporal queries, and support business analytics. ## Motivation Current challenges: 1. Audit requirements need complete order history 2. "What was the order state at time X?" queries are impossible 3. Analytics team needs event stream for real-time dashboards 4. Order state reconstruction for customer support is manual ## Detailed Design ### Event Store ``` OrderCreated { orderId, customerId, items[], timestamp } OrderItemAdded { orderId, item, timestamp } OrderItemRemoved { orderId, itemId, timestamp } PaymentReceived { orderId, amount, paymentId, timestamp } OrderShipped { orderId, trackingNumber, timestamp } ``` ### Projections - **CurrentOrderState**: Materialized view for queries - **OrderHistory**: Complete timeline for audit - **DailyOrderMetrics**: Analytics aggregation ### Technology - Event Store: EventStoreDB (purpose-built, handles projections) - Alternative considered: Kafka + custom projection service ## Drawbacks - Learning curve for team - Increased complexity vs. CRUD - Need to design events carefully (immutable once stored) - Storage growth (events never deleted) ## Alternatives 1. **Audit tables**: Simpler but doesn't enable temporal queries 2. **CDC from existing DB**: Complex, doesn't change data model 3. **Hybrid**: Event source only for order state changes ## Unresolved Questions - [ ] Event schema versioning strategy - [ ] Retention policy for events - [ ] Snapshot frequency for performance ## Implementation Plan 1. Prototype with single order type (2 weeks) 2. Team training on event sourcing (1 week) 3. Full implementation and migration (4 weeks) 4. Monitoring and optimization (ongoing) ## References - [Event Sourcing by Martin Fowler](https://martinfowler.com/eaaDev/EventSourcing.html) - [EventStoreDB Documentation](https://www.eventstore.com/docs) ``` ## ADR Management ### Directory Structure ``` docs/ ā”œā”€ā”€ adr/ │ ā”œā”€ā”€ README.md # Index and guidelines │ ā”œā”€ā”€ template.md # Team's ADR template │ ā”œā”€ā”€ 0001-use-postgresql.md │ ā”œā”€ā”€ 0002-caching-strategy.md │ ā”œā”€ā”€ 0003-mongodb-user-profiles.md # [DEPRECATED] │ └── 0020-deprecate-mongodb.md # Supersedes 0003 ``` ### ADR Index (README.md) ```markdown # Architecture Decision Records This directory contains Architecture Decision Records (ADRs) for [Project Name]. ## Index | ADR | Title | Status | Date | | ------------------------------------- | ---------------------------------- | ---------- | ---------- | | [0001](0001-use-postgresql.md) | Use PostgreSQL as Primary Database | Accepted | 2024-01-10 | | [0002](0002-caching-strategy.md) | Caching Strategy with Redis | Accepted | 2024-01-12 | | [0003](0003-mongodb-user-profiles.md) | MongoDB for User Profiles | Deprecated | 2023-06-15 | | [0020](0020-deprecate-mongodb.md) | Deprecate MongoDB | Accepted | 2024-01-15 | ## Creating a New ADR 1. Copy `template.md` to `NNNN-title-with-dashes.md` 2. Fill in the template 3. Submit PR for review 4. Update this index after approval ## ADR Status - **Proposed**: Under discussion - **Accepted**: Decision made, implementing - **Deprecated**: No longer relevant - **Superseded**: Replaced by another ADR - **Rejected**: Considered but not adopted ``` ### Automation (adr-tools) ```bash # Install adr-tools brew install adr-tools # Initialize ADR directory adr init docs/adr # Create new ADR adr new "Use PostgreSQL as Primary Database" # Supersede an ADR adr new -s 3 "Deprecate MongoDB in Favor of PostgreSQL" # Generate table of contents adr generate toc > docs/adr/README.md # Link related ADRs adr link 2 "Complements" 1 "Is complemented by" ``` ## Review Process ```markdown ## ADR Review Checklist ### Before Submission - [ ] Context clearly explains the problem - [ ] All viable options considered - [ ] Pros/cons balanced and honest - [ ] Consequences (positive and negative) documented - [ ] Related ADRs linked ### During Review - [ ] At least 2 senior engineers reviewed - [ ] Affected teams consulted - [ ] Security implications considered - [ ] Cost implications documented - [ ] Reversibility assessed ### After Acceptance - [ ] ADR index updated - [ ] Team notified - [ ] Implementation tickets created - [ ] Related documentation updated ``` ## Best Practices ### Do's - **Write ADRs early** - Before implementation starts - **Keep them short** - 1-2 pages maximum - **Be honest about trade-offs** - Include real cons - **Link related decisions** - Build decision graph - **Update status** - Deprecate when superseded ### Don'ts - **Don't change accepted ADRs** - Write new ones to supersede - **Don't skip context** - Future readers need background - **Don't hide failures** - Rejected decisions are valuable - **Don't be vague** - Specific decisions, specific consequences - **Don't forget implementation** - ADR without action is waste ## Resources - [Documenting Architecture Decisions (Michael Nygard)](https://cognitect.com/blog/2011/11/15/documenting-architecture-decisions) - [MADR Template](https://adr.github.io/madr/) - [ADR GitHub Organization](https://adr.github.io/) - [adr-tools](https://github.com/npryce/adr-tools)
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šŸ¤– Auto-discovered
šŸ¤–system prompt•7 months ago

e2e-testing-patterns

Master end-to-end testing with Playwright and Cypress to build

coding
⭐1
# E2E Testing Patterns Build reliable, fast, and maintainable end-to-end test suites that provide confidence to ship code quickly and catch regressions before users do. ## When to Use This Skill - Implementing end-to-end test automation - Debugging flaky or unreliable tests - Testing critical user workflows - Setting up CI/CD test pipelines - Testing across multiple browsers - Validating accessibility requirements - Testing responsive designs - Establishing E2E testing standards ## Core Concepts ### 1. E2E Testing Fundamentals **What to Test with E2E:** - Critical user journeys (login, checkout, signup) - Complex interactions (drag-and-drop, multi-step forms) - Cross-browser compatibility - Real API integration - Authentication flows **What NOT to Test with E2E:** - Unit-level logic (use unit tests) - API contracts (use integration tests) - Edge cases (too slow) - Internal implementation details ### 2. Test Philosophy **The Testing Pyramid:** ``` /\ /E2E\ ← Few, focused on critical paths /─────\ /Integr\ ← More, test component interactions /────────\ /Unit Tests\ ← Many, fast, isolated /────────────\ ``` **Best Practices:** - Test user behavior, not implementation - Keep tests independent - Make tests deterministic - Optimize for speed - Use data-testid, not CSS selectors ## Playwright Patterns ### Setup and Configuration ```typescript // playwright.config.ts import { defineConfig, devices } from "@playwright/test"; export default defineConfig({ testDir: "./e2e", timeout: 30000, expect: { timeout: 5000, }, fullyParallel: true, forbidOnly: !!process.env.CI, retries: process.env.CI ? 2 : 0, workers: process.env.CI ? 1 : undefined, reporter: [["html"], ["junit", { outputFile: "results.xml" }]], use: { baseURL: "http://localhost:3000", trace: "on-first-retry", screenshot: "only-on-failure", video: "retain-on-failure", }, projects: [ { name: "chromium", use: { ...devices["Desktop Chrome"] } }, { name: "firefox", use: { ...devices["Desktop Firefox"] } }, { name: "webkit", use: { ...devices["Desktop Safari"] } }, { name: "mobile", use: { ...devices["iPhone 13"] } }, ], }); ``` ### Pattern 1: Page Object Model ```typescript // pages/LoginPage.ts import { Page, Locator } from "@playwright/test"; export class LoginPage { readonly page: Page; readonly emailInput: Locator; readonly passwordInput: Locator; readonly loginButton: Locator; readonly errorMessage: Locator; constructor(page: Page) { this.page = page; this.emailInput = page.getByLabel("Email"); this.passwordInput = page.getByLabel("Password"); this.loginButton = page.getByRole("button", { name: "Login" }); this.errorMessage = page.getByRole("alert"); } async goto() { await this.page.goto("/login"); } async login(email: string, password: string) { await this.emailInput.fill(email); await this.passwordInput.fill(password); await this.loginButton.click(); } async getErrorMessage(): Promise<string> { return (await this.errorMessage.textContent()) ?? ""; } } // Test using Page Object import { test, expect } from "@playwright/test"; import { LoginPage } from "./pages/LoginPage"; test("successful login", async ({ page }) => { const loginPage = new LoginPage(page); await loginPage.goto(); await loginPage.login("user@example.com", "password123"); await expect(page).toHaveURL("/dashboard"); await expect(page.getByRole("heading", { name: "Dashboard" })).toBeVisible(); }); test("failed login shows error", async ({ page }) => { const loginPage = new LoginPage(page); await loginPage.goto(); await loginPage.login("invalid@example.com", "wrong"); const error = await loginPage.getErrorMessage(); expect(error).toContain("Invalid credentials"); }); ``` ### Pattern 2: Fixtures for Test Data ```typescript // fixtures/test-data.ts import { test as base } from "@playwright/test"; type TestData = { testUser: { email: string; password: string; name: string; }; adminUser: { email: string; password: string; }; }; export const test = base.extend<TestData>({ testUser: async ({}, use) => { const user = { email: `test-${Date.now()}@example.com`, password: "Test123!@#", name: "Test User", }; // Setup: Create user in database await createTestUser(user); await use(user); // Teardown: Clean up user await deleteTestUser(user.email); }, adminUser: async ({}, use) => { await use({ email: "admin@example.com", password: process.env.ADMIN_PASSWORD!, }); }, }); // Usage in tests import { test } from "./fixtures/test-data"; test("user can update profile", async ({ page, testUser }) => { await page.goto("/login"); await page.getByLabel("Email").fill(testUser.email); await page.getByLabel("Password").fill(testUser.password); await page.getByRole("button", { name: "Login" }).click(); await page.goto("/profile"); await page.getByLabel("Name").fill("Updated Name"); await page.getByRole("button", { name: "Save" }).click(); await expect(page.getByText("Profile updated")).toBeVisible(); }); ``` ### Pattern 3: Waiting Strategies ```typescript // āŒ Bad: Fixed timeouts await page.waitForTimeout(3000); // Flaky! // āœ… Good: Wait for specific conditions await page.waitForLoadState("networkidle"); await page.waitForURL("/dashboard"); await page.waitForSelector('[data-testid="user-profile"]'); // āœ… Better: Auto-waiting with assertions await expect(page.getByText("Welcome")).toBeVisible(); await expect(page.getByRole("button", { name: "Submit" })).toBeEnabled(); // Wait for API response const responsePromise = page.waitForResponse( (response) => response.url().includes("/api/users") && response.status() === 200, ); await page.getByRole("button", { name: "Load Users" }).click(); const response = await responsePromise; const data = await response.json(); expect(data.users).toHaveLength(10); // Wait for multiple conditions await Promise.all([ page.waitForURL("/success"), page.waitForLoadState("networkidle"), expect(page.getByText("Payment successful")).toBeVisible(), ]); ``` ### Pattern 4: Network Mocking and Interception ```typescript // Mock API responses test("displays error when API fails", async ({ page }) => { await page.route("**/api/users", (route) => { route.fulfill({ status: 500, contentType: "application/json", body: JSON.stringify({ error: "Internal Server Error" }), }); }); await page.goto("/users"); await expect(page.getByText("Failed to load users")).toBeVisible(); }); // Intercept and modify requests test("can modify API request", async ({ page }) => { await page.route("**/api/users", async (route) => { const request = route.request(); const postData = JSON.parse(request.postData() || "{}"); // Modify request postData.role = "admin"; await route.continue({ postData: JSON.stringify(postData), }); }); // Test continues... }); // Mock third-party services test("payment flow with mocked Stripe", async ({ page }) => { await page.route("**/api/stripe/**", (route) => { route.fulfill({ status: 200, body: JSON.stringify({ id: "mock_payment_id", status: "succeeded", }), }); }); // Test payment flow with mocked response }); ``` ## Cypress Patterns ### Setup and Configuration ```typescript // cypress.config.ts import { defineConfig } from "cypress"; export default defineConfig({ e2e: { baseUrl: "http://localhost:3000", viewportWidth: 1280, viewportHeight: 720, video: false, screenshotOnRunFailure: true, defaultCommandTimeout: 10000, requestTimeout: 10000, setupNodeEvents(on, config) { // Implement node event listeners }, }, }); ``` ### Pattern 1: Custom Commands ```typescript // cypress/support/commands.ts declare global { namespace Cypress { interface Chainable { login(email: string, password: string): Chainable<void>; createUser(userData: UserData): Chainable<User>; dataCy(value: string): Chainable<JQuery<HTMLElement>>; } } } Cypress.Commands.add("login", (email: string, password: string) => { cy.visit("/login"); cy.get('[data-testid="email"]').type(email); cy.get('[data-testid="password"]').type(password); cy.get('[data-testid="login-button"]').click(); cy.url().should("include", "/dashboard"); }); Cypress.Commands.add("createUser", (userData: UserData) => { return cy.request("POST", "/api/users", userData).its("body"); }); Cypress.Commands.add("dataCy", (value: string) => { return cy.get(`[data-cy="${value}"]`); }); // Usage cy.login("user@example.com", "password"); cy.dataCy("submit-button").click(); ``` ### Pattern 2: Cypress Intercept ```typescript // Mock API calls cy.intercept("GET", "/api/users", { statusCode: 200, body: [ { id: 1, name: "John" }, { id: 2, name: "Jane" }, ], }).as("getUsers"); cy.visit("/users"); cy.wait("@getUsers"); cy.get('[data-testid="user-list"]').children().should("have.length", 2); // Modify responses cy.intercept("GET", "/api/users", (req) => { req.reply((res) => { // Modify response res.body.users = res.body.users.slice(0, 5); res.send(); }); }); // Simulate slow network cy.intercept("GET", "/api/data", (req) => { req.reply((res) => { res.delay(3000); // 3 second delay res.send(); }); }); ``` ## Advanced Patterns ### Pattern 1: Visual Regression Testing ```typescript // With Playwright import { test, expect } from "@playwright/test"; test("homepage looks correct", async ({ page }) => { await page.goto("/"); await expect(page).toHaveScreenshot("homepage.png", { fullPage: true, maxDiffPixels: 100, }); }); test("button in all states", async ({ page }) => { await page.goto("/components"); const button = page.getByRole("button", { name: "Submit" }); // Default state await expect(button).toHaveScreenshot("button-default.png"); // Hover state await button.hover(); await expect(button).toHaveScreenshot("button-hover.png"); // Disabled state await button.evaluate((el) => el.setAttribute("disabled", "true")); await expect(button).toHaveScreenshot("button-disabled.png"); }); ``` ### Pattern 2: Parallel Testing with Sharding ```typescript // playwright.config.ts export default defineConfig({ projects: [ { name: "shard-1", use: { ...devices["Desktop Chrome"] }, grepInvert: /@slow/, shard: { current: 1, total: 4 }, }, { name: "shard-2", use: { ...devices["Desktop Chrome"] }, shard: { current: 2, total: 4 }, }, // ... more shards ], }); // Run in CI // npx playwright test --shard=1/4 // npx playwright test --shard=2/4 ``` ### Pattern 3: Accessibility Testing ```typescript // Install: npm install @axe-core/playwright import { test, expect } from "@playwright/test"; import AxeBuilder from "@axe-core/playwright"; test("page should not have accessibility violations", async ({ page }) => { await page.goto("/"); const accessibilityScanResults = await new AxeBuilder({ page }) .exclude("#third-party-widget") .analyze(); expect(accessibilityScanResults.violations).toEqual([]); }); test("form is accessible", async ({ page }) => { await page.goto("/signup"); const results = await new AxeBuilder({ page }).include("form").analyze(); expect(results.violations).toEqual([]); }); ``` ## Best Practices 1. **Use Data Attributes**: `data-testid` or `data-cy` for stable selectors 2. **Avoid Brittle Selectors**: Don't rely on CSS classes or DOM structure 3. **Test User Behavior**: Click, type, see - not implementation details 4. **Keep Tests Independent**: Each test should run in isolation 5. **Clean Up Test Data**: Create and destroy test data in each test 6. **Use Page Objects**: Encapsulate page logic 7. **Meaningful Assertions**: Check actual user-visible behavior 8. **Optimize for Speed**: Mock when possible, parallel execution ```typescript // āŒ Bad selectors cy.get(".btn.btn-primary.submit-button").click(); cy.get("div > form > div:nth-child(2) > input").type("text"); // āœ… Good selectors cy.getByRole("button", { name: "Submit" }).click(); cy.getByLabel("Email address").type("user@example.com"); cy.get('[data-testid="email-input"]').type("user@example.com"); ``` ## Common Pitfalls - **Flaky Tests**: Use proper waits, not fixed timeouts - **Slow Tests**: Mock external APIs, use parallel execution - **Over-Testing**: Don't test every edge case with E2E - **Coupled Tests**: Tests should not depend on each other - **Poor Selectors**: Avoid CSS classes and nth-child - **No Cleanup**: Clean up test data after each test - **Testing Implementation**: Test user behavior, not internals ## Debugging Failing Tests ```typescript // Playwright debugging // 1. Run in headed mode npx playwright test --headed // 2. Run in debug mode npx playwright test --debug // 3. Use trace viewer await page.screenshot({ path: 'screenshot.png' }); await page.video()?.saveAs('video.webm'); // 4. Add test.step for better reporting test('checkout flow', async ({ page }) => { await test.step('Add item to cart', async () => { await page.goto('/products'); await page.getByRole('button', { name: 'Add to Cart' }).click(); }); await test.step('Proceed to checkout', async () => { await page.goto('/cart'); await page.getByRole('button', { name: 'Checkout' }).click(); }); }); // 5. Inspect page state await page.pause(); // Pauses execution, opens inspector ``` ## Resources - **references/playwright-best-practices.md**: Playwright-specific patterns - **references/cypress-best-practices.md**: Cypress-specific patterns - **references/flaky-test-debugging.md**: Debugging unreliable tests - **assets/e2e-testing-checklist.md**: What to test with E2E - **assets/selector-strategies.md**: Finding reliable selectors - **scripts/test-analyzer.ts**: Analyze test flakiness and duration
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šŸ¤– Auto-discovered
šŸ¤–system prompt•7 months ago

kpi-dashboard-design

Design effective KPI dashboards with metrics selection,

coding
⭐1
# KPI Dashboard Design Comprehensive patterns for designing effective Key Performance Indicator (KPI) dashboards that drive business decisions. ## When to Use This Skill - Designing executive dashboards - Selecting meaningful KPIs - Building real-time monitoring displays - Creating department-specific metrics views - Improving existing dashboard layouts - Establishing metric governance ## Core Concepts ### 1. KPI Framework | Level | Focus | Update Frequency | Audience | | --------------- | ---------------- | ----------------- | ---------- | | **Strategic** | Long-term goals | Monthly/Quarterly | Executives | | **Tactical** | Department goals | Weekly/Monthly | Managers | | **Operational** | Day-to-day | Real-time/Daily | Teams | ### 2. SMART KPIs ``` Specific: Clear definition Measurable: Quantifiable Achievable: Realistic targets Relevant: Aligned to goals Time-bound: Defined period ``` ### 3. Dashboard Hierarchy ``` ā”œā”€ā”€ Executive Summary (1 page) │ ā”œā”€ā”€ 4-6 headline KPIs │ ā”œā”€ā”€ Trend indicators │ └── Key alerts ā”œā”€ā”€ Department Views │ ā”œā”€ā”€ Sales Dashboard │ ā”œā”€ā”€ Marketing Dashboard │ ā”œā”€ā”€ Operations Dashboard │ └── Finance Dashboard └── Detailed Drilldowns ā”œā”€ā”€ Individual metrics └── Root cause analysis ``` ## Common KPIs by Department ### Sales KPIs ```yaml Revenue Metrics: - Monthly Recurring Revenue (MRR) - Annual Recurring Revenue (ARR) - Average Revenue Per User (ARPU) - Revenue Growth Rate Pipeline Metrics: - Sales Pipeline Value - Win Rate - Average Deal Size - Sales Cycle Length Activity Metrics: - Calls/Emails per Rep - Demos Scheduled - Proposals Sent - Close Rate ``` ### Marketing KPIs ```yaml Acquisition: - Cost Per Acquisition (CPA) - Customer Acquisition Cost (CAC) - Lead Volume - Marketing Qualified Leads (MQL) Engagement: - Website Traffic - Conversion Rate - Email Open/Click Rate - Social Engagement ROI: - Marketing ROI - Campaign Performance - Channel Attribution - CAC Payback Period ``` ### Product KPIs ```yaml Usage: - Daily/Monthly Active Users (DAU/MAU) - Session Duration - Feature Adoption Rate - Stickiness (DAU/MAU) Quality: - Net Promoter Score (NPS) - Customer Satisfaction (CSAT) - Bug/Issue Count - Time to Resolution Growth: - User Growth Rate - Activation Rate - Retention Rate - Churn Rate ``` ### Finance KPIs ```yaml Profitability: - Gross Margin - Net Profit Margin - EBITDA - Operating Margin Liquidity: - Current Ratio - Quick Ratio - Cash Flow - Working Capital Efficiency: - Revenue per Employee - Operating Expense Ratio - Days Sales Outstanding - Inventory Turnover ``` ## Dashboard Layout Patterns ### Pattern 1: Executive Summary ``` ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā” │ EXECUTIVE DASHBOARD [Date Range ā–¼] │ ā”œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¬ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¬ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¬ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¤ │ REVENUE │ PROFIT │ CUSTOMERS │ NPS SCORE │ │ $2.4M │ $450K │ 12,450 │ 72 │ │ ā–² 12% │ ā–² 8% │ ā–² 15% │ ā–² 5pts │ ā”œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”“ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”“ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”“ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¤ │ │ │ Revenue Trend │ Revenue by Product │ │ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā” │ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā” │ │ │ /\ /\ │ │ │ ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ 45% │ │ │ │ / \ / \ /\ │ │ │ ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ 32% │ │ │ │ / \/ \ / \ │ │ │ ā–ˆā–ˆā–ˆā–ˆ 18% │ │ │ │ / \/ \ │ │ │ ā–ˆā–ˆ 5% │ │ │ ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜ │ ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜ │ │ │ ā”œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¤ │ šŸ”“ Alert: Churn rate exceeded threshold (>5%) │ │ 🟔 Warning: Support ticket volume 20% above average │ ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜ ``` ### Pattern 2: SaaS Metrics Dashboard ``` ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā” │ SAAS METRICS Jan 2024 [Monthly ā–¼] │ ā”œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¬ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¤ │ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā” │ MRR GROWTH │ │ │ MRR │ │ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā” │ │ │ $125,000 │ │ │ /── │ │ │ │ ā–² 8% │ │ │ /────/ │ │ │ ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜ │ │ /────/ │ │ │ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā” │ │ /────/ │ │ │ │ ARR │ │ │ /────/ │ │ │ │ $1,500,000 │ │ ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜ │ │ │ ā–² 15% │ │ J F M A M J J A S O N D │ │ ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜ │ │ ā”œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¼ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¤ │ UNIT ECONOMICS │ COHORT RETENTION │ │ │ │ │ CAC: $450 │ Month 1: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ 100% │ │ LTV: $2,700 │ Month 3: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ 85% │ │ LTV/CAC: 6.0x │ Month 6: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ 80% │ │ │ Month 12: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ 72% │ │ Payback: 4 months │ │ ā”œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”“ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¤ │ CHURN ANALYSIS │ │ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¬ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¬ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¬ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā” │ │ │ Gross │ Net │ Logo │ Expansion │ │ │ │ 4.2% │ 1.8% │ 3.1% │ 2.4% │ │ │ ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”“ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”“ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”“ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜ │ ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜ ``` ### Pattern 3: Real-time Operations ``` ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā” │ OPERATIONS CENTER Live ā— Last: 10:42:15 │ ā”œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¬ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¤ │ SYSTEM HEALTH │ SERVICE STATUS │ │ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā” │ │ │ │ CPU MEM DISK │ │ ā— API Gateway Healthy │ │ │ 45% 72% 58% │ │ ā— User Service Healthy │ │ │ ā–ˆā–ˆā–ˆ ā–ˆā–ˆā–ˆā–ˆ ā–ˆā–ˆā–ˆ │ │ ā— Payment Service Degraded │ │ │ ā–ˆā–ˆā–ˆ ā–ˆā–ˆā–ˆā–ˆ ā–ˆā–ˆā–ˆ │ │ ā— Database Healthy │ │ │ ā–ˆā–ˆā–ˆ ā–ˆā–ˆā–ˆā–ˆ ā–ˆā–ˆā–ˆ │ │ ā— Cache Healthy │ │ ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜ │ │ ā”œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¼ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¤ │ REQUEST THROUGHPUT │ ERROR RATE │ │ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā” │ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā” │ │ │ ā–ā–‚ā–ƒā–„ā–…ā–†ā–‡ā–ˆā–‡ā–†ā–…ā–„ā–ƒā–‚ā–ā–‚ā–ƒā–„ā–… │ │ │ ▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁ │ │ │ ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜ │ ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜ │ │ Current: 12,450 req/s │ Current: 0.02% │ │ Peak: 18,200 req/s │ Threshold: 1.0% │ ā”œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”“ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¤ │ RECENT ALERTS │ │ 10:40 🟔 High latency on payment-service (p99 > 500ms) │ │ 10:35 🟢 Resolved: Database connection pool recovered │ │ 10:22 šŸ”“ Payment service circuit breaker tripped │ ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜ ``` ## Implementation Patterns ### SQL for KPI Calculations ```sql -- Monthly Recurring Revenue (MRR) WITH mrr_calculation AS ( SELECT DATE_TRUNC('month', billing_date) AS month, SUM( CASE subscription_interval WHEN 'monthly' THEN amount WHEN 'yearly' THEN amount / 12 WHEN 'quarterly' THEN amount / 3 END ) AS mrr FROM subscriptions WHERE status = 'active' GROUP BY DATE_TRUNC('month', billing_date) ) SELECT month, mrr, LAG(mrr) OVER (ORDER BY month) AS prev_mrr, (mrr - LAG(mrr) OVER (ORDER BY month)) / LAG(mrr) OVER (ORDER BY month) * 100 AS growth_pct FROM mrr_calculation; -- Cohort Retention WITH cohorts AS ( SELECT user_id, DATE_TRUNC('month', created_at) AS cohort_month FROM users ), activity AS ( SELECT user_id, DATE_TRUNC('month', event_date) AS activity_month FROM user_events WHERE event_type = 'active_session' ) SELECT c.cohort_month, EXTRACT(MONTH FROM age(a.activity_month, c.cohort_month)) AS months_since_signup, COUNT(DISTINCT a.user_id) AS active_users, COUNT(DISTINCT a.user_id)::FLOAT / COUNT(DISTINCT c.user_id) * 100 AS retention_rate FROM cohorts c LEFT JOIN activity a ON c.user_id = a.user_id AND a.activity_month >= c.cohort_month GROUP BY c.cohort_month, EXTRACT(MONTH FROM age(a.activity_month, c.cohort_month)) ORDER BY c.cohort_month, months_since_signup; -- Customer Acquisition Cost (CAC) SELECT DATE_TRUNC('month', acquired_date) AS month, SUM(marketing_spend) / NULLIF(COUNT(new_customers), 0) AS cac, SUM(marketing_spend) AS total_spend, COUNT(new_customers) AS customers_acquired FROM ( SELECT DATE_TRUNC('month', u.created_at) AS acquired_date, u.id AS new_customers, m.spend AS marketing_spend FROM users u JOIN marketing_spend m ON DATE_TRUNC('month', u.created_at) = m.month WHERE u.source = 'marketing' ) acquisition GROUP BY DATE_TRUNC('month', acquired_date); ``` ### Python Dashboard Code (Streamlit) ```python import streamlit as st import pandas as pd import plotly.express as px import plotly.graph_objects as go st.set_page_config(page_title="KPI Dashboard", layout="wide") # Header with date filter col1, col2 = st.columns([3, 1]) with col1: st.title("Executive Dashboard") with col2: date_range = st.selectbox( "Period", ["Last 7 Days", "Last 30 Days", "Last Quarter", "YTD"] ) # KPI Cards def metric_card(label, value, delta, prefix="", suffix=""): delta_color = "green" if delta >= 0 else "red" delta_arrow = "ā–²" if delta >= 0 else "ā–¼" st.metric( label=label, value=f"{prefix}{value:,.0f}{suffix}", delta=f"{delta_arrow} {abs(delta):.1f}%" ) col1, col2, col3, col4 = st.columns(4) with col1: metric_card("Revenue", 2400000, 12.5, prefix="$") with col2: metric_card("Customers", 12450, 15.2) with col3: metric_card("NPS Score", 72, 5.0) with col4: metric_card("Churn Rate", 4.2, -0.8, suffix="%") # Charts col1, col2 = st.columns(2) with col1: st.subheader("Revenue Trend") revenue_data = pd.DataFrame({ 'Month': pd.date_range('2024-01-01', periods=12, freq='M'), 'Revenue': [180000, 195000, 210000, 225000, 240000, 255000, 270000, 285000, 300000, 315000, 330000, 345000] }) fig = px.line(revenue_data, x='Month', y='Revenue', line_shape='spline', markers=True) fig.update_layout(height=300) st.plotly_chart(fig, use_container_width=True) with col2: st.subheader("Revenue by Product") product_data = pd.DataFrame({ 'Product': ['Enterprise', 'Professional', 'Starter', 'Other'], 'Revenue': [45, 32, 18, 5] }) fig = px.pie(product_data, values='Revenue', names='Product', hole=0.4) fig.update_layout(height=300) st.plotly_chart(fig, use_container_width=True) # Cohort Heatmap st.subheader("Cohort Retention") cohort_data = pd.DataFrame({ 'Cohort': ['Jan', 'Feb', 'Mar', 'Apr', 'May'], 'M0': [100, 100, 100, 100, 100], 'M1': [85, 87, 84, 86, 88], 'M2': [78, 80, 76, 79, None], 'M3': [72, 74, 70, None, None], 'M4': [68, 70, None, None, None], }) fig = go.Figure(data=go.Heatmap( z=cohort_data.iloc[:, 1:].values, x=['M0', 'M1', 'M2', 'M3', 'M4'], y=cohort_data['Cohort'], colorscale='Blues', text=cohort_data.iloc[:, 1:].values, texttemplate='%{text}%', textfont={"size": 12}, )) fig.update_layout(height=250) st.plotly_chart(fig, use_container_width=True) # Alerts Section st.subheader("Alerts") alerts = [ {"level": "error", "message": "Churn rate exceeded threshold (>5%)"}, {"level": "warning", "message": "Support ticket volume 20% above average"}, ] for alert in alerts: if alert["level"] == "error": st.error(f"šŸ”“ {alert['message']}") elif alert["level"] == "warning": st.warning(f"🟔 {alert['message']}") ``` ## Best Practices ### Do's - **Limit to 5-7 KPIs** - Focus on what matters - **Show context** - Comparisons, trends, targets - **Use consistent colors** - Red=bad, green=good - **Enable drilldown** - From summary to detail - **Update appropriately** - Match metric frequency ### Don'ts - **Don't show vanity metrics** - Focus on actionable data - **Don't overcrowd** - White space aids comprehension - **Don't use 3D charts** - They distort perception - **Don't hide methodology** - Document calculations - **Don't ignore mobile** - Ensure responsive design ## Resources - [Stephen Few's Dashboard Design](https://www.perceptualedge.com/articles/visual_business_intelligence/rules_for_using_color.pdf) - [Edward Tufte's Principles](https://www.edwardtufte.com/tufte/) - [Google Data Studio Gallery](https://datastudio.google.com/gallery)
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šŸ‘ļø0
šŸ¤– Auto-discovered
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changelog-automation

Automate changelog generation from commits, PRs, and releases

coding
⭐1
# Changelog Automation Patterns and tools for automating changelog generation, release notes, and version management following industry standards. ## When to Use This Skill - Setting up automated changelog generation - Implementing Conventional Commits - Creating release note workflows - Standardizing commit message formats - Generating GitHub/GitLab release notes - Managing semantic versioning ## Core Concepts ### 1. Keep a Changelog Format ```markdown # Changelog All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). ## [Unreleased] ### Added - New feature X ## [1.2.0] - 2024-01-15 ### Added - User profile avatars - Dark mode support ### Changed - Improved loading performance by 40% ### Deprecated - Old authentication API (use v2) ### Removed - Legacy payment gateway ### Fixed - Login timeout issue (#123) ### Security - Updated dependencies for CVE-2024-1234 [Unreleased]: https://github.com/user/repo/compare/v1.2.0...HEAD [1.2.0]: https://github.com/user/repo/compare/v1.1.0...v1.2.0 ``` ### 2. Conventional Commits ``` <type>[optional scope]: <description> [optional body] [optional footer(s)] ``` | Type | Description | Changelog Section | | ---------- | ---------------- | ------------------ | | `feat` | New feature | Added | | `fix` | Bug fix | Fixed | | `docs` | Documentation | (usually excluded) | | `style` | Formatting | (usually excluded) | | `refactor` | Code restructure | Changed | | `perf` | Performance | Changed | | `test` | Tests | (usually excluded) | | `chore` | Maintenance | (usually excluded) | | `ci` | CI changes | (usually excluded) | | `build` | Build system | (usually excluded) | | `revert` | Revert commit | Removed | ### 3. Semantic Versioning ``` MAJOR.MINOR.PATCH MAJOR: Breaking changes (feat! or BREAKING CHANGE) MINOR: New features (feat) PATCH: Bug fixes (fix) ``` ## Implementation ### Method 1: Conventional Changelog (Node.js) ```bash # Install tools npm install -D @commitlint/cli @commitlint/config-conventional npm install -D husky npm install -D standard-version # or npm install -D semantic-release # Setup commitlint cat > commitlint.config.js << 'EOF' module.exports = { extends: ['@commitlint/config-conventional'], rules: { 'type-enum': [ 2, 'always', [ 'feat', 'fix', 'docs', 'style', 'refactor', 'perf', 'test', 'chore', 'ci', 'build', 'revert', ], ], 'subject-case': [2, 'never', ['start-case', 'pascal-case', 'upper-case']], 'subject-max-length': [2, 'always', 72], }, }; EOF # Setup husky npx husky init echo "npx --no -- commitlint --edit \$1" > .husky/commit-msg ``` ### Method 2: standard-version Configuration ```javascript // .versionrc.js module.exports = { types: [ { type: "feat", section: "Features" }, { type: "fix", section: "Bug Fixes" }, { type: "perf", section: "Performance Improvements" }, { type: "revert", section: "Reverts" }, { type: "docs", section: "Documentation", hidden: true }, { type: "style", section: "Styles", hidden: true }, { type: "chore", section: "Miscellaneous", hidden: true }, { type: "refactor", section: "Code Refactoring", hidden: true }, { type: "test", section: "Tests", hidden: true }, { type: "build", section: "Build System", hidden: true }, { type: "ci", section: "CI/CD", hidden: true }, ], commitUrlFormat: "{{host}}/{{owner}}/{{repository}}/commit/{{hash}}", compareUrlFormat: "{{host}}/{{owner}}/{{repository}}/compare/{{previousTag}}...{{currentTag}}", issueUrlFormat: "{{host}}/{{owner}}/{{repository}}/issues/{{id}}", userUrlFormat: "{{host}}/{{user}}", releaseCommitMessageFormat: "chore(release): {{currentTag}}", scripts: { prebump: 'echo "Running prebump"', postbump: 'echo "Running postbump"', prechangelog: 'echo "Running prechangelog"', postchangelog: 'echo "Running postchangelog"', }, }; ``` ```json // package.json scripts { "scripts": { "release": "standard-version", "release:minor": "standard-version --release-as minor", "release:major": "standard-version --release-as major", "release:patch": "standard-version --release-as patch", "release:dry": "standard-version --dry-run" } } ``` ### Method 3: semantic-release (Full Automation) ```javascript // release.config.js module.exports = { branches: [ "main", { name: "beta", prerelease: true }, { name: "alpha", prerelease: true }, ], plugins: [ "@semantic-release/commit-analyzer", "@semantic-release/release-notes-generator", [ "@semantic-release/changelog", { changelogFile: "CHANGELOG.md", }, ], [ "@semantic-release/npm", { npmPublish: true, }, ], [ "@semantic-release/github", { assets: ["dist/**/*.js", "dist/**/*.css"], }, ], [ "@semantic-release/git", { assets: ["CHANGELOG.md", "package.json"], message: "chore(release): ${nextRelease.version} [skip ci]\n\n${nextRelease.notes}", }, ], ], }; ``` ### Method 4: GitHub Actions Workflow ```yaml # .github/workflows/release.yml name: Release on: push: branches: [main] workflow_dispatch: inputs: release_type: description: "Release type" required: true default: "patch" type: choice options: - patch - minor - major permissions: contents: write pull-requests: write jobs: release: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 with: fetch-depth: 0 token: ${{ secrets.GITHUB_TOKEN }} - uses: actions/setup-node@v4 with: node-version: "20" cache: "npm" - run: npm ci - name: Configure Git run: | git config user.name "github-actions[bot]" git config user.email "github-actions[bot]@users.noreply.github.com" - name: Run semantic-release env: GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} NPM_TOKEN: ${{ secrets.NPM_TOKEN }} run: npx semantic-release # Alternative: manual release with standard-version manual-release: if: github.event_name == 'workflow_dispatch' runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 with: fetch-depth: 0 - uses: actions/setup-node@v4 with: node-version: "20" - run: npm ci - name: Configure Git run: | git config user.name "github-actions[bot]" git config user.email "github-actions[bot]@users.noreply.github.com" - name: Bump version and generate changelog run: npx standard-version --release-as ${{ inputs.release_type }} - name: Push changes run: git push --follow-tags origin main - name: Create GitHub Release uses: softprops/action-gh-release@v1 with: tag_name: ${{ steps.version.outputs.tag }} body_path: RELEASE_NOTES.md generate_release_notes: true ``` ### Method 5: git-cliff (Rust-based, Fast) ```toml # cliff.toml [changelog] header = """ # Changelog All notable changes to this project will be documented in this file. """ body = """ {% if version %}\ ## [{{ version | trim_start_matches(pat="v") }}] - {{ timestamp | date(format="%Y-%m-%d") }} {% else %}\ ## [Unreleased] {% endif %}\ {% for group, commits in commits | group_by(attribute="group") %} ### {{ group | upper_first }} {% for commit in commits %} - {% if commit.scope %}**{{ commit.scope }}:** {% endif %}\ {{ commit.message | upper_first }}\ {% if commit.github.pr_number %} ([#{{ commit.github.pr_number }}](https://github.com/owner/repo/pull/{{ commit.github.pr_number }})){% endif %}\ {% endfor %} {% endfor %} """ footer = """ {% for release in releases -%} {% if release.version -%} {% if release.previous.version -%} [{{ release.version | trim_start_matches(pat="v") }}]: \ https://github.com/owner/repo/compare/{{ release.previous.version }}...{{ release.version }} {% endif -%} {% else -%} [unreleased]: https://github.com/owner/repo/compare/{{ release.previous.version }}...HEAD {% endif -%} {% endfor %} """ trim = true [git] conventional_commits = true filter_unconventional = true split_commits = false commit_parsers = [ { message = "^feat", group = "Features" }, { message = "^fix", group = "Bug Fixes" }, { message = "^doc", group = "Documentation" }, { message = "^perf", group = "Performance" }, { message = "^refactor", group = "Refactoring" }, { message = "^style", group = "Styling" }, { message = "^test", group = "Testing" }, { message = "^chore\\(release\\)", skip = true }, { message = "^chore", group = "Miscellaneous" }, ] filter_commits = false tag_pattern = "v[0-9]*" skip_tags = "" ignore_tags = "" topo_order = false sort_commits = "oldest" [github] owner = "owner" repo = "repo" ``` ```bash # Generate changelog git cliff -o CHANGELOG.md # Generate for specific range git cliff v1.0.0..v2.0.0 -o RELEASE_NOTES.md # Preview without writing git cliff --unreleased --dry-run ``` ### Method 6: Python (commitizen) ```toml # pyproject.toml [tool.commitizen] name = "cz_conventional_commits" version = "1.0.0" version_files = [ "pyproject.toml:version", "src/__init__.py:__version__", ] tag_format = "v$version" update_changelog_on_bump = true changelog_incremental = true changelog_start_rev = "v0.1.0" [tool.commitizen.customize] message_template = "{{change_type}}{% if scope %}({{scope}}){% endif %}: {{message}}" schema = "<type>(<scope>): <subject>" schema_pattern = "^(feat|fix|docs|style|refactor|perf|test|chore)(\\(\\w+\\))?:\\s.*" bump_pattern = "^(feat|fix|perf|refactor)" bump_map = {"feat" = "MINOR", "fix" = "PATCH", "perf" = "PATCH", "refactor" = "PATCH"} ``` ```bash # Install pip install commitizen # Create commit interactively cz commit # Bump version and update changelog cz bump --changelog # Check commits cz check --rev-range HEAD~5..HEAD ``` ## Release Notes Templates ### GitHub Release Template ```markdown ## What's Changed ### šŸš€ Features {{ range .Features }} - {{ .Title }} by @{{ .Author }} in #{{ .PR }} {{ end }} ### šŸ› Bug Fixes {{ range .Fixes }} - {{ .Title }} by @{{ .Author }} in #{{ .PR }} {{ end }} ### šŸ“š Documentation {{ range .Docs }} - {{ .Title }} by @{{ .Author }} in #{{ .PR }} {{ end }} ### šŸ”§ Maintenance {{ range .Chores }} - {{ .Title }} by @{{ .Author }} in #{{ .PR }} {{ end }} ## New Contributors {{ range .NewContributors }} - @{{ .Username }} made their first contribution in #{{ .PR }} {{ end }} **Full Changelog**: https://github.com/owner/repo/compare/v{{ .Previous }}...v{{ .Current }} ``` ### Internal Release Notes ```markdown # Release v2.1.0 - January 15, 2024 ## Summary This release introduces dark mode support and improves checkout performance by 40%. It also includes important security updates. ## Highlights ### šŸŒ™ Dark Mode Users can now switch to dark mode from settings. The preference is automatically saved and synced across devices. ### ⚔ Performance - Checkout flow is 40% faster - Reduced bundle size by 15% ## Breaking Changes None in this release. ## Upgrade Guide No special steps required. Standard deployment process applies. ## Known Issues - Dark mode may flicker on initial load (fix scheduled for v2.1.1) ## Dependencies Updated | Package | From | To | Reason | | ------- | ------- | ------- | ------------------------ | | react | 18.2.0 | 18.3.0 | Performance improvements | | lodash | 4.17.20 | 4.17.21 | Security patch | ``` ## Commit Message Examples ```bash # Feature with scope feat(auth): add OAuth2 support for Google login # Bug fix with issue reference fix(checkout): resolve race condition in payment processing Closes #123 # Breaking change feat(api)!: change user endpoint response format BREAKING CHANGE: The user endpoint now returns `userId` instead of `id`. Migration guide: Update all API consumers to use the new field name. # Multiple paragraphs fix(database): handle connection timeouts gracefully Previously, connection timeouts would cause the entire request to fail without retry. This change implements exponential backoff with up to 3 retries before failing. The timeout threshold has been increased from 5s to 10s based on p99 latency analysis. Fixes #456 Reviewed-by: @alice ``` ## Best Practices ### Do's - **Follow Conventional Commits** - Enables automation - **Write clear messages** - Future you will thank you - **Reference issues** - Link commits to tickets - **Use scopes consistently** - Define team conventions - **Automate releases** - Reduce manual errors ### Don'ts - **Don't mix changes** - One logical change per commit - **Don't skip validation** - Use commitlint - **Don't manual edit** - Generated changelogs only - **Don't forget breaking changes** - Mark with `!` or footer - **Don't ignore CI** - Validate commits in pipeline ## Resources - [Keep a Changelog](https://keepachangelog.com/) - [Conventional Commits](https://www.conventionalcommits.org/) - [Semantic Versioning](https://semver.org/) - [semantic-release](https://semantic-release.gitbook.io/) - [git-cliff](https://git-cliff.org/)
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šŸ¤–system prompt•7 months ago

debugging-strategies

Master systematic debugging techniques, profiling tools, and root

coding
⭐1
# Debugging Strategies Transform debugging from frustrating guesswork into systematic problem-solving with proven strategies, powerful tools, and methodical approaches. ## When to Use This Skill - Tracking down elusive bugs - Investigating performance issues - Understanding unfamiliar codebases - Debugging production issues - Analyzing crash dumps and stack traces - Profiling application performance - Investigating memory leaks - Debugging distributed systems ## Core Principles ### 1. The Scientific Method **1. Observe**: What's the actual behavior? **2. Hypothesize**: What could be causing it? **3. Experiment**: Test your hypothesis **4. Analyze**: Did it prove/disprove your theory? **5. Repeat**: Until you find the root cause ### 2. Debugging Mindset **Don't Assume:** - "It can't be X" - Yes it can - "I didn't change Y" - Check anyway - "It works on my machine" - Find out why **Do:** - Reproduce consistently - Isolate the problem - Keep detailed notes - Question everything - Take breaks when stuck ### 3. Rubber Duck Debugging Explain your code and problem out loud (to a rubber duck, colleague, or yourself). Often reveals the issue. ## Systematic Debugging Process ### Phase 1: Reproduce ```markdown ## Reproduction Checklist 1. **Can you reproduce it?** - Always? Sometimes? Randomly? - Specific conditions needed? - Can others reproduce it? 2. **Create minimal reproduction** - Simplify to smallest example - Remove unrelated code - Isolate the problem 3. **Document steps** - Write down exact steps - Note environment details - Capture error messages ``` ### Phase 2: Gather Information ```markdown ## Information Collection 1. **Error Messages** - Full stack trace - Error codes - Console/log output 2. **Environment** - OS version - Language/runtime version - Dependencies versions - Environment variables 3. **Recent Changes** - Git history - Deployment timeline - Configuration changes 4. **Scope** - Affects all users or specific ones? - All browsers or specific ones? - Production only or also dev? ``` ### Phase 3: Form Hypothesis ```markdown ## Hypothesis Formation Based on gathered info, ask: 1. **What changed?** - Recent code changes - Dependency updates - Infrastructure changes 2. **What's different?** - Working vs broken environment - Working vs broken user - Before vs after 3. **Where could this fail?** - Input validation - Business logic - Data layer - External services ``` ### Phase 4: Test & Verify ```markdown ## Testing Strategies 1. **Binary Search** - Comment out half the code - Narrow down problematic section - Repeat until found 2. **Add Logging** - Strategic console.log/print - Track variable values - Trace execution flow 3. **Isolate Components** - Test each piece separately - Mock dependencies - Remove complexity 4. **Compare Working vs Broken** - Diff configurations - Diff environments - Diff data ``` ## Debugging Tools ### JavaScript/TypeScript Debugging ```typescript // Chrome DevTools Debugger function processOrder(order: Order) { debugger; // Execution pauses here const total = calculateTotal(order); console.log("Total:", total); // Conditional breakpoint if (order.items.length > 10) { debugger; // Only breaks if condition true } return total; } // Console debugging techniques console.log("Value:", value); // Basic console.table(arrayOfObjects); // Table format console.time("operation"); /* code */ console.timeEnd("operation"); // Timing console.trace(); // Stack trace console.assert(value > 0, "Value must be positive"); // Assertion // Performance profiling performance.mark("start-operation"); // ... operation code performance.mark("end-operation"); performance.measure("operation", "start-operation", "end-operation"); console.log(performance.getEntriesByType("measure")); ``` **VS Code Debugger Configuration:** ```json // .vscode/launch.json { "version": "0.2.0", "configurations": [ { "type": "node", "request": "launch", "name": "Debug Program", "program": "${workspaceFolder}/src/index.ts", "preLaunchTask": "tsc: build - tsconfig.json", "outFiles": ["${workspaceFolder}/dist/**/*.js"], "skipFiles": ["<node_internals>/**"] }, { "type": "node", "request": "launch", "name": "Debug Tests", "program": "${workspaceFolder}/node_modules/jest/bin/jest", "args": ["--runInBand", "--no-cache"], "console": "integratedTerminal" } ] } ``` ### Python Debugging ```python # Built-in debugger (pdb) import pdb def calculate_total(items): total = 0 pdb.set_trace() # Debugger starts here for item in items: total += item.price * item.quantity return total # Breakpoint (Python 3.7+) def process_order(order): breakpoint() # More convenient than pdb.set_trace() # ... code # Post-mortem debugging try: risky_operation() except Exception: import pdb pdb.post_mortem() # Debug at exception point # IPython debugging (ipdb) from ipdb import set_trace set_trace() # Better interface than pdb # Logging for debugging import logging logging.basicConfig(level=logging.DEBUG) logger = logging.getLogger(__name__) def fetch_user(user_id): logger.debug(f'Fetching user: {user_id}') user = db.query(User).get(user_id) logger.debug(f'Found user: {user}') return user # Profile performance import cProfile import pstats cProfile.run('slow_function()', 'profile_stats') stats = pstats.Stats('profile_stats') stats.sort_stats('cumulative') stats.print_stats(10) # Top 10 slowest ``` ### Go Debugging ```go // Delve debugger // Install: go install github.com/go-delve/delve/cmd/dlv@latest // Run: dlv debug main.go import ( "fmt" "runtime" "runtime/debug" ) // Print stack trace func debugStack() { debug.PrintStack() } // Panic recovery with debugging func processRequest() { defer func() { if r := recover(); r != nil { fmt.Println("Panic:", r) debug.PrintStack() } }() // ... code that might panic } // Memory profiling import _ "net/http/pprof" // Visit http://localhost:6060/debug/pprof/ // CPU profiling import ( "os" "runtime/pprof" ) f, _ := os.Create("cpu.prof") pprof.StartCPUProfile(f) defer pprof.StopCPUProfile() // ... code to profile ``` ## Advanced Debugging Techniques ### Technique 1: Binary Search Debugging ```bash # Git bisect for finding regression git bisect start git bisect bad # Current commit is bad git bisect good v1.0.0 # v1.0.0 was good # Git checks out middle commit # Test it, then: git bisect good # if it works git bisect bad # if it's broken # Continue until bug found git bisect reset # when done ``` ### Technique 2: Differential Debugging Compare working vs broken: ```markdown ## What's Different? | Aspect | Working | Broken | | ------------ | ----------- | -------------- | | Environment | Development | Production | | Node version | 18.16.0 | 18.15.0 | | Data | Empty DB | 1M records | | User | Admin | Regular user | | Browser | Chrome | Safari | | Time | During day | After midnight | Hypothesis: Time-based issue? Check timezone handling. ``` ### Technique 3: Trace Debugging ```typescript // Function call tracing function trace( target: any, propertyKey: string, descriptor: PropertyDescriptor, ) { const originalMethod = descriptor.value; descriptor.value = function (...args: any[]) { console.log(`Calling ${propertyKey} with args:`, args); const result = originalMethod.apply(this, args); console.log(`${propertyKey} returned:`, result); return result; }; return descriptor; } class OrderService { @trace calculateTotal(items: Item[]): number { return items.reduce((sum, item) => sum + item.price, 0); } } ``` ### Technique 4: Memory Leak Detection ```typescript // Chrome DevTools Memory Profiler // 1. Take heap snapshot // 2. Perform action // 3. Take another snapshot // 4. Compare snapshots // Node.js memory debugging if (process.memoryUsage().heapUsed > 500 * 1024 * 1024) { console.warn("High memory usage:", process.memoryUsage()); // Generate heap dump require("v8").writeHeapSnapshot(); } // Find memory leaks in tests let beforeMemory: number; beforeEach(() => { beforeMemory = process.memoryUsage().heapUsed; }); afterEach(() => { const afterMemory = process.memoryUsage().heapUsed; const diff = afterMemory - beforeMemory; if (diff > 10 * 1024 * 1024) { // 10MB threshold console.warn(`Possible memory leak: ${diff / 1024 / 1024}MB`); } }); ``` ## Debugging Patterns by Issue Type ### Pattern 1: Intermittent Bugs ```markdown ## Strategies for Flaky Bugs 1. **Add extensive logging** - Log timing information - Log all state transitions - Log external interactions 2. **Look for race conditions** - Concurrent access to shared state - Async operations completing out of order - Missing synchronization 3. **Check timing dependencies** - setTimeout/setInterval - Promise resolution order - Animation frame timing 4. **Stress test** - Run many times - Vary timing - Simulate load ``` ### Pattern 2: Performance Issues ```markdown ## Performance Debugging 1. **Profile first** - Don't optimize blindly - Measure before and after - Find bottlenecks 2. **Common culprits** - N+1 queries - Unnecessary re-renders - Large data processing - Synchronous I/O 3. **Tools** - Browser DevTools Performance tab - Lighthouse - Python: cProfile, line_profiler - Node: clinic.js, 0x ``` ### Pattern 3: Production Bugs ```markdown ## Production Debugging 1. **Gather evidence** - Error tracking (Sentry, Bugsnag) - Application logs - User reports - Metrics/monitoring 2. **Reproduce locally** - Use production data (anonymized) - Match environment - Follow exact steps 3. **Safe investigation** - Don't change production - Use feature flags - Add monitoring/logging - Test fixes in staging ``` ## Best Practices 1. **Reproduce First**: Can't fix what you can't reproduce 2. **Isolate the Problem**: Remove complexity until minimal case 3. **Read Error Messages**: They're usually helpful 4. **Check Recent Changes**: Most bugs are recent 5. **Use Version Control**: Git bisect, blame, history 6. **Take Breaks**: Fresh eyes see better 7. **Document Findings**: Help future you 8. **Fix Root Cause**: Not just symptoms ## Common Debugging Mistakes - **Making Multiple Changes**: Change one thing at a time - **Not Reading Error Messages**: Read the full stack trace - **Assuming It's Complex**: Often it's simple - **Debug Logging in Prod**: Remove before shipping - **Not Using Debugger**: console.log isn't always best - **Giving Up Too Soon**: Persistence pays off - **Not Testing the Fix**: Verify it actually works ## Quick Debugging Checklist ```markdown ## When Stuck, Check: - [ ] Spelling errors (typos in variable names) - [ ] Case sensitivity (fileName vs filename) - [ ] Null/undefined values - [ ] Array index off-by-one - [ ] Async timing (race conditions) - [ ] Scope issues (closure, hoisting) - [ ] Type mismatches - [ ] Missing dependencies - [ ] Environment variables - [ ] File paths (absolute vs relative) - [ ] Cache issues (clear cache) - [ ] Stale data (refresh database) ``` ## Resources - **references/debugging-tools-guide.md**: Comprehensive tool documentation - **references/performance-profiling.md**: Performance debugging guide - **references/production-debugging.md**: Debugging live systems - **assets/debugging-checklist.md**: Quick reference checklist - **assets/common-bugs.md**: Common bug patterns - **scripts/debug-helper.ts**: Debugging utility functions
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