Claude-Code-Workflow skill-tuning
Universal skill diagnosis and optimization tool. Detect and fix skill execution issues including context explosion, long-tail forgetting, data flow disruption, and agent coordination failures. Supports Gemini CLI for deep analysis. Triggers on "skill tuning", "tune skill", "skill diagnosis", "optimize skill", "skill debug".
install
source · Clone the upstream repo
git clone https://github.com/catlog22/Claude-Code-Workflow
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/catlog22/Claude-Code-Workflow "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills/skill-tuning" ~/.claude/skills/catlog22-claude-code-workflow-skill-tuning && rm -rf "$T"
manifest:
.claude/skills/skill-tuning/SKILL.mdsource content
Skill Tuning
Autonomous diagnosis and optimization for skill execution issues.
Architecture
┌─────────────────────────────────────────────────────┐ │ Phase 0: Read Specs (mandatory) │ │ → problem-taxonomy.md, tuning-strategies.md │ └─────────────────────────────────────────────────────┘ ↓ ┌─────────────────────────────────────────────────────┐ │ Orchestrator (state-driven) │ │ Read state → Select action → Execute → Update → ✓ │ └─────────────────────────────────────────────────────┘ ↓ ↓ ┌──────────────────────┐ ┌──────────────────┐ │ Diagnosis Phase │ │ Gemini CLI │ │ • Context │ │ Deep analysis │ │ • Memory │ │ (on-demand) │ │ • DataFlow │ │ │ │ • Agent │ │ Complex issues │ │ • Docs │ │ Architecture │ │ • Token Usage │ │ Performance │ └──────────────────────┘ └──────────────────┘ ↓ ┌───────────────────┐ │ Fix & Verify │ │ Apply → Re-test │ └───────────────────┘
Core Issues Detected
| Priority | Problem | Root Cause | Fix Strategy |
|---|---|---|---|
| P0 | Authoring Violation | Intermediate files, state bloat, file relay | eliminate_intermediate, minimize_state |
| P1 | Data Flow Disruption | Scattered state, inconsistent formats | state_centralization, schema_enforcement |
| P2 | Agent Coordination | Fragile chains, no error handling | error_wrapping, result_validation |
| P3 | Context Explosion | Unbounded history, full content passing | sliding_window, path_reference |
| P4 | Long-tail Forgetting | Early constraint loss | constraint_injection, checkpoint_restore |
| P5 | Token Consumption | Verbose prompts, state bloat | prompt_compression, lazy_loading |
Problem Categories (Detailed Specs)
See specs/problem-taxonomy.md for:
- Detection patterns (regex/checks)
- Severity calculations
- Impact assessments
Tuning Strategies (Detailed Specs)
See specs/tuning-strategies.md for:
- 10+ strategies per category
- Implementation patterns
- Verification methods
Workflow
| Step | Action | Orchestrator Decision | Output |
|---|---|---|---|
| 1 | | status='pending' | Backup, session created |
| 2 | | After init | Required dimensions + coverage |
| 3 | Diagnosis (6 types) | Focus areas | state.diagnosis.{type} |
| 4 | | Critical issues OR user request | Deep findings |
| 5 | | All diagnosis complete | state.final_report |
| 6 | | Issues found | state.proposed_fixes[] |
| 7 | | Pending fixes | Applied + verified |
| 8 | | Quality gates pass | session.status='completed' |
Action Reference
| Category | Actions | Purpose |
|---|---|---|
| Setup | action-init | Initialize backup, session state |
| Analysis | action-analyze-requirements | Decompose user request via Gemini CLI |
| Diagnosis | action-diagnose-{context,memory,dataflow,agent,docs,token_consumption} | Detect category-specific issues |
| Deep Analysis | action-gemini-analysis | Gemini CLI: complex/critical issues |
| Reporting | action-generate-report | Consolidate findings → final_report |
| Fixing | action-propose-fixes, action-apply-fix | Generate + apply fixes |
| Verify | action-verify | Re-run diagnosis, check gates |
| Exit | action-complete, action-abort | Finalize or rollback |
Full action details: phases/actions/
State Management
Single source of truth:
.workflow/.scratchpad/skill-tuning-{ts}/state.json
{ "status": "pending|running|completed|failed", "target_skill": { "name": "...", "path": "..." }, "diagnosis": { "context": {...}, "memory": {...}, "dataflow": {...}, "agent": {...}, "docs": {...}, "token_consumption": {...} }, "issues": [{"id":"...", "severity":"...", "category":"...", "strategy":"..."}], "proposed_fixes": [...], "applied_fixes": [...], "quality_gate": "pass|fail", "final_report": "..." }
See phases/state-schema.md for complete schema.
Orchestrator Logic
See phases/orchestrator.md for:
- Decision logic (termination checks → action selection)
- State transitions
- Error recovery
Key Principles
- Problem-First: Diagnosis before any fix
- Data-Driven: Record traces, token counts, snapshots
- Iterative: Multiple rounds until quality gates pass
- Reversible: All changes with backup checkpoints
- Non-Invasive: Minimal changes, maximum clarity
Usage Examples
# Basic skill diagnosis /skill-tuning "Fix memory leaks in my skill" # Deep analysis with Gemini /skill-tuning "Architecture issues in async workflow" # Focus on specific areas /skill-tuning "Optimize token consumption and fix agent coordination" # Custom issue /skill-tuning "My skill produces inconsistent outputs"
Output
After completion, review:
- Full state with final_report.workflow/.scratchpad/skill-tuning-{ts}/state.json
- Markdown summary (in state.json)state.final_report
- List of applied fixes with verification resultsstate.applied_fixes
Reference Documents
| Document | Purpose |
|---|---|
| specs/problem-taxonomy.md | Classification + detection patterns |
| specs/tuning-strategies.md | Fix implementation guide |
| specs/dimension-mapping.md | Dimension ↔ Spec mapping |
| specs/quality-gates.md | Quality verification criteria |
| phases/orchestrator.md | Workflow orchestration |
| phases/state-schema.md | State structure definition |
| phases/actions/ | Individual action implementations |