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cc-agent-audit
Claude Code 專案配置審計。觸發:review/優化 CLAUDE.md、skills、settings、定期清洗累積內容、新專案上線前檢查。
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// RATINGS
// README
A batteries-included working environment for Claude Code. Dispatch agents, skills, and statusline — all extracted from daily production use.
What's Inside
ai-toolkit/
├── agents/ # SOP agents (symlink to ~/.claude/agents/)
│ ├── analyst.md # Architecture / Planning / Audit
│ ├── investigator.md # Search / Explore / Debug / External research
│ ├── builder.md # Code implementation / Testing
│ ├── reviewer.md # Code review / Dead code cleanup
│ ├── doc-sync.md # Doc init / Doc sync
│ └── agent-factory.md # Design and generate new agents
├── skills/ # Skills (symlink to ~/.claude/skills/)
│ ├── handoff/ # Session handoff
│ ├── thorough/ # Relentless delivery mode
│ ├── vector-memory/ # Persistent vector memory usage guide
│ ├── project-docs/ # Project documentation structure
│ ├── agentskill-expertise/ # Skill design knowledge base
│ ├── collaboration-style/ # AI-human collaboration framework
│ └── self-growth/ # Continuous learning framework
├── domain-skills/ # Domain-specific skill sets
│ ├── darkseoking/ # SEO & Threads algorithm (3 skills)
│ └── claude-code/ # Claude Code reverse engineering (6 skills)
├── mcp.example.json # MCP server config template
└── statusline/ # Cost & context monitoring
Agents
SOP-style prompts for Claude Code's Agent tool. When /thorough dispatches parallel subagents, prompt quality determines output quality — these agents provide step-based workflows with hard thresholds, classification heuristics, and structured output formats.
| Agent | Model | When to use |
|---|---|---|
analyst | sonnet | "design this", "plan the implementation", "audit codebase health" |
investigator | haiku | "find all usages of X", "how does this work", "why does this fail" |
builder | sonnet | "implement this", "modify the handler", "write tests for X" |
reviewer | sonnet | "review this code", "find dead code", "clean up unused exports" |
doc-sync | haiku | "set up project docs", "sync docs after changes" |
agent-factory | opus | "create a new agent", "improve this agent's prompt" |
Each agent auto-detects its mode from dispatch context. One agent, multiple workflows.
Design Principles
- Zero concept explanation — All operational instructions. Claude already knows what CQRS is.
- Step-based SOP — "Do X, then Y, if Z threshold → action." Not "You are an expert at..."
- Hard rules as threshold + trigger —
>50 lines → flag,>4 nesting levels → flag. Not "keep functions small." - Classification heuristics —
AUTO-FIX / ASK / CRITICALwith concrete criteria. Not checklists. - Structured output — Every agent ends with a report template. Consistent, parseable.
Skills
| Skill | Description |
|---|---|
/handoff | Session handoff — compress context into a structured prompt for seamless continuation |
/thorough | Relentless delivery mode — exhaust all options, cost-aware model selection, verify before done |
/vector-memory | Persistent vector memory via LanceDB — store facts, decisions, lessons across sessions |
/project-docs | Project documentation structure — standard proj-[name]/ layout with ADRs, stories, and operations guides |
/agentskill-expertise | Agent Skill design knowledge base — mechanisms, philosophy, patterns, pitfalls |
/collaboration-style | AI-human collaboration norms — friction cases, coding style, behavioral guidelines |
/self-growth | Continuous learning framework — learn from work, organize knowledge, build feedback loops |
Domain Skills
Deep skill sets built around specific topics or practitioners' methodologies. Unlike generic skills, these encode domain expertise with layered architecture (knowledge → operations → prediction).
| Domain | Skills | Description |
|---|---|---|
| darkseoking | 3 | SEO & Threads algorithm — mindset (8 mental models), post optimizer (pre-publish checklist), post predictor (V2 dual-stage Views×ER) |
| claude-code | 6 | Claude Code reverse engineering — prompt craft, cost engineering, harness patterns, security, agent design, agent audit |
Each domain has its own README with setup instructions and architecture overview.
MCP Servers
Example configuration for the MCP servers used in this toolkit.
mcp.example.json— copy to your project as.mcp.jsonand fill in your API keys.
| Server | What it does |
|---|---|
@cablate/memory-lancedb-mcp | Persistent vector memory with hybrid search (semantic + keyword) |
| Serena | Semantic code intelligence — symbol search, references, refactoring |
Statusline
Cost and context monitoring for Claude Code. Two-line display with context alerts and plan usage tracking.
Normal (< 60% context):
┌──────────────────────────────────────────────────────────────────┐
│ Claude Opus 4 | [=======--------------] 45.2K/200.0K 22.6% │
│ 5h: 12.3% (4h 22m) | 7d: 8.1% (6d 3h) │
└──────────────────────────────────────────────────────────────────┘
Warning (>= 60% context):
┌──────────────────────────────────────────────────────────────────┐
│ Claude Sonnet 4 | concise | [============--------] 130.5K/200.0K 65.3% /handoff soon │
│ 5h: 45.0% (2h 10m) | 7d: 22.4% (5d 1h) │
└──────────────────────────────────────────────────────────────────┘
Critical (>= 80% context):
┌──────────────────────────────────────────────────────────────────┐
│ Claude Opus 4 | [==================--] 310.0K/200.0K 95.0% !! HANDOFF NOW !! │
│ 5h: 78.2% (1h 05m) | 7d: 51.3% (3d 12h) │
│ !! DO NOT close/resume -- use /handoff first, or waste 6%+ of 5h tokens !! │
└──────────────────────────────────────────────────────────────────┘
Line 1 — Model name, output style (if not default), context progress bar with K-precision token counts, usage %, and alerts at 150K/200K/300K thresholds.
Line 2 — 5-hour and 7-day plan usage rates with reset countdowns. Fetched from Claude API (cached 5min) or inline rate_limits (v2.1.80+).
Line 3 — Appears at 250K+ tokens. Hard warning against closing/resuming without handoff.
// ~/.claude/settings.json
{ "status_line_command": "powershell -NoProfile -File C:/Users/YOU/.claude/statusline.ps1" }
License
// HOW IT'S BUILT
KEY FILES