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skill-idea-miner

Mine Claude Code session logs for skill idea candidates. Use when running the skill generation pipeline to extract, score, and backlog new skill ideas from recent coding sessions.

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查看安装方法

包含的文件(7)

  • SKILL.md2.9 KB
  • references/idea_extraction_rubric.md6.3 KB
  • scripts/mine_session_logs.py24.4 KB
  • scripts/score_ideas.py15.1 KB
  • scripts/tests/conftest.py223 B
  • scripts/tests/test_mine_session_logs.py30.8 KB
  • scripts/tests/test_score_ideas.py9.9 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Skill Idea Miner

Automatically extract skill idea candidates from Claude Code session logs, score them for novelty, feasibility, and work utility, and maintain a prioritized backlog for downstream skill generation.

When to Use

  • Weekly automated pipeline run for skill idea generation
  • Manual backlog refresh: python3 scripts/mine_session_logs.py
  • Dry-run to preview candidates without LLM scoring

Workflow

Stage 1: Session Log Mining

  1. Enumerate session logs from project directories in ~/.claude/projects/
  2. Filter to past 7 days by file mtime, confirm with timestamp field
  3. Extract user messages (type: "user", userType: "external")
  4. Extract tool usage patterns from assistant messages
  5. Run deterministic signal detection:
    • Skill usage frequency (skills/*/ path references)
    • Error patterns (non-zero exit codes, is_error flags, exception keywords)
    • Repetitive tool sequences (3+ tools repeated 3+ times)
    • Automation request keywords (English and Japanese)
    • Unresolved requests (5+ minute gap after user message)
  6. Invoke Claude CLI headless for idea abstraction
  7. Output raw_candidates.yaml

Stage 2: Scoring and Deduplication

  1. Load existing skills from skills/*/SKILL.md frontmatter
  2. Deduplicate via Jaccard similarity (threshold > 0.5) against:
    • Existing skill names and descriptions
    • Existing backlog ideas
  3. Score non-duplicate candidates with Claude CLI:
    • Novelty (0-100): differentiation from existing skills
    • Feasibility (0-100): technical implementability
    • Work Utility (0-100): practical value for business professionals
    • Composite = 0.3 * Novelty + 0.3 * Feasibility + 0.4 * Work Utility
  4. Merge scored candidates into logs/.skill_generation_backlog.yaml

Output Format

raw_candidates.yaml

generated_at_utc: "2026-03-08T06:00:00Z"
lookback_days: 7
sessions_analyzed: 12
candidates:
  - id: "raw_20260308_001"
    title: "Project Charter Generator"
    scanned_projects: ["PycharmProjects-claude-skills-library"]
    description: "Generate project charters from requirements."
    category: "project-management"

Backlog (logs/.skill_generation_backlog.yaml)

updated_at_utc: "2026-03-08T06:15:00Z"
ideas:
  - id: "idea_20260308_001"
    title: "Project Charter Generator"
    description: "Skill that generates project charters..."
    category: "project-management"
    scores: {novelty: 75, feasibility: 60, work_utility: 80, composite: 72.5}
    status: "pending"

Resources

  • references/idea_extraction_rubric.md -- Signal detection criteria and scoring rubric
  • scripts/mine_session_logs.py -- Session log parser
  • scripts/score_ideas.py -- Scorer and deduplicator

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