SuperAPI AI Directory

skill-evolution

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Updated 10-15 22:34

About this skill

Skill Evolution Manager

Enables skills to automatically improve based on usage patterns, user edits, and success rates. Provides version control with safe rollback capability.

Overview

  • Reviewing how skills are performing across sessions
  • Identifying patterns in user edits to skill outputs
  • Applying learned improvements to skill templates
  • Rolling back problematic skill changes
  • Tracking skill version history and success rates

Quick Reference

Command Description
/ork:skill-evolution Show evolution report for all skills
/ork:skill-evolution analyze <skill-id> Analyze specific skill patterns
/ork:skill-evolution evolve <skill-id> Review and apply suggestions
/ork:skill-evolution history <skill-id> Show version history
/ork:skill-evolution rollback <skill-id> <version> Restore previous version
/ork:skill-evolution promote <skill-id> Holdout bake-off: promote a candidate only if it beats champion by margin

How It Works

The skill evolution system operates in three phases:

COLLECT                    ANALYZE                    ACT
───────                    ───────                    ───
┌─────────────┐           ┌─────────────┐           ┌─────────────┐
│ PostTool    │──────────▶│ Evolution   │──────────▶│ /ork:skill- │
│ Edit        │  patterns │ Analyzer    │ suggest   │ evolution   │
│ Tracker     │           │ Engine      │           │ command     │
└─────────────┘           └─────────────┘           └─────────────┘
     │                          │                          │
     ▼                          ▼                          ▼
┌─────────────┐           ┌─────────────┐           ┌─────────────┐
│ edit-       │           │ evolution-  │           │ versions/   │
│ patterns.   │           │ registry.   │           │ snapshots   │
│ jsonl       │           │ json        │           │             │
└─────────────┘           └─────────────┘           └─────────────┘

Load details: Read("${CLAUDE_SKILL_DIR}/rules/pattern-detection-heuristics.md") for tracked edit patterns and detection regexes. Load details: Read("${CLAUDE_SKILL_DIR}/rules/confidence-scoring.md") for suggestion thresholds.


Subcommands

Each subcommand is documented with implementation details, shell commands, and sample output. Load details: Read("${CLAUDE_SKILL_DIR}/references/evolution-commands.md")

Report (Default)

/ork:skill-evolution — Shows evolution report for all tracked skills with usage counts, success rates, and pending suggestions.

Analyze

/ork:skill-evolution analyze <skill-id> — Deep-dives into edit patterns for a specific skill, showing frequency, sample counts, and confidence scores.

Evolve

/ork:skill-evolution evolve <skill-id> — Interactive review of improvement suggestions. Uses AskUserQuestion for each suggestion (Apply / Skip / Reject). Creates version snapshot before applying.

History

/ork:skill-evolution history <skill-id> — Shows version history with performance metrics per version.

Rollback

/ork:skill-evolution rollback <skill-id> <version> — Restores a previous version after confirmation. Current version is backed up automatically.


Data Files

File Purpose Format
.claude/feedback/edit-patterns.jsonl Raw edit pattern events JSONL (append-only)
.claude/feedback/evolution-registry.json Aggregated suggestions JSON
.claude/feedback/metrics.json Skill usage metrics JSON
skills/<cat>/<name>/versions/ Version snapshots Directory
skills/<cat>/<name>/versions/manifest.json Version metadata JSON

Auto-Evolution Safety

Load details: Read("${CLAUDE_SKILL_DIR}/rules/auto-evolution-triggers.md") for full safety mechanisms, health monitoring, and trigger criteria.

Key safeguards: version snapshots before changes, auto-alert on >20% success rate drop, human review required, rejected suggestions never re-suggested.


Holdout-Promotion Gate (Champion / Challenger)

/ork:skill-evolution promote <skill-id> — promote a candidate edit ONLY if it beats the current version on a sealed holdout eval set by a margin (default 0.5 on the 0–10 rubric). Both scores + the promote/reject decision append to an append-only promotion-ledger.jsonl for audit. This is the objective gate evolve was missing — an "Apply?" prompt is not proof the edit is better — and the native mechanism for "auto-evaluate all skills + agents to standard": a skill graduates by winning a bake-off, not by a human eyeballing a diff.

champion (HEAD) -- vs -- challenger (candidate)
        +--------+--------+
   SEALED HOLDOUT (hash-locked) -- bare-eval forked graders
                 v
   delta = challenger - champion >= margin ?  ->  PROMOTE : REJECT  (both logged)

Grading runs through bare-eval (--bare --print, CLAUDE_CODE_FORK_SUBAGENT=1) so champion and challenger see byte-identical, isolated conditions — the only variable is the SKILL.md version. Ties reject (incumbent wins); a per-dimension min_blocker auto-rejects a one-axis regression even when the composite improves.

Anti-gaming: the challenger generator never reads evals/holdout.jsonl (input allowlist = edit-patterns.jsonl only), and every bake-off + CI recomputes LC_ALL=C sha256 of the holdout against holdout.lock.json — train-on-test or a silent holdout edit fails closed. Expensive by design (2*N grader calls; --bare requires ANTHROPIC_API_KEY and bills tokens), so it runs on-demand or in CI only, never in a background hook ($0 idle).

Load details: Read("${CLAUDE_SKILL_DIR}/references/holdout-promotion-gate.md") — ledger/lock JSON schemas, decision rule, run loop, /goal + CI wiring.


References

Load on demand with Read("${CLAUDE_SKILL_DIR}/references/<file>"):

File Content
evolution-commands.md Subcommand implementation, shell commands, and sample output
evolution-analysis.md Evolution analysis methodology
version-management.md Version management guide
holdout-promotion-gate.md Champion/challenger gate: sealed holdout, ledger schema, decision rule, /goal + CI wiring

Rules

Load on demand with Read("${CLAUDE_SKILL_DIR}/rules/<file>"):

File Content
pattern-detection-heuristics.md Edit pattern categories and regex detection
confidence-scoring.md Suggestion thresholds and confidence criteria
auto-evolution-triggers.md Safety mechanisms and trigger criteria

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