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πŸ“textβ€’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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πŸ€– Auto-discovered
πŸ“textβ€’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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πŸ€– Auto-discovered
πŸ“textβ€’6 months ago

ARCH-AEP Tiered Remediation Cycle

Run a scope-locked remediation cycle that normalizes findings, revalidates them in parallel, and clears tiers with verification evidence.

architecture
⭐1
# ARCH-AEP Tiered Remediation Cycle Imported from curated first-party documentation sources. ## What this covers Use this workflow when you need an orchestrated engineering review cycle with strict scope lock, tiered execution, and audit-grade evidence. ## Use this when - Large remediation efforts spanning multiple PRs - Parallel specialist review with shared backlog authority - Tracking verification evidence through closure ## Expected outcomes - Scope changes are controlled instead of creeping mid-cycle - Severity tiers drive remediation order predictably - Verification evidence is treated as part of done ## Source synthesis - CHELATEDAI/docs/ARCH AGENTIC ENGINEERING AND PLANNING/workflow.md (https://github.com/mattmre/CHELATEDAI/blob/main/docs/ARCH%20AGENTIC%20ENGINEERING%20AND%20PLANNING/workflow.md) - CHELATEDAI/docs/ARCH AGENTIC ENGINEERING AND PLANNING/orchestrator-briefing.md (https://github.com/mattmre/CHELATEDAI/blob/main/docs/ARCH%20AGENTIC%20ENGINEERING%20AND%20PLANNING/orchestrator-briefing.md) ## Dedupe notes Condenses the core ARCH-AEP workflow and briefing docs into a single remediation-cycle entry instead of importing both separately. ## Source excerpts ### CHELATEDAI/docs/ARCH AGENTIC ENGINEERING AND PLANNING/workflow.md ## Workflow (ARCH phase) 1. Scope lock - Define PR range and time window. - Freeze inputs (refinement report + framework + PR list). 2. Discovery + normalization - Orchestrator ingests `agentic-review-framework.md` and the latest refinement report. - Normalize all findings into a single backlog with unique IDs. - De-duplicate, merge overlaps, and assign provisional severity. - Record backlog in `docs/ARCH AGENTIC ENGINEERING AND PLANNING/backlog-YYYY-MM-DD.md`. 3. Parallel re-validation - Spawn specialist agents to re-validate findings against current main. - Each agent must attach exact file paths and line ranges. - Propose the smallest safe fix, acceptance criteria, and effort sizing (S/M/L). 4. Architecture and planning synthesis - Orchestrator merges validated findings into a master backlog. - Re-score and re-rank using the sorting model. - Identify dependency chains and blockers. ### CHELATEDAI/docs/ARCH AGENTIC ENGINEERING AND PLANNING/orchestrator-briefing.md Purpose: Quick reference for the ARCH-AEP documentation set, plus the narrative to start a new session. Full file index: `docs/INDEX.md` ## What Exists In This Folder - `README.md`: narrative overview and intent for ARCH-AEP. - `workflow.md`: end-to-end workflow specification with phases, guardrails, and enhancements. - `templates.md`: ID and branch conventions, tracker table format, and status log. - `backlog-template.md`: template for the master backlog file. - `backlog-index.md`: index of backlog files. - `next-session.md`: short handoff checklist for resuming work. - `phase-planning.md`: long-running planning record for the current cycle. - `schedule-and-tracking.md`: cadence, gates, and milestone tracking. - `agent-learning.md`: cross-session learnings and reusable patterns. - `change-log.md`: scope/defer decisions with audit context. - `risk-memo-template.md`: Critical/High risk memo template. - `risk-memos/README.md`: storage location for risk memos. - `phase-summary-template.md`: template for per-PR or per-phase summaries. - `phase-summaries/README.md`: storage location for phase summaries. - `verification-log.md`: test/build evidence mirror for PRs. - `tracker-pointer.md`: pointer to the active tracker file. - `tracker-index.md`: index of tracker files. - `scope-lock-t ...
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docs
πŸ“textβ€’6 months ago

Submodule Hygiene Workflow

Add, update, validate, document, and review git submodule changes without losing track of dependency state.

productivity
⭐1
# Submodule Hygiene Workflow Imported from curated first-party documentation sources. ## What this covers Use this workflow when repositories rely on submodules and you need a disciplined way to update them safely. ## Use this when - Adding or updating repository submodules - Documenting submodule changes alongside code changes - Avoiding broken references during review ## Expected outcomes - Submodule changes are treated as a documented workflow - Validation happens before the review handoff - Dependency movement stays visible to the team ## Source synthesis - EVOKORE-MCP/docs/SUBMODULE_WORKFLOW.md (https://github.com/mattmre/EVOKORE-MCP/blob/main/docs/SUBMODULE_WORKFLOW.md) ## Dedupe notes Uses the dedicated submodule workflow doc because the guidance is operationally specific and not already represented on the site. ## Source excerpts ### EVOKORE-MCP/docs/SUBMODULE_WORKFLOW.md This repository may consume external content through git submodules. Use this workflow to keep documentation updates reviewable and predictable. ## 1) Add or Register a Submodule ```bash git submodule add <repo-url> <target-path> git submodule update --init --recursive ``` Commit both: - `.gitmodules` - the submodule pointer change at `<target-path>` ## 2) Pull Latest Submodule Content ```bash git submodule update --remote --merge git submodule update --init --recursive ``` Then inspect: ```bash git status git diff --submodule ``` ## 3) Validate Submodule Cleanliness (Local + CI) Run the same guard used in CI before opening your PR: ```bash git submodule status --recursive node scripts/validate-submodule-cleanliness.js ``` Cleanliness semantics: - `-` => uninitialized submodule - `+` => submodule commit mismatch (worktree vs gitlink pointer) - `U` => submodule merge conflict - dirty submodule worktree => non-empty `git -C <submodule> status --porcelain` Submodule paths can include spaces (for example `SKILLS/ANTHROPIC COOKBOOK`), so always quote path arguments when running manual `git -C` commands. ## 4) Update Docs in This Repo When a submodule changes behavior, update: - `docs/README.md` if canonical links changed - `docs/USAGE.md` / `docs/TROUBLESHOOTING.md` if runtime guidance changed - `README.md` / `CONTRIBUTING.md` if contributor workflow changed ## 5) PR Expectations For submodule-related PRs: 1. Commit inside the submodule first. 2. Return to the parent repo and verify `git submodule status` has no unexpected `-dirty` entries. 3. Commit the updated submodule pointer in the parent repository. 4. Include any matching docs updates in this repository. 5. Mention the upstream submodule commit SHA in the PR description.
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docs
πŸ“textβ€’6 months ago

PR Merge Boundary Validation Runbook

Validate chained pull requests at each merge boundary with explicit checks, stale-approval handling, and rollback awareness.

devops
⭐1
# PR Merge Boundary Validation Runbook Imported from curated first-party documentation sources. ## What this covers Use this runbook when a merge sequence spans dependent pull requests and each boundary needs fresh validation. ## Use this when - Managing dependency-chained pull requests - Refreshing stale approvals near merge time - Reducing merge surprises through checkpoint validation ## Expected outcomes - Each merge boundary has a concrete verification step - Review freshness stays visible as branches evolve - Rollback planning is captured before the merge happens ## Source synthesis - EVOKORE-MCP/docs/PR_MERGE_RUNBOOK.md (https://github.com/mattmre/EVOKORE-MCP/blob/main/docs/PR_MERGE_RUNBOOK.md) ## Dedupe notes Keeps the merge-boundary validation concept separate from more general workflow or orchestration docs. ## Source excerpts ### EVOKORE-MCP/docs/PR_MERGE_RUNBOOK.md Operator runbook for reliable merges and context-rot prevention. ## Pre-merge Checklist - [ ] PR scope matches approved plan - [ ] PR description is filled using `.github/PULL_REQUEST_TEMPLATE.md` - [ ] PR metadata automation check (`scripts/validate-pr-metadata.js`) is passing for pull_request CI runs - [ ] Required tests pass locally/CI - [ ] Docs updated for user-facing behavior changes - [ ] Release-impacting changes called out - [ ] Follow-up issues captured (if any) ## Required Checks by Change Type Use this as the minimum check set before approval and merge: | Change type | Required checks | | --- | --- | | Docs-only changes | `node test-docs-canonical-links.js` | | Ops/docs process changes (`docs/PR_MERGE_RUNBOOK.md`, `next-session.md`, orchestration docs) | `node test-ops-docs-validation.js` and `node test-docs-canonical-links.js` | | Source/tooling/config changes (`src/`, `scripts/`, workflow/config files) | Relevant targeted tests for touched area plus CI-required suite | | Release-flow changes | `node test-npm-release-flow-validation.js` plus docs/link checks | If a PR spans multiple change types, run the union of required checks. ## Reviewer Responsibilities - Confirm PR scope and dependency assumptions are explicit in description. - Confirm PR metadata fields from `.github/PULL_REQUEST_TEMPLATE.md` are complete. - Verify required checks for each change type are attached in PR evidence. - Block approval if dependency base PR is not merged or branch is stale. - Approve only the current chain head; do not pre-approve non-head dependent PRs. - Confirm all review conversations are resolved before final approval. - Ensure merge strategy and rollback notes are documented for risky changes. ## Merge Steps 1. Rebase or update branch with latest target branch. 2. Re-run required validations. 3. Confirm reviewer approvals and resolved conversations. 4. Merge via approved strategy. 5. Record merge commit/PR number in tracker. ## Merge-boundary Checkpoints At every dependency merge boundary (`base -> dependent`): 1. Rebase dependent PR branch on latest `main` immediately after parent merge. 2. Re-run required checks and attach updated evidence in PR metadata. 3. Revalidate approvals for the new head state (stale approvals must be refreshed). 4. Confirm merge-boundary revalidation notes are updated before merge. ## Merge-order Controls (Dependency Chain) 1. Define merge order explicitly in PR descriptions (`base -> dependent`). 2. Merge only the current chain head; hold dependents until parent merge is complete. 3. After each merge, rebase ...
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docs
πŸ€–system promptβ€’6 months ago

Cross-CLI MCP Config Sync

Keep Claude, Cursor, Gemini, and related CLI integrations aligned with a repeatable dry-run and apply workflow.

productivity
⭐1
# Cross-CLI MCP Config Sync Imported from curated first-party documentation sources. ## What this covers Use this skill when multiple AI clients need the same MCP configuration without drifting out of sync. ## Use this when - Rolling out a shared MCP config to multiple clients - Previewing config changes before applying them - Standardizing developer setup across tools ## Expected outcomes - Cross-client MCP setup becomes easier to repeat - Dry-run and apply modes reduce accidental changes - Environment-specific details stay documented near the workflow ## Source synthesis - EVOKORE-MCP/docs/CLI_INTEGRATION.md (https://github.com/mattmre/EVOKORE-MCP/blob/main/docs/CLI_INTEGRATION.md) ## Dedupe notes Uses the dedicated CLI integration guide as the canonical source for config sync instead of duplicating setup notes elsewhere. ## Source excerpts ### EVOKORE-MCP/docs/CLI_INTEGRATION.md EVOKORE-MCP isn't just an MCP Server-Ò€—it also ships with natively integrated UI hooks designed to make your AI CLI experience (like Gemini CLI or Claude Code) significantly more powerful and transparent. ## 🍨 The Interactive Status Line When you connect EVOKORE-MCP to your AI Assistant, you can optionally enable the **EVOKORE Status Line**. Every time the AI finishes a thought or a tool execution, this hook intercepts the internal JSON payload and renders a beautiful, color-coded ASCII status bar at the bottom of your terminal showing: - **Location**: Your current working directory. - **Model Identity**: The exact LLM model currently loaded. - **Skill Count**: A live count of the MCP Agent Skills currently indexed in your library. - **Context Window Health**: A dynamic, color-coded progress bar showing exactly how many tokens you have consumed. --- ### 💜 Enabling in Gemini CLI Gemini CLI features a robust native hook engine. You can configure it to execute the EVOKORE Status Line immediately after every model response (`AfterModel`). **Step 1:** Locate your global settings file (`~/.gemini/settings.json`). **Step 2:** Ensure hooks are enabled, and add the `AfterModel` event array to the root of the JSON object: ```json { "enableHooks": true, "hooks": { "AfterModel": [ { "type": "command", "command": "node /absolute/path/to/EVOKORE-MCP/scripts/status.js" } ] } } ``` **Step 3:** Restart your Gemini CLI! --- ### 💜 Enabling in Claude Code Claude Code features an undocumented internal hook architecture that natively supports this status line. *(Note: Because this feature is currently undocumented by Anthropic, Claude Code's `doctor` command will display "Found 1 settings issue". This is perfectly normal and the status line will still execute successfully)*. **Step 1:** Locate your Claude settings file (`~/.claude/settings.json`). **Step 2:** Add the `statusLine` block to the root of the JSON object: ```json { "statusLine": { "type": "command", "command": "node /absolute/path/to/EVOKORE-MCP/scripts/status.js" } } ``` **Step 3:** Restart Claude Code. --- ### Òő ï¸ A Note on GitHub Copilot and Codex Microsoft's GitHub Copilot CLI and OpenAI's Codex CLI **do not natively support** these JSON hook configurations. If you want the EVOKORE Status Line to appear after commands in these tools, you must configure a native PowerShell/Bash alias wrapper around the CLI execution. **Example (PowerShell Profile):** ```powershell function copilot-evokore { gh copilot $args node "/absolute/path/to/EV ...
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docs
πŸ€–system promptβ€’6 months ago

Hook Observability and Session Replay

Instrument hooks with replayable logs, task-state visibility, and non-blocking observability around agent sessions.

devops
⭐1
# Hook Observability and Session Replay Imported from curated first-party documentation sources. ## What this covers Use this skill when you need to understand what hooks fired, what they emitted, and how a session can be replayed after the fact. ## Use this when - Debugging hook-driven automation - Replaying session events after failures - Adding observability without blocking interactive work ## Expected outcomes - Hook activity becomes inspectable and replayable - Operational state survives beyond a single terminal session - Observability stays useful without overwhelming operators ## Source synthesis - EVOKORE-MCP/docs/VOICE_AND_HOOKS.md (https://github.com/mattmre/EVOKORE-MCP/blob/main/docs/VOICE_AND_HOOKS.md) - EVOKORE-MCP/docs/USE_CASES_AND_WALKTHROUGHS.md (https://github.com/mattmre/EVOKORE-MCP/blob/main/docs/USE_CASES_AND_WALKTHROUGHS.md) ## Dedupe notes Focuses on replay and observability instead of importing the broader voice-sidecar guide verbatim. ## Source excerpts ### EVOKORE-MCP/docs/VOICE_AND_HOOKS.md EVOKORE currently has three separate voice-related systems plus a set of hook and observability utilities. They overlap in operator workflows, but they are not the same runtime. ## The three voice-related systems ### 1. ElevenLabs MCP proxy This is the optional `elevenlabs` child server configured in `mcp.config.json`. What it is: - proxied through the EVOKORE router - exposed as prefixed MCP tools - available to any EVOKORE-connected MCP client when configured successfully What it is for: - text-to-speech and other ElevenLabs MCP operations as tools - routing voice-related actions through the standard EVOKORE proxy/security stack Requirements: - `uvx` available on PATH - `ELEVENLABS_API_KEY` set ### 2. VoiceMode VoiceMode is a separate voice-conversation system for Claude Code. What it is: - registered separately from EVOKORE - not routed through EVOKOREÒ€ℒs stdio server - used for bidirectional voice conversation in Claude Code What it is for: - speaking to Claude and hearing spoken responses - using `OPENAI_API_KEY` and VoiceModeÒ€ℒs own runtime Windows note: - VoiceMode relies on `uvx` being directly available - set `OPENAI_API_KEY` in the shell that launches Claude Code ### 3. VoiceSidecar VoiceSidecar is a standalone WebSocket server implemented in `src/Voice ... ### EVOKORE-MCP/docs/USE_CASES_AND_WALKTHROUGHS.md This guide turns the runtime contracts into practical operator flows. ## Walkthrough 1: Adopt a workflow from the skill library Use this when you want EVOKORE to retrieve process guidance before the model starts acting. ### Goal Find and adopt an existing workflow such as `session-wrap`. ### Steps 1. Ask the client to search skills: ```text Search the MCP for a workflow about session wrap-up and continuity. ``` 2. EVOKORE uses `search_skills` and returns matching skills. 3. Ask for a specific skill: ```text Show me help for the session-wrap skill. ``` 4. EVOKORE uses `get_skill_help` and returns the skillÒ€ℒs internal instructions. 5. For broader task matching, ask: ```text Resolve a workflow for wrapping this session, documenting open risks, and preparing the next handoff. ``` 6. EVOKORE uses `resolve_workflow` and injects the top 1-3 relevant workflows directly into the tool response. ### Why this matters - keeps the model grounded in repo-specific process - reduces prompt drift - makes handoff and governance behavior repeatable ## Walkthrough 2: Use a proxied tool that requires HITL approval Use this when the tool is configured as `require_approval` in `permissions.yml`. ### Goal Allow a protected proxied tool call such as `fs_write_f ...
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docs
πŸ€–system promptβ€’6 months ago

Multi-Server MCP Aggregation Pattern

Aggregate tools across multiple MCP child servers with prefixing, collision avoidance, and routing rules that stay deterministic.

architecture
⭐1
# Multi-Server MCP Aggregation Pattern Imported from curated first-party documentation sources. ## What this covers Use this pattern when an MCP host must broker tools from multiple child servers without sacrificing clarity or control. ## Use this when - Combining tools from several MCP backends - Avoiding tool-name collisions across providers - Keeping origin and routing visible during execution ## Expected outcomes - Server-prefixed names make tool origins obvious - Collisions are avoided without brittle manual renaming - Operators can extend the tool surface without losing determinism ## Source synthesis - EVOKORE-MCP/docs/AGENT33_IMPROVEMENT_INSTRUCTIONS.md (https://github.com/mattmre/EVOKORE-MCP/blob/main/docs/AGENT33_IMPROVEMENT_INSTRUCTIONS.md) - EVOKORE-MCP/docs/TOOLS_AND_DISCOVERY.md (https://github.com/mattmre/EVOKORE-MCP/blob/main/docs/TOOLS_AND_DISCOVERY.md) ## Dedupe notes Uses the improvement-transfer doc as the primary source, with the discovery doc covering prefixing and compatibility details. ## Source excerpts ### EVOKORE-MCP/docs/AGENT33_IMPROVEMENT_INSTRUCTIONS.md > **Purpose**: Feed this file into Claude Code CLI when working on the Agent33 repo. It contains patterns, architectures, and capabilities proven in EVOKORE-MCP that Agent33 should adopt. --- ## 1. Multi-Server MCP Aggregation Pattern **What Agent33 lacks**: Agent33's MCP server (Phase 43) is a single-endpoint bridge. It doesn't aggregate multiple child MCP servers behind a unified namespace. **What to build**: A proxy layer that spawns and manages multiple child MCP servers from a single config file, presenting them as one unified tool surface. ### Implementation spec: ``` mcp.config.json { "servers": { "github": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-github"], "env": { "GITHUB_TOKEN": "${GITHUB_TOKEN}" } }, "fs": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-filesystem", "./"] }, "elevenlabs": { "command": "uvx", "args": ["elevenlabs-mcp"], "env": { "ELEVENLABS_API_KEY": "${ELEVENLABS_API_KEY}" } } } } ``` **Key patterns from EVOKORE**: - **Tool name prefixing**: Every proxied tool gets renamed `{serverId}_{originalName}` to prevent namespace collisions (e.g., `github_create_issue`, `fs_read_file`). First-registration-wins for duplicates. - **Environment interpolation**: `${VAR}` syntax in `env` blocks resolved ... ### EVOKORE-MCP/docs/TOOLS_AND_DISCOVERY.md This page explains how EVOKORE presents tools, how proxy names are built, and how `discover_tools` changes the visible tool surface. ## Two tool populations ### Native EVOKORE tools These tools are defined by EVOKORE itself: - `docs_architect` - `skill_creator` - `resolve_workflow` - `search_skills` - `get_skill_help` - `discover_tools` Properties: - always available - always visible - not subject to proxy prefixing ### Proxied child-server tools These come from child servers in `mcp.config.json`. Current configured sources: - `github` - `fs` - optional `elevenlabs` Properties: - fetched from child servers at startup - renamed with server prefixes - governed by `permissions.yml` - routed through `ProxyManager` ## Prefixing and compatibility EVOKORE rewrites proxied tool names to: ```text ${serverId}_${tool.name} ``` Why this exists: - prevents tool-name collisions across child servers - makes origin obvious during execution and review - keeps exact-name routing deterministic Examples: | Upstream tool | EVOKORE-exposed tool | |---|---| | `read_file` from `fs` | `fs_read_file` | | `create_issue` from `github` | `github_create_issue` | ### Duplicate-prefixed name policy If two child registrations would create the same final prefixed name: - the first registrati ...
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docs
πŸ€–system promptβ€’6 months ago

Human-in-the-Loop Approval Token Workflow

Gate risky tool execution behind approval tokens so agents can retry safely after a human reviewer signs off.

security
⭐1
# Human-in-the-Loop Approval Token Workflow Imported from curated first-party documentation sources. ## What this covers Use this workflow when autonomous execution needs a durable handoff from human review back into the agent loop. ## Use this when - Retrying a blocked tool call after approval - Adding a human checkpoint to sensitive actions - Reducing insecure workarounds around approval flows ## Expected outcomes - Approval becomes a reusable tokenized workflow - Agents resume work without losing execution context - Security controls stay explicit instead of being implied ## Source synthesis - EVOKORE-MCP/docs/V2_MULTI_AGENT_WORKFLOWS.md (https://github.com/mattmre/EVOKORE-MCP/blob/main/docs/V2_MULTI_AGENT_WORKFLOWS.md) - EVOKORE-MCP/docs/AGENT33_IMPROVEMENT_INSTRUCTIONS.md (https://github.com/mattmre/EVOKORE-MCP/blob/main/docs/AGENT33_IMPROVEMENT_INSTRUCTIONS.md) ## Dedupe notes Synthesizes the approval-token concept from the main workflow doc and the Agent33 improvement transfer notes. ## Source excerpts ### EVOKORE-MCP/docs/V2_MULTI_AGENT_WORKFLOWS.md With EVOKORE-MCP v2.0 fully operational, we can now leverage 40+ proxied GitHub and Filesystem tools seamlessly within complex multi-agent workflows. The core architectural advancements include: ## 1. Dynamic Tool Prefixing & Indexing Instead of loading 40+ tools into an LLM's context window statically (which causes massive bloat), EVOKORE's `ProxyManager` boots child servers (like `@modelcontextprotocol/server-github` and `@modelcontextprotocol/server-filesystem`) and dynamically prefixes their tools (`github_create_issue`, `fs_write_file`). This prevents namespace collisions while keeping the tools accessible to native skills. ## 2. Human-in-the-Loop (HITL) Security Interceptor Automated multi-agent workflows involving sensitive endpoints (like GitHub write access or file deletion) are governed by EVOKORE's stateless `_evokore_approval_token` architecture. - When an agent attempts a restricted action, the tool call is intercepted and blocked. - The server returns an error explicitly commanding the agent to prompt the human for approval. - Upon approval, the agent retries the exact tool call with the injected token, securely fulfilling the workflow without severing the conversational context. ## 3. Active Skill Orchestration (Native Harnessing) Unlike v1.0 where skills merel ... ### EVOKORE-MCP/docs/AGENT33_IMPROVEMENT_INSTRUCTIONS.md > **Purpose**: Feed this file into Claude Code CLI when working on the Agent33 repo. It contains patterns, architectures, and capabilities proven in EVOKORE-MCP that Agent33 should adopt. --- ## 1. Multi-Server MCP Aggregation Pattern **What Agent33 lacks**: Agent33's MCP server (Phase 43) is a single-endpoint bridge. It doesn't aggregate multiple child MCP servers behind a unified namespace. **What to build**: A proxy layer that spawns and manages multiple child MCP servers from a single config file, presenting them as one unified tool surface. ### Implementation spec: ``` mcp.config.json { "servers": { "github": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-github"], "env": { "GITHUB_TOKEN": "${GITHUB_TOKEN}" } }, "fs": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-filesystem", "./"] }, "elevenlabs": { "command": "uvx", "args": ["elevenlabs-mcp"], "env": { "ELEVENLABS_API_KEY": "${ELEVENLABS_API_KEY}" } } } } ``` **Key patterns from EVOKORE**: - **Tool name prefixing**: Every proxied tool gets renamed `{serverId}_{originalName}` to prevent namespace collisions (e.g., `github_create_issue`, `fs_read_file`). First-registration-wins for duplicates. - **Environment interpolation**: `${VAR}` syntax in `env` blocks resolved ...
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πŸ€–system promptβ€’6 months ago

Dynamic Tool Discovery and Session Activation

Expose only native tools at session start, then activate proxied tools on demand through a searchable discovery layer.

architecture
⭐1
# Dynamic Tool Discovery and Session Activation Imported from curated first-party documentation sources. ## What this covers Use this skill when you need smaller tool payloads, exact-name compatibility, and session-scoped tool activation. ## Use this when - Reducing tool-list bloat for focused sessions - Preserving exact-name tool calls while hiding noise - Activating proxied tools only when a task requires them ## Expected outcomes - Discovery changes listing visibility without breaking routing - Session-scoped activation keeps tools relevant to the task - Operators can trade compatibility against payload size intentionally ## Source synthesis - EVOKORE-MCP/docs/TOOLS_AND_DISCOVERY.md (https://github.com/mattmre/EVOKORE-MCP/blob/main/docs/TOOLS_AND_DISCOVERY.md) ## Dedupe notes Uses the canonical EVOKORE-MCP discovery doc instead of duplicating the same concept from walkthrough and migration docs. ## Source excerpts ### EVOKORE-MCP/docs/TOOLS_AND_DISCOVERY.md This page explains how EVOKORE presents tools, how proxy names are built, and how `discover_tools` changes the visible tool surface. ## Two tool populations ### Native EVOKORE tools These tools are defined by EVOKORE itself: - `docs_architect` - `skill_creator` - `resolve_workflow` - `search_skills` - `get_skill_help` - `discover_tools` Properties: - always available - always visible - not subject to proxy prefixing ### Proxied child-server tools These come from child servers in `mcp.config.json`. Current configured sources: - `github` - `fs` - optional `elevenlabs` Properties: - fetched from child servers at startup - renamed with server prefixes - governed by `permissions.yml` - routed through `ProxyManager` ## Prefixing and compatibility EVOKORE rewrites proxied tool names to: ```text ${serverId}_${tool.name} ``` Why this exists: - prevents tool-name collisions across child servers - makes origin obvious during execution and review - keeps exact-name routing deterministic Examples: | Upstream tool | EVOKORE-exposed tool | |---|---| | `read_file` from `fs` | `fs_read_file` | | `create_issue` from `github` | `github_create_issue` | ### Duplicate-prefixed name policy If two child registrations would create the same final prefixed name: - the first registration wins - later duplicates are skipped - EVOKORE logs a warning and duplicate summary ## Discovery modes | Mode | What `tools/list` returns | Best for | |---|---|---| | `legacy` | all native + proxied tools | maximum compatibility | | `dynamic` | native tools + session-activated proxied tools | smaller initial tool payloads | Environment toggle: ```bash EVOKORE_TOOL_DISCOVERY_MODE=legacy EVOKORE_TOOL_DISCOVERY_MODE=dynamic ``` ## Dynamic discovery lifecycle In `dynamic` mode, EVOKORE uses a session-scoped activation set. Lifecycle: 1. session starts with only native tools visible 2. user/model calls `discover_tools` 3. `ToolCatalogIndex` searches the merged native + proxied catalog 4. matching proxied tools are activated for that session 5. EVOKORE emits `sendToolListChanged()` best-effort 6. client re-runs `tools/list` or auto-refreshes ```mermaid flowchart TD A[Session starts in dynamic mode] --> B[tools/list shows native tools] B --> C[discover_tools query] C --> D[ToolCatalogIndex searches merged catalog] D --> E[Matching proxied tools added to session activation set] E --> F[sendToolListChanged best-effort] F --> G[Client refreshes tools/list] G --> H[Activated proxied tools now visible] D --> I[Exact-name proxied call still works eve ...
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πŸ“textβ€’6 months ago

Docker-Backed Jupyter Kernel Operator

Operate containerized Jupyter kernels with enablement, smoke checks, cleanup, and failure handling baked into the runbook.

devops
⭐1
# Docker-Backed Jupyter Kernel Operator Imported from curated first-party documentation sources. ## What this covers Use this runbook when you need isolated notebook execution, clear container lifecycle management, and troubleshooting guidance. ## Use this when - Enabling containerized notebook workflows - Cleaning up kernel containers safely - Troubleshooting notebook execution environments ## Expected outcomes - Kernel startup and cleanup steps are documented end-to-end - Failure modes are easier to diagnose - Notebook execution can be repeated without manual guesswork ## Source synthesis - AGENT33/docs/runbooks/jupyter-kernel-containers.md (https://github.com/mattmre/AGENT33/blob/main/docs/runbooks/jupyter-kernel-containers.md) ## Dedupe notes Uses the AGENT33 Jupyter container runbook as a focused operations import without duplicating broader walkthroughs. ## Source excerpts ### AGENT33/docs/runbooks/jupyter-kernel-containers.md ## Purpose Operate the Docker-backed Jupyter kernel adapter introduced for Phase 38 Stage 3 / Phase 42 follow-on work. ## Enablement Set: - `JUPYTER_KERNEL_ENABLED=true` - `JUPYTER_KERNEL_MODE=docker` Optional settings: - `JUPYTER_KERNEL_DOCKER_IMAGE` - `JUPYTER_KERNEL_ALLOWED_IMAGES` - `JUPYTER_KERNEL_NETWORK_ENABLED` - `JUPYTER_KERNEL_MOUNT_WORKDIR` - `JUPYTER_KERNEL_CONTAINER_WORKDIR` ## Operational Notes - Docker mode publishes kernel ports to the host and mounts a per-session runtime directory containing the Jupyter connection file. - When `JUPYTER_KERNEL_NETWORK_ENABLED=false`, the adapter starts containers with `--network none`. - Working-directory mounting is opt-in and should only point at paths already approved by workflow / execution policy. - The adapter enforces an image allowlist when one is configured. ## Failure Modes - `jupyter_client not installed`: install with `pip install agent33[jupyter]` - `docker executable not found`: install Docker and ensure `docker` is on `PATH` - `Docker image ... is not permitted`: align the requested image with `JUPYTER_KERNEL_ALLOWED_IMAGES` - kernel startup timeout: inspect Docker logs for the session container and verify the image includes `ipykernel` ## Cleanup - One-shot sessions are removed after execution. - Stateful sessions are removed explicitly or via adapter shutdown. - Forced cleanup uses `docker rm -f <container>` and deletes the runtime connection directory. ## Quick Smoke Workflow Register a minimal workflow that exercises the Docker-backed `code-interpreter` tool: ```bash curl -X POST http://localhost:8000/v1/workflows/ \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '{ "name": "docker-kernel-smoke", "version": "1.0.0", "description": "Validate Docker-backed Jupyter execution", "triggers": {"manual": true}, "inputs": {}, "outputs": { "result": {"type": "object"} }, "steps": [ { "id": "run-notebook-code", "action": "execute-code", "inputs": { "tool_id": "code-interpreter", "language": "python", "code": "print(6 * 7)" } } ], "execution": {"mode": "sequential"} }' ``` Then execute it: ```bash curl -X POST http://localhost:8000/v1/workflows/docker-kernel-smoke/execute \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '{"inputs": {}}' ```
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πŸ“textβ€’6 months ago

Improvement Cycle Review Wizard

Run a live improvement-cycle workflow that links review artifacts, approvals, tool requests, and operator checkpoints.

productivity
⭐1
# Improvement Cycle Review Wizard Imported from curated first-party documentation sources. ## What this covers Use this workflow when an operator needs a guided improvement cycle with live status, explicit approvals, and linked artifacts. ## Use this when - Operational review sessions with live progress - Approval-heavy improvement cycles - Coordinating review artifacts with execution steps ## Expected outcomes - Live workflow execution remains visible to operators - Artifacts, approvals, and tool requests stay connected - Improvement loops become easier to audit and rerun ## Source synthesis - AGENT33/docs/phase25-26-live-review-walkthrough.md (https://github.com/mattmre/AGENT33/blob/main/docs/phase25-26-live-review-walkthrough.md) - AGENT33/docs/operator-improvement-cycle-and-jupyter.md (https://github.com/mattmre/AGENT33/blob/main/docs/operator-improvement-cycle-and-jupyter.md) ## Dedupe notes Merges AGENT33 live review walkthrough details with the shorter operator-focused improvement-cycle guide. ## Source excerpts ### AGENT33/docs/phase25-26-live-review-walkthrough.md This guide documents the operator flow introduced by the Phase 25 live workflow transport and the Phase 26/27 improvement-cycle review wizard stack. ## Scope - Live workflow execution with run-scoped graph refresh - WebSocket-first status streaming with authenticated SSE fallback - Improvement-cycle preset creation - Explanation artifact generation for `plan_review` and `diff_review` - Linked review creation, risk assessment, L1/L2 signoff, and final approval - Pending tool-approval triage inside the same workflow domain > Note > This walkthrough reflects the review stack built on `codex/session58-phase26-wizard` and validated in `codex/session60-phase22-docs-validation`. If the related PRs are still open, `main` may not yet expose every surface described here. ## Operator Flow ```mermaid sequenceDiagram participant UI as "Frontend Control Plane" participant WF as "Workflow APIs" participant VIZ as "Visualization APIs" participant EXP as "Explanation APIs" participant REV as "Review APIs" participant HITL as "Tool Approval APIs" UI->>WF: "POST /v1/workflows/{name}/execute (single mode, caller run_id)" UI->>VIZ: "GET /v1/visualizations/workflows/{workflow_id}/graph?run_id=..." UI->>WF: "WS /v1/workflows/{run_id}/ws" alt "WebSocket unav ... ### AGENT33/docs/operator-improvement-cycle-and-jupyter.md This guide covers the merged operator surfaces for: - the Phase 26 improvement-cycle review wizard - the Phase 27 canonical workflow presets - the Phase 38 Docker-backed Jupyter kernel workflow Use it when you want the shortest current path from UI entry point to a real workflow run. ## 1. Improvement-Cycle Wizard The wizard is mounted inside the frontend control plane under the `Workflows` domain. ### Entry path 1. Open the frontend at `http://localhost:3000` 2. Authenticate with a bearer token or API key 3. Open `Advanced Settings` 4. Select the `Workflows` domain 5. Use the `Improvement Cycle Wizard` panel at the top of the page ### What the wizard does The wizard stitches together the backend surfaces that previously had to be called manually: - plan review / diff review generation - review creation and risk assessment - L1 and L2 review submission - tool approval request review and decision capture Reference implementation: - frontend: `frontend/src/features/improvement-cycle/ImprovementCycleWizard.tsx` - tests: `frontend/src/features/improvement-cycle/ImprovementCycleWizard.test.tsx` For the detailed review flow, keep using: - [`phase25-26-live-review-walkthrough.md`](phase25-26-live-review-walkthrough.md) ## 2. Canonical Workflow Presets The `Workflows` doma ...
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πŸ“textβ€’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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πŸ“textβ€’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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πŸ“textβ€’6 months ago

Guardrailed Code Review Pipeline

Run a staged code review workflow with explicit risk assessment, reviewer handoffs, and merge gates.

coding
⭐1
# Guardrailed Code Review Pipeline Imported from curated first-party documentation sources. ## What this covers Use this workflow when a change needs structured review evidence, clear approval stages, and a rollback-aware path to merge. ## Use this when - Multi-step L1 and L2 review signoff - High-risk changes that need audit trails - Standardizing reviewer decisions before merge ## Expected outcomes - Review states and approval checkpoints stay explicit - Risk assessment and evidence are captured before merge - The workflow remains small enough to reuse across repositories ## Source synthesis - AGENT33/docs/functionality-and-workflows.md (https://github.com/mattmre/AGENT33/blob/main/docs/functionality-and-workflows.md) - AGENT33/docs/walkthroughs.md (https://github.com/mattmre/AGENT33/blob/main/docs/walkthroughs.md) ## Dedupe notes Combines AGENT33 lifecycle mapping and operator walkthrough material into one review-oriented site entry. ## Source excerpts ### AGENT33/docs/functionality-and-workflows.md ### 4.1 Review Lifecycle States: - `draft -> ready -> l1-review -> l1-approved -> (optional l2-review -> l2-approved) -> approved -> merged` Main APIs: - `/v1/reviews/{id}/assess` - `/v1/reviews/{id}/assign-l1` - `/v1/reviews/{id}/l1` - `/v1/reviews/{id}/assign-l2` - `/v1/reviews/{id}/l2` - `/v1/reviews/{id}/approve` - `/v1/reviews/{id}/merge` ### AGENT33/docs/walkthroughs.md ## 4. Review Lifecycle (Two-Layer Signoff) Create review: ```bash curl -X POST http://localhost:8000/v1/reviews/ \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '{"task_id":"TASK-101","branch":"feat/docs-refresh","pr_number":12}' ``` Assess risk: ```bash curl -X POST http://localhost:8000/v1/reviews/<review_id>/assess \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '{"triggers":["api-public","security"]}' ``` Move to ready and assign L1: ```bash curl -X POST http://localhost:8000/v1/reviews/<review_id>/ready -H "Authorization: Bearer $TOKEN" curl -X POST http://localhost:8000/v1/reviews/<review_id>/assign-l1 -H "Authorization: Bearer $TOKEN" ``` Submit L1 decision: ```bash curl -X POST http://localhost:8000/v1/reviews/<review_id>/l1 \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '{"decision":"approved","issues":[],"comments":"L1 pass"}' ``` If L2 required, continue: ```bash curl -X POST http://localhost:8000/v1/reviews/<review_id>/assign-l2 -H "Authorization: Bearer $TOKEN" curl -X POST http://localhost:8000/v1/reviews/<review_id>/l2 \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '{"decision":"approved","issues":[],"commen ...
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πŸ€–system promptβ€’7 months ago

git-advanced-workflows

Master advanced Git workflows including rebasing, cherry-picking,

coding
⭐1
# Git Advanced Workflows Master advanced Git techniques to maintain clean history, collaborate effectively, and recover from any situation with confidence. ## When to Use This Skill - Cleaning up commit history before merging - Applying specific commits across branches - Finding commits that introduced bugs - Working on multiple features simultaneously - Recovering from Git mistakes or lost commits - Managing complex branch workflows - Preparing clean PRs for review - Synchronizing diverged branches ## Core Concepts ### 1. Interactive Rebase Interactive rebase is the Swiss Army knife of Git history editing. **Common Operations:** - `pick`: Keep commit as-is - `reword`: Change commit message - `edit`: Amend commit content - `squash`: Combine with previous commit - `fixup`: Like squash but discard message - `drop`: Remove commit entirely **Basic Usage:** ```bash # Rebase last 5 commits git rebase -i HEAD~5 # Rebase all commits on current branch git rebase -i $(git merge-base HEAD main) # Rebase onto specific commit git rebase -i abc123 ``` ### 2. Cherry-Picking Apply specific commits from one branch to another without merging entire branches. ```bash # Cherry-pick single commit git cherry-pick abc123 # Cherry-pick range of commits (exclusive start) git cherry-pick abc123..def456 # Cherry-pick without committing (stage changes only) git cherry-pick -n abc123 # Cherry-pick and edit commit message git cherry-pick -e abc123 ``` ### 3. Git Bisect Binary search through commit history to find the commit that introduced a bug. ```bash # Start bisect git bisect start # Mark current commit as bad git bisect bad # Mark known good commit git bisect good v1.0.0 # Git will checkout middle commit - test it # Then mark as good or bad git bisect good # or: git bisect bad # Continue until bug found # When done git bisect reset ``` **Automated Bisect:** ```bash # Use script to test automatically git bisect start HEAD v1.0.0 git bisect run ./test.sh # test.sh should exit 0 for good, 1-127 (except 125) for bad ``` ### 4. Worktrees Work on multiple branches simultaneously without stashing or switching. ```bash # List existing worktrees git worktree list # Add new worktree for feature branch git worktree add ../project-feature feature/new-feature # Add worktree and create new branch git worktree add -b bugfix/urgent ../project-hotfix main # Remove worktree git worktree remove ../project-feature # Prune stale worktrees git worktree prune ``` ### 5. Reflog Your safety net - tracks all ref movements, even deleted commits. ```bash # View reflog git reflog # View reflog for specific branch git reflog show feature/branch # Restore deleted commit git reflog # Find commit hash git checkout abc123 git branch recovered-branch # Restore deleted branch git reflog git branch deleted-branch abc123 ``` ## Practical Workflows ### Workflow 1: Clean Up Feature Branch Before PR ```bash # Start with feature branch git checkout feature/user-auth # Interactive rebase to clean history git rebase -i main # Example rebase operations: # - Squash "fix typo" commits # - Reword commit messages for clarity # - Reorder commits logically # - Drop unnecessary commits # Force push cleaned branch (safe if no one else is using it) git push --force-with-lease origin feature/user-auth ``` ### Workflow 2: Apply Hotfix to Multiple Releases ```bash # Create fix on main git checkout main git commit -m "fix: critical security patch" # Apply to release branches git checkout release/2.0 git cherry-pick abc123 git checkout release/1.9 git cherry-pick abc123 # Handle conflicts if they arise git cherry-pick --continue # or git cherry-pick --abort ``` ### Workflow 3: Find Bug Introduction ```bash # Start bisect git bisect start git bisect bad HEAD git bisect good v2.1.0 # Git checks out middle commit - run tests npm test # If tests fail git bisect bad # If tests pass git bisect good # Git will automatically checkout next commit to test # Repeat until bug found # Automated version git bisect start HEAD v2.1.0 git bisect run npm test ``` ### Workflow 4: Multi-Branch Development ```bash # Main project directory cd ~/projects/myapp # Create worktree for urgent bugfix git worktree add ../myapp-hotfix hotfix/critical-bug # Work on hotfix in separate directory cd ../myapp-hotfix # Make changes, commit git commit -m "fix: resolve critical bug" git push origin hotfix/critical-bug # Return to main work without interruption cd ~/projects/myapp git fetch origin git cherry-pick hotfix/critical-bug # Clean up when done git worktree remove ../myapp-hotfix ``` ### Workflow 5: Recover from Mistakes ```bash # Accidentally reset to wrong commit git reset --hard HEAD~5 # Oh no! # Use reflog to find lost commits git reflog # Output shows: # abc123 HEAD@{0}: reset: moving to HEAD~5 # def456 HEAD@{1}: commit: my important changes # Recover lost commits git reset --hard def456 # Or create branch from lost commit git branch recovery def456 ``` ## Advanced Techniques ### Rebase vs Merge Strategy **When to Rebase:** - Cleaning up local commits before pushing - Keeping feature branch up-to-date with main - Creating linear history for easier review **When to Merge:** - Integrating completed features into main - Preserving exact history of collaboration - Public branches used by others ```bash # Update feature branch with main changes (rebase) git checkout feature/my-feature git fetch origin git rebase origin/main # Handle conflicts git status # Fix conflicts in files git add . git rebase --continue # Or merge instead git merge origin/main ``` ### Autosquash Workflow Automatically squash fixup commits during rebase. ```bash # Make initial commit git commit -m "feat: add user authentication" # Later, fix something in that commit # Stage changes git commit --fixup HEAD # or specify commit hash # Make more changes git commit --fixup abc123 # Rebase with autosquash git rebase -i --autosquash main # Git automatically marks fixup commits ``` ### Split Commit Break one commit into multiple logical commits. ```bash # Start interactive rebase git rebase -i HEAD~3 # Mark commit to split with 'edit' # Git will stop at that commit # Reset commit but keep changes git reset HEAD^ # Stage and commit in logical chunks git add file1.py git commit -m "feat: add validation" git add file2.py git commit -m "feat: add error handling" # Continue rebase git rebase --continue ``` ### Partial Cherry-Pick Cherry-pick only specific files from a commit. ```bash # Show files in commit git show --name-only abc123 # Checkout specific files from commit git checkout abc123 -- path/to/file1.py path/to/file2.py # Stage and commit git commit -m "cherry-pick: apply specific changes from abc123" ``` ## Best Practices 1. **Always Use --force-with-lease**: Safer than --force, prevents overwriting others' work 2. **Rebase Only Local Commits**: Don't rebase commits that have been pushed and shared 3. **Descriptive Commit Messages**: Future you will thank present you 4. **Atomic Commits**: Each commit should be a single logical change 5. **Test Before Force Push**: Ensure history rewrite didn't break anything 6. **Keep Reflog Aware**: Remember reflog is your safety net for 90 days 7. **Branch Before Risky Operations**: Create backup branch before complex rebases ```bash # Safe force push git push --force-with-lease origin feature/branch # Create backup before risky operation git branch backup-branch git rebase -i main # If something goes wrong git reset --hard backup-branch ``` ## Common Pitfalls - **Rebasing Public Branches**: Causes history conflicts for collaborators - **Force Pushing Without Lease**: Can overwrite teammate's work - **Losing Work in Rebase**: Resolve conflicts carefully, test after rebase - **Forgetting Worktree Cleanup**: Orphaned worktrees consume disk space - **Not Backing Up Before Experiment**: Always create safety branch - **Bisect on Dirty Working Directory**: Commit or stash before bisecting ## Recovery Commands ```bash # Abort operations in progress git rebase --abort git merge --abort git cherry-pick --abort git bisect reset # Restore file to version from specific commit git restore --source=abc123 path/to/file # Undo last commit but keep changes git reset --soft HEAD^ # Undo last commit and discard changes git reset --hard HEAD^ # Recover deleted branch (within 90 days) git reflog git branch recovered-branch abc123 ``` ## Resources - **references/git-rebase-guide.md**: Deep dive into interactive rebase - **references/git-conflict-resolution.md**: Advanced conflict resolution strategies - **references/git-history-rewriting.md**: Safely rewriting Git history - **assets/git-workflow-checklist.md**: Pre-PR cleanup checklist - **assets/git-aliases.md**: Useful Git aliases for advanced workflows - **scripts/git-clean-branches.sh**: Clean up merged and stale branches
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πŸ€– Auto-discovered
πŸ€–system promptβ€’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 // ❌ Bad: Fixed timeouts await page.waitForTimeout(3000); // Flaky! // βœ… Good: Wait for specific conditions await page.waitForLoadState("networkidle"); await page.waitForURL("/dashboard"); await page.waitForSelector('[data-testid="user-profile"]'); // βœ… 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 // ❌ Bad selectors cy.get(".btn.btn-primary.submit-button").click(); cy.get("div > form > div:nth-child(2) > input").type("text"); // βœ… 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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πŸ€– Auto-discovered
πŸ€–system promptβ€’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 β†’ 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? β†’ Activity Is it orchestration/decision logic? β†’ 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 Γ— 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 β†’ identical outputs every time **Prohibited in Workflows** (Source: docs.temporal.io/workflows): - ❌ Threading, locks, synchronization primitives - ❌ Random number generation (`random()`) - ❌ Global state or static variables - ❌ System time (`datetime.now()`) - ❌ Direct file I/O or network calls - ❌ Non-deterministic libraries **Allowed in Workflows**: - βœ… `workflow.now()` (deterministic time) - βœ… `workflow.random()` (deterministic random) - βœ… Pure functions and calculations - βœ… 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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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
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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" β†’ "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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πŸ€– Auto-discovered