Evolve

Skill antonioshaman/aura-companion/.agents/skills/evolve

Self-learning AI companion — 29 skills: adaptive knowledge base + Carmack Council + impeccable design. Every session makes it smarter.

Install

npx -y skills add antonioshaman/aura-companion --skill evolve

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

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What its author says it does

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Meta-skill that analyzes the knowledge base itself — promotes recurring patterns to CLAUDE.md rules, prunes stale entries, identifies knowledge gaps, and suggests new skills.

SKILL.md

3.3 KB, 709 tokens by cl100k_base, as published. Nobody here has run it

Analyze and evolve the knowledge base and project configuration. This is the meta-improvement loop.

Process

1. Audit Knowledge Base Health

Read all .agents/knowledge/*.jsonl files and compute:

Total entries per category
Confidence distribution (how many high/medium/low)
Age distribution (entries older than 30 days may be stale)
Tag coverage (which areas of the codebase have knowledge, which don't)

2. Promote Recurring Patterns (mode: promote)

When a pattern appears 3+ times across sessions or has high confidence with broad impact:

Extract the core rule
Add it to the appropriate section in CLAUDE.md
Mark the KB entry as promoted: true (keep for history, but no longer surfaced by /prime)

Example promotion:

KB entry: "Always test WebSocket changes against both NDJSON and JSON-RPC backends"
→ Becomes a bullet point in CLAUDE.md's Architecture section

3. Prune Stale Entries (mode: prune)

An entry is stale when:

It references a file that no longer exists
It describes a bug that's been fixed (check git log)
Its recommendation contradicts a newer entry
It has confidence: low and is older than 14 days without re-confirmation
outdatedReports >= helpfulCount and outdatedReports >= 2 (the field-driven signal — at least two flags and no fresh confirmations to balance them)
usageCount >= 10 and helpfulCount == 0 (surfaced often but never re-confirmed → too generic to be useful)

Actions:

Remove clearly stale entries
Downgrade confidence on questionable entries
Flag uncertain entries for human review

4. Identify Knowledge Gaps (mode: gaps)

Cross-reference:

Files in web/server/ and web/src/ that have NO knowledge entries tagged to them
Recent commits that touched areas with no KB coverage
Test files without corresponding gotchas or patterns

Output a list of suggested areas to investigate.

5. Suggest New Skills

If the knowledge base reveals:

A repeated workflow that takes multiple steps → suggest a new skill to automate it
A category of gotchas around a specific tool/library → suggest a targeted skill
A testing pattern used frequently → suggest codifying it as a skill

6. Report

## Evolution Report

### Knowledge Base Health
- Total entries: N (patterns: X, gotchas: Y, decisions: Z, ...)
- Confidence: H high, M medium, L low
- Coverage: N/M source files have associated knowledge

### Actions Taken
- Promoted N patterns to CLAUDE.md
- Pruned N stale entries
- Downgraded N entries to lower confidence

### Knowledge Gaps
- [area]: no entries covering [specific aspect]

### Suggested Skills
- [skill-name]: [why it would be useful]

*Next evolution recommended: [date]*

When to Run

After 5+ sessions of accumulated learning
When the knowledge base exceeds 50 entries
Monthly as maintenance
When CLAUDE.md feels out of sync with actual development practices