Skill: testlbin/skill-evolver (version 0.1.0)

--- name: skill-evolver description: | A complete skill lifecycle manager for discovering, orchestrating, fusing, and evolving skills. Helps decide which skills to use, how to compose or fuse them, and whether to materialize a successful workflow into a new reusable skill. Trigger when: - User asks how to choose or combine skills - No single skill is sufficient and orchestration is needed - A solved workflow may need to be preserved as a new skill - Multiple skills need to be fused into one Do not trigger when: - User explicitly requests one specific skill - Native Claude ability is obviously sufficient --- # Skill Evolver Solve first. Materialize later. ## Workflow ### Phase 0: Setup Output Directory Create a timestamped output directory for this session: ```bash # Format: output/MM-DD-<feature-slug>/ # Example: output/03-09-pdf-translate/ mkdir -p "output/$(date +%m-%d)-<feature-slug>" ``` > **Tip**: Use a short slug derived from the task (e.g., `pdf-translate`, `data-export`, `api-integration`) Store the output path for subsequent phases: ``` OUTPUT_DIR=output/<created-directory> ``` ### Phase 1: Intent Analysis Analyze the user task and output `${OUTPUT_DIR}/01-intent.md`. See template: [references/templates/01-intent.md](references/templates/01-intent.md) ### Phase 2: Skill Search Follow the complete skill search workflow: → [references/skill-search.md](references/skill-search.md) This workflow covers: - CLI prerequisites and installation - Local + Registry (dual-track) search - Skill selection checkpoint - Installation and verification - Security audit **Output files:** - `${OUTPUT_DIR}/02-candidates.md` - Merged search results - `${OUTPUT_DIR}/02-verify.md` - Installation verification (if installed) - `${OUTPUT_DIR}/02-audit.md` - Security audit report (if installed) ### Phase 3: Deep Inspection For each candidate skill, perform deep analysis: Follow the workflow: [references/skill-inspector.md](references/skill-inspector.md) Output: `${OUTPUT_DIR}/03-inspection.md` ### Checkpoint: Approach Decision After inspection, evaluate whether skills can solve the task: **LLM evaluates:** - Do skill capabilities match task requirements? - Is modification needed? - Is fusion beneficial? **LLM Recommendation:** - **Orchestration** (skills match well, no major modification) - **Fusion** (skills partially match, combining creates new value) - **Native** (no suitable skills found) Options for user: - **A**: Orchestration (LLM recommended) - **B**: Skill Fusion (enter coding mode) - **C**: Use native abilities instead - **D**: Re-analyze (return to Phase 3) ### Phase 3.5: Skill Fusion (Conditional) Only if approach is **Fusion** Follow the complete skill fusion workflow: → [references/skill-fusion.md](references/skill-fusion.md) This workflow covers: - Fusion spec design - Invoke skill-creator - Audit fused skill **Output files:** - `${OUTPUT_DIR}/03-fusion-spec.md` - Fusion specification - `${OUTPUT_DIR}/03-fusion-audit.md` - Security audit (if fusion) ### Phase 4: Orchestration Design execution plan and output `${OUTPUT_DIR}/04-orchestration.md`. See template: [references/templates/04-orchestration.md](references/templates/04-orchestration.md) ### Checkpoint: Plan Confirmation Use `AskUserQuestion` tool (or similar tool to Human-in-the-Loop) to confirm plan: - **A**: Proceed with this plan - **B**: Modify the plan - **C**: Show alternatives - **D**: Additional requirements (then revise) ### Phase 5: Execution Execute the plan. For each step: - Native: use your own reasoning - Skill: invoke the skill with appropriate input ### Checkpoint: Materialization Decision Use `AskUserQuestion` tool (or similar tool to Human-in-the-Loop) to ask about preservation: - **A**: Yes, create a new skill (invoke `skill-creator`) - **B**: No, this was one-time - **C**: Save as draft for later review - **D**: Additional requirements (then adjust scope) ## Principles ``` Priority: native > orchestration > temporary > persistent - Prefer native for simple tasks - Prefer orchestration when existing skills can solve it - Materialize only after validation + proven reuse value - Always provide option [D] for additional input - Re-optimize when user provides new information ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)