workflow-improvement

Solid

Retrospective evaluation and improvement of skills, agents, commands, and hooks

AI & Automation 308 stars 27 forks Updated today MIT

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Skill Content

# Workflow Improvement ## When To Use Use this skill after running a command or completing a short session slice where execution felt slow, confusing, repetitive, or fragile. This skill focuses on improving the *workflow assets* (skills, agents, commands, hooks) that were involved, not on feature work itself. ## When NOT To Use - Implementing features - focus on feature work first ## Required TodoWrite Items 1. `fix-workflow:context-gathered` 2. `fix-workflow:slice-captured` 3. `fix-workflow:workflow-recreated` 4. `fix-workflow:improvements-generated` 5. `fix-workflow:plan-agreed` 6. `fix-workflow:changes-implemented` 7. `fix-workflow:validated` 8. `fix-workflow:lesson-stored` ## Step 0: Gather Improvement Context (`context-gathered`) Before analyzing the current session, gather existing improvement data: ### 0.1: Check Skill Execution History Query memory-palace logs for recent performance issues: ```bash # Recent failures (last 7 days) /skill-logs --failures-only --last 7d # Performance metrics for involved plugins pensive:skill-review --plugin sanctum --recommendations ``` **Capture:** - Skills with stability_gap > 0.3 - Recent failure patterns and error messages - Performance degradation trends ### 0.2: Query Knowledge Base Search for previously captured workflow lessons: ```bash # If memory-palace review-chamber is available /review-room search "workflow improvement" --room lessons /review-room search "efficiency" --room patterns ``` **Look for:** - Simil...

Details

Author
athola
Repository
athola/claude-night-market
Created
6 months ago
Last Updated
today
Language
Python
License
MIT

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