knowledge-curation

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

509 stars

Best use case

knowledge-curation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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

Teams using knowledge-curation should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/knowledge-curation/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/methodologies/metaswarm/skills/knowledge-curation/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/knowledge-curation/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How knowledge-curation Compares

Feature / Agentknowledge-curationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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`

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