knowledge-curation

Solid

Context priming before work (bd prime) and self-reflection after completion to extract patterns, gotchas, and decisions into the knowledge base.

AI & Automation 1,160 stars 71 forks Updated today MIT

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Skill Content

# Knowledge Curation ## Overview Two-phase knowledge management: prime context before work starts, and extract learnings after work completes. Knowledge persists in JSONL files for cross-session continuity. ## When to Use - Before starting any work (prime mode) - After completing work, BEFORE PR creation (reflect mode) - When recovering from context loss (recovery priming) ## Knowledge Categories | Category | File | Content | |----------|------|---------| | Critical Rules | facts.jsonl | MUST FOLLOW constraints | | Gotchas | gotchas.jsonl | Common pitfalls | | Patterns | patterns.jsonl | Codebase best practices | | Decisions | decisions.jsonl | Architectural choices with rationale | | Anti-Patterns | anti-patterns.jsonl | What NOT to do | | Codebase Facts | codebase-facts.jsonl | Structural information | | API Behaviors | api-behaviors.jsonl | Undocumented quirks | ## Process ### Prime Mode 1. Load knowledge base files for work type 2. Surface MUST FOLLOW rules first 3. Present GOTCHAS and PATTERNS 4. Load relevant DECISIONS ### Reflect Mode 1. Extract patterns from completed work 2. Identify gotchas from review failures 3. Record architectural decisions with rationale 4. Persist to .beads/knowledge/ ## Tool Use Invoke via babysitter process: `methodologies/metaswarm/metaswarm-knowledge-cycle`

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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