Provide implementations of advanced data structures
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
FreePublished on GitHub
knowledge-curation
Context priming before work (bd prime) and self-reflection after completion to extract patterns, gotchas, and decisions into the knowledge base.
The English summary is being prepared. Showing the original description.
See how to installFiles included (2)
- SKILL.md1.6 KB
- README.md660 B
SKILL.md (original)
Review the instructions the agent will receive before you install.
- 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
- Load knowledge base files for work type
- Surface MUST FOLLOW rules first
- Present GOTCHAS and PATTERNS
- Load relevant DECISIONS
Reflect Mode
- Extract patterns from completed work
- Identify gotchas from review failures
- Record architectural decisions with rationale
- Persist to .beads/knowledge/
Tool Use
Invoke via babysitter process: methodologies/metaswarm/metaswarm-knowledge-cycle
Reviews
No reviews yet. Tell others what you thought.
Comments
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
More skills from this repository
Fresh adversarial code review with binary PASS/FAIL verdicts, evidence citations, and anchoring bias prevention via fresh reviewer spawning.
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
agent-booster
FreeWASM-based instant code transforms for simple tasks, achieving 352x speedup over LLM inference with zero cost.
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
Coordinate Crew (persistent) and Polecat (transient) agents using Gas Town's hook-based work distribution and GUPP principle.
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
Generate visual representations of algorithm execution
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026
anti-drift
FreeHierarchical coordination and drift detection with frequent checkpoints, shared memory coherence validation, role specialization enforcement, and short task cycles.
The English summary is being prepared. Showing the original description.
a5c-ai/babysitter1.9KUpdated Sep 17, 2026