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https://github.com/catlog22/Claude-Code-Workflow.git
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Add quality gates and tuning strategies documentation
- Introduced quality gates specification for skill tuning, detailing quality dimensions, scoring, and gate definitions. - Added comprehensive tuning strategies for various issue categories, including context explosion, long-tail forgetting, data flow, and agent coordination. - Created templates for diagnosis reports and fix proposals to standardize documentation and reporting processes.
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.claude/skills/skill-tuning/SKILL.md
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.claude/skills/skill-tuning/SKILL.md
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---
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name: skill-tuning
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description: 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".
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allowed-tools: Task, AskUserQuestion, Read, Write, Bash, Glob, Grep, mcp__ace-tool__search_context
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---
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# Skill Tuning
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Universal skill diagnosis and optimization tool that identifies and resolves skill execution problems through iterative multi-agent analysis.
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## Architecture Overview
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```
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┌─────────────────────────────────────────────────────────────────────────────┐
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│ Skill Tuning Architecture (Autonomous Mode + Gemini CLI) │
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├─────────────────────────────────────────────────────────────────────────────┤
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│ │
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│ ⚠️ Phase 0: Specification → 阅读规范 + 理解目标 skill 结构 (强制前置) │
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│ Study │
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│ ↓ │
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│ ┌───────────────────────────────────────────────────────────────────────┐ │
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│ │ Orchestrator (状态驱动决策) │ │
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│ │ 读取诊断状态 → 选择下一步动作 → 执行 → 更新状态 → 循环直到完成 │ │
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│ └───────────────────────────────────────────────────────────────────────┘ │
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│ │ │
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│ ┌────────────┬───────────┼───────────┬────────────┬────────────┐ │
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│ ↓ ↓ ↓ ↓ ↓ ↓ │
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│ ┌──────┐ ┌─────────┐ ┌────────┐ ┌────────┐ ┌────────┐ ┌─────────┐ │
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│ │ Init │ │Diagnose │ │Diagnose│ │Diagnose│ │Diagnose│ │ Gemini │ │
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│ │ │ │ Context │ │ Memory │ │DataFlow│ │ Agent │ │Analysis │ │
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│ └──────┘ └─────────┘ └────────┘ └────────┘ └────────┘ └─────────┘ │
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│ │ │ │ │ │ │ │
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│ └───────────┴───────────┴───────────┴────────────┴────────────┘ │
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│ ↓ │
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│ ┌──────────────────┐ │
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│ │ Apply Fixes + │ │
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│ │ Verify Results │ │
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│ └──────────────────┘ │
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│ │
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│ ┌───────────────────────────────────────────────────────────────────────┐ │
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│ │ Gemini CLI Integration │ │
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│ │ 根据用户需求动态调用 gemini cli 进行深度分析: │ │
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│ │ • 复杂问题分析 (prompt engineering, architecture review) │ │
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│ │ • 代码模式识别 (pattern matching, anti-pattern detection) │ │
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│ │ • 修复策略生成 (fix generation, refactoring suggestions) │ │
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│ └───────────────────────────────────────────────────────────────────────┘ │
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│ │
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└─────────────────────────────────────────────────────────────────────────────┘
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```
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## Problem Domain
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Based on comprehensive analysis, skill-tuning addresses **core skill issues** and **general optimization areas**:
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### Core Skill Issues (自动检测)
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| Priority | Problem | Root Cause | Solution Strategy |
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|----------|---------|------------|-------------------|
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| **P0** | Data Flow Disruption | Scattered state, inconsistent formats | Centralized session store, transactional updates |
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| **P1** | Agent Coordination | Fragile call chains, merge complexity | Dedicated orchestrator, enforced data contracts |
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| **P2** | Context Explosion | Token accumulation, multi-turn bloat | Context summarization, sliding window, structured state |
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| **P3** | Long-tail Forgetting | Early constraint loss | Constraint injection, checkpointing, goal alignment |
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### General Optimization Areas (按需分析 via Gemini CLI)
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| Category | Issues | Gemini Analysis Scope |
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|----------|--------|----------------------|
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| **Prompt Engineering** | 模糊指令, 输出格式不一致, 幻觉风险 | 提示词优化, 结构化输出设计 |
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| **Architecture** | 阶段划分不合理, 依赖混乱, 扩展性差 | 架构审查, 模块化建议 |
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| **Performance** | 执行慢, Token消耗高, 重复计算 | 性能分析, 缓存策略 |
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| **Error Handling** | 错误恢复不当, 无降级策略, 日志不足 | 容错设计, 可观测性增强 |
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| **Output Quality** | 输出不稳定, 格式漂移, 质量波动 | 质量门控, 验证机制 |
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| **User Experience** | 交互不流畅, 反馈不清晰, 进度不可见 | UX优化, 进度追踪 |
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## Key Design Principles
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1. **Problem-First Diagnosis**: Systematic identification before any fix attempt
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2. **Data-Driven Analysis**: Record execution traces, token counts, state snapshots
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3. **Iterative Refinement**: Multiple tuning rounds until quality gates pass
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4. **Non-Destructive**: All changes are reversible with backup checkpoints
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5. **Agent Coordination**: Use specialized sub-agents for each diagnosis type
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6. **Gemini CLI On-Demand**: Deep analysis via CLI for complex/custom issues
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---
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## Gemini CLI Integration
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根据用户需求动态调用 Gemini CLI 进行深度分析。
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### Trigger Conditions
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| Condition | Action | CLI Mode |
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|-----------|--------|----------|
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| 用户描述复杂问题 | 调用 Gemini 分析问题根因 | `analysis` |
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| 自动诊断发现 critical 问题 | 请求深度分析确认 | `analysis` |
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| 用户请求架构审查 | 执行架构分析 | `analysis` |
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| 需要生成修复代码 | 生成修复提案 | `write` |
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| 标准策略不适用 | 请求定制化策略 | `analysis` |
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### CLI Command Template
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```bash
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ccw cli -p "
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PURPOSE: ${purpose}
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TASK: ${task_steps}
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MODE: ${mode}
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CONTEXT: @${skill_path}/**/*
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EXPECTED: ${expected_output}
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RULES: $(cat ~/.claude/workflows/cli-templates/protocols/${mode}-protocol.md) | ${constraints}
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" --tool gemini --mode ${mode} --cd ${skill_path}
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```
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### Analysis Types
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#### 1. Problem Root Cause Analysis
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```bash
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ccw cli -p "
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PURPOSE: Identify root cause of skill execution issue: ${user_issue_description}
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TASK: • Analyze skill structure and phase flow • Identify anti-patterns • Trace data flow issues
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MODE: analysis
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CONTEXT: @**/*.md
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EXPECTED: JSON with { root_causes: [], patterns_found: [], recommendations: [] }
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RULES: $(cat ~/.claude/workflows/cli-templates/protocols/analysis-protocol.md) | Focus on execution flow
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" --tool gemini --mode analysis
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```
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#### 2. Architecture Review
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```bash
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ccw cli -p "
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PURPOSE: Review skill architecture for scalability and maintainability
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TASK: • Evaluate phase decomposition • Check state management patterns • Assess agent coordination
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MODE: analysis
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CONTEXT: @**/*.md
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EXPECTED: Architecture assessment with improvement recommendations
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RULES: $(cat ~/.claude/workflows/cli-templates/protocols/analysis-protocol.md) | Focus on modularity
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" --tool gemini --mode analysis
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```
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#### 3. Fix Strategy Generation
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```bash
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ccw cli -p "
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PURPOSE: Generate fix strategy for issue: ${issue_id} - ${issue_description}
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TASK: • Analyze issue context • Design fix approach • Generate implementation plan
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MODE: analysis
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CONTEXT: @**/*.md
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EXPECTED: JSON with { strategy: string, changes: [], verification_steps: [] }
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RULES: $(cat ~/.claude/workflows/cli-templates/protocols/analysis-protocol.md) | Minimal invasive changes
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" --tool gemini --mode analysis
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```
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---
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## Mandatory Prerequisites
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> **CRITICAL**: Read these documents before executing any action.
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### Core Specs (Required)
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| Document | Purpose | Priority |
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|----------|---------|----------|
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| [specs/problem-taxonomy.md](specs/problem-taxonomy.md) | Problem classification and detection patterns | **P0** |
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| [specs/tuning-strategies.md](specs/tuning-strategies.md) | Fix strategies for each problem type | **P0** |
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| [specs/quality-gates.md](specs/quality-gates.md) | Quality thresholds and verification criteria | P1 |
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### Templates (Reference)
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| Document | Purpose |
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|----------|---------|
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| [templates/diagnosis-report.md](templates/diagnosis-report.md) | Diagnosis report structure |
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| [templates/fix-proposal.md](templates/fix-proposal.md) | Fix proposal format |
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---
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## Execution Flow
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```
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┌─────────────────────────────────────────────────────────────────────────────┐
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│ Phase 0: Specification Study (强制前置 - 禁止跳过) │
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│ → Read: specs/problem-taxonomy.md (问题分类) │
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│ → Read: specs/tuning-strategies.md (调优策略) │
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│ → Read: Target skill's SKILL.md and phases/*.md │
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│ → Output: 内化规范,理解目标 skill 结构 │
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├─────────────────────────────────────────────────────────────────────────────┤
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│ action-init: Initialize Tuning Session │
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│ → Create work directory: .workflow/.scratchpad/skill-tuning-{timestamp} │
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│ → Initialize state.json with target skill info │
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│ → Create backup of target skill files │
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├─────────────────────────────────────────────────────────────────────────────┤
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│ action-diagnose-context: Context Explosion Analysis │
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│ → Scan for token accumulation patterns │
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│ → Detect multi-turn dialogue growth │
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│ → Output: context-diagnosis.json │
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├─────────────────────────────────────────────────────────────────────────────┤
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│ action-diagnose-memory: Long-tail Forgetting Analysis │
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│ → Trace constraint propagation through phases │
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│ → Detect early instruction loss │
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│ → Output: memory-diagnosis.json │
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├─────────────────────────────────────────────────────────────────────────────┤
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│ action-diagnose-dataflow: Data Flow Analysis │
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│ → Map state transitions between phases │
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│ → Detect format inconsistencies │
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│ → Output: dataflow-diagnosis.json │
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├─────────────────────────────────────────────────────────────────────────────┤
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│ action-diagnose-agent: Agent Coordination Analysis │
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│ → Analyze agent call patterns │
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│ → Detect result passing issues │
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│ → Output: agent-diagnosis.json │
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├─────────────────────────────────────────────────────────────────────────────┤
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│ action-generate-report: Consolidated Report │
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│ → Merge all diagnosis results │
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│ → Prioritize issues by severity │
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│ → Output: tuning-report.md │
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├─────────────────────────────────────────────────────────────────────────────┤
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│ action-propose-fixes: Fix Proposal Generation │
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│ → Generate fix strategies for each issue │
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│ → Create implementation plan │
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│ → Output: fix-proposals.json │
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├─────────────────────────────────────────────────────────────────────────────┤
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│ action-apply-fix: Apply Selected Fix │
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│ → User selects fix to apply │
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│ → Execute fix with backup │
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│ → Update state with fix result │
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├─────────────────────────────────────────────────────────────────────────────┤
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│ action-verify: Verification │
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│ → Re-run affected diagnosis │
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│ → Check quality gates │
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│ → Update iteration count │
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├─────────────────────────────────────────────────────────────────────────────┤
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│ action-complete: Finalization │
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│ → Generate final report │
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│ → Cleanup temporary files │
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│ → Output: tuning-summary.md │
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└─────────────────────────────────────────────────────────────────────────────┘
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```
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## Directory Setup
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```javascript
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const timestamp = new Date().toISOString().slice(0,19).replace(/[-:T]/g, '');
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const workDir = `.workflow/.scratchpad/skill-tuning-${timestamp}`;
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Bash(`mkdir -p "${workDir}/diagnosis"`);
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Bash(`mkdir -p "${workDir}/backups"`);
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Bash(`mkdir -p "${workDir}/fixes"`);
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```
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## Output Structure
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```
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.workflow/.scratchpad/skill-tuning-{timestamp}/
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├── state.json # Session state (orchestrator-managed)
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├── diagnosis/
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│ ├── context-diagnosis.json # Context explosion analysis
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│ ├── memory-diagnosis.json # Long-tail forgetting analysis
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│ ├── dataflow-diagnosis.json # Data flow analysis
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│ └── agent-diagnosis.json # Agent coordination analysis
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├── backups/
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│ └── {skill-name}-backup/ # Original skill files backup
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├── fixes/
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│ ├── fix-proposals.json # Proposed fixes
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│ └── applied-fixes.json # Applied fix history
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├── tuning-report.md # Consolidated diagnosis report
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└── tuning-summary.md # Final summary
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```
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## State Schema
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```typescript
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interface TuningState {
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status: 'pending' | 'running' | 'completed' | 'failed';
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target_skill: {
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name: string;
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path: string;
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execution_mode: 'sequential' | 'autonomous';
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};
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user_issue_description: string;
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diagnosis: {
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context: DiagnosisResult | null;
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memory: DiagnosisResult | null;
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dataflow: DiagnosisResult | null;
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agent: DiagnosisResult | null;
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};
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issues: Issue[];
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proposed_fixes: Fix[];
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applied_fixes: AppliedFix[];
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iteration_count: number;
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max_iterations: number;
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quality_score: number;
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completed_actions: string[];
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current_action: string | null;
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errors: Error[];
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error_count: number;
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}
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interface DiagnosisResult {
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status: 'completed' | 'skipped';
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issues_found: number;
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severity: 'critical' | 'high' | 'medium' | 'low' | 'none';
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details: any;
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}
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interface Issue {
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id: string;
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type: 'context_explosion' | 'memory_loss' | 'dataflow_break' | 'agent_failure';
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severity: 'critical' | 'high' | 'medium' | 'low';
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location: string;
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description: string;
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evidence: string[];
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}
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interface Fix {
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id: string;
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issue_id: string;
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strategy: string;
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description: string;
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changes: FileChange[];
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risk: 'low' | 'medium' | 'high';
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}
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```
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## Reference Documents
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| Document | Purpose |
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|----------|---------|
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| [phases/orchestrator.md](phases/orchestrator.md) | Orchestrator decision logic |
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| [phases/state-schema.md](phases/state-schema.md) | State structure definition |
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| [phases/actions/action-init.md](phases/actions/action-init.md) | Initialize tuning session |
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| [phases/actions/action-diagnose-context.md](phases/actions/action-diagnose-context.md) | Context explosion diagnosis |
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| [phases/actions/action-diagnose-memory.md](phases/actions/action-diagnose-memory.md) | Long-tail forgetting diagnosis |
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| [phases/actions/action-diagnose-dataflow.md](phases/actions/action-diagnose-dataflow.md) | Data flow diagnosis |
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| [phases/actions/action-diagnose-agent.md](phases/actions/action-diagnose-agent.md) | Agent coordination diagnosis |
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| [phases/actions/action-generate-report.md](phases/actions/action-generate-report.md) | Report generation |
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| [phases/actions/action-propose-fixes.md](phases/actions/action-propose-fixes.md) | Fix proposal |
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| [phases/actions/action-apply-fix.md](phases/actions/action-apply-fix.md) | Fix application |
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| [phases/actions/action-verify.md](phases/actions/action-verify.md) | Verification |
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| [phases/actions/action-complete.md](phases/actions/action-complete.md) | Finalization |
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| [specs/problem-taxonomy.md](specs/problem-taxonomy.md) | Problem classification |
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| [specs/tuning-strategies.md](specs/tuning-strategies.md) | Fix strategies |
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| [specs/quality-gates.md](specs/quality-gates.md) | Quality criteria |
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Reference in New Issue
Block a user