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🦀 ClawHub

Codex Review

by @abczsl520

Three-tier code quality defense: L1 quick scan, L2 deep audit (via bug-audit), L3 cross-validation with adversarial testing. 三级代码质量防线。

Versionv2.1.0
Downloads754
#crypto-defi#legal
TERMINAL
clawhub install codex-review

📖 About This Skill

name: codex-review version: 2.1.0 description: "Three-tier code quality defense: L1 quick scan, L2 deep audit (via bug-audit), L3 cross-validation with adversarial testing. 三级代码质量防线。" metadata: { "openclaw": { "emoji": "🔍" } } tags: - code-review - quality-assurance - bug-detection - security-audit - cross-validation - ai-code-review - nodejs - openclaw-skill - clawhub - devops

Codex Review — Three-Tier Code Quality Defense

Unified orchestration layer: picks audit depth based on trigger phrases. bug-audit is invoked as an independent skill — never modified.

Security & Privacy

  • Read-only by default: This skill only reads your project files for analysis. It does NOT modify, delete, or upload your code anywhere.
  • Optional external model: L1/L3 can use an external code-review API (OpenAI-compatible) for a second opinion. This is opt-in — if no API key is configured, the skill works fine with agent-only review.
  • Credentials via environment variables only: API keys are loaded from CODEX_REVIEW_API_KEY env var. Never hardcoded, never logged, never stored.
  • Local-only artifacts: Hotspot files are written to system temp directory and auto-cleaned. No network transmission of analysis results.
  • No data exfiltration: Code snippets sent to the external API are limited to the files being reviewed. No telemetry, no analytics, no third-party data sharing beyond the configured review model.

    • Prerequisites

  • External model API (optional, for L1 Round 1 and L3): Any OpenAI-compatible endpoint.
    • - Set env vars: CODEX_REVIEW_API_BASE (default: https://api.openai.com/v1), CODEX_REVIEW_API_KEY, CODEX_REVIEW_MODEL (default: gpt-4o) - Works without this — falls back to agent-only audit
  • bug-audit skill (optional): Required for L2/L3. Without it, L2 uses a built-in fallback.
  • curl: For API calls (standard on macOS/Linux)

    • Trigger Mapping

    | User says | Level | What it does | Est. time | |-----------|-------|--------------|-----------| | "review" / "quick scan" / "review下" / "检查下" | L1 | External model scan + agent deep pass | 5-10 min | | "audit" / "deep audit" / "审计下" / "排查下" | L2 | Full bug-audit flow (or built-in fallback) | 30-60 min | | "pre-deploy check" / "上线前检查" | L1→L2 | L1 scan → record hotspots → L2 audit → hotspot gap check | 40-70 min | | "cross-validate" / "highest level" / "交叉验证" | L3 | Dual independent audits + compare + adversarial test | 60-90 min |

    Level 1: Quick Scan (core of codex-review)

    Flow

    1. Gather code — local read, git clone , server scp, user-pasted snippet, or PR diff 2. Exclude — node_modules/, .git/, package-lock.json, dist/, *.db, __pycache__/, vendor/ 3. Round 1 — send to external model API for automated scan (skipped if no API key) 4. Round 2 — current agent does deep supplementary pass 5. Merge & dedup — output severity-graded report 6. Write hotspot file (for L1→L2 handoff)

    External Model API Call

    curl -s "${CODEX_REVIEW_API_BASE:-https://api.openai.com/v1}/chat/completions" \
  -H "Authorization: Bearer ${CODEX_REVIEW_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "${CODEX_REVIEW_MODEL:-gpt-4o}",
    "messages": [
      {"role": "system", "content": ""},
      {"role": "user", "content": ""}
    ],
    "temperature": 0.2,
    "max_tokens": 6000
  }'

    Fallback: If API call fails or times out (120s), skip Round 1 and complete with agent-only audit.

    System Prompt (L1 External Scan)

    You are an expert code reviewer. Find ALL bugs and security issues:
1. CRITICAL — Security vulnerabilities (XSS, injection, auth bypass), crash bugs
2. HIGH — Logic errors, race conditions, unhandled exceptions
3. MEDIUM — Missing validation, edge cases, performance issues
4. LOW — Code style, dead code, minor improvements
    For each: Severity, File+line, Issue, Fix with code snippet.
Focus on real bugs, not style opinions. Output language: match the user's language.

    Agent Round 2 — Universal Checklist

  • [ ] Cross-file logic consistency (imports, exports, shared state)
  • [ ] Authentication & authorization bypass
  • [ ] Race conditions (concurrent requests, DB write conflicts)
  • [ ] Unhandled exceptions / missing error boundaries
  • [ ] Input validation & sanitization (SQL injection, XSS, path traversal)
  • [ ] Memory/resource leaks (unclosed connections, event listener buildup)
  • [ ] Sensitive data exposure (keys in code, logs, error messages)
  • [ ] Timezone handling (UTC vs local)
  • [ ] Dependency vulnerabilities (outdated packages, known CVEs)

    • Agent Round 2 — Tech-Stack Specific (auto-detect & apply)

    Node.js/Express:

  • [ ] SQLite pitfalls (DEFAULT doesn't support functions, double-quote = column name)
  • [ ] Middleware ordering (auth before route handlers)
  • [ ] pm2/cluster mode compatibility

    • Python/Django/Flask:

  • [ ] ORM N+1 queries
  • [ ] CSRF protection enabled
  • [ ] Debug mode in production

    • Frontend (React/Vue/vanilla):

  • [ ] innerHTML / dangerouslySetInnerHTML without sanitization
  • [ ] WebView compatibility (WeChat, in-app browsers)
  • [ ] Nginx sub-path / base URL issues

    • Other stacks: adapt checklist to detected technology.

    Code Volume Control

  • Single API request: backend core files only (server + routes + db + config)
  • Send frontend as a second batch if needed
  • Very large projects (>50 files): summarize file tree first, then scan in priority order

    • Hotspot File (L1→L2 handoff)

    After L1, write issue summary to ${TMPDIR:-/tmp}/codex-review-hotspots.json: 
    {
  "project": "my-project",
  "timestamp": "2026-03-05T22:00:00",
  "hotspots": [
    {"file": "routes/admin.js", "severity": "CRITICAL", "brief": "Admin auth bypass via localhost"},
    {"file": "routes/game.js", "severity": "CRITICAL", "brief": "Score submission no server validation"}
  ]
}

    This file is only used internally for L1→L2 handoff. bug-audit is unaware of it.

    Level 2: Deep Audit

    Flow (bug-audit available)

    1. Read bug-audit's SKILL.md and execute its full flow (6 Phases) 2. bug-audit itself is never modified 3. Agent strictly follows bug-audit's specification

    Flow (bug-audit NOT available — built-in fallback)

    1. Phase 1: Project Dissection — read all source files, build dependency graph 2. Phase 2: Build Check Matrix — generate project-specific checklist from actual code patterns 3. Phase 3: Exhaustive Verification — verify every checklist item against real code 4. Phase 4: Reproduce — for each finding, trace the exact execution path 5. Phase 5: Report — output full severity-graded report 6. Phase 6: Fix Suggestions — provide concrete code patches

    Level 1→2 Cascade: Pre-Deploy Check

    Flow

    1. Execute L1 quick scan 2. Write hotspot file 3. Execute L2 (bug-audit or fallback) 4. After L2, agent does hotspot gap analysis: - Read hotspot file - Check if L2 report covers each L1 hotspot - Uncovered hotspots → targeted deep analysis, add to report - L1 vs L2 conclusions conflict → flag for manual review 5. Output final merged report

    Level 3: Cross-Validation (highest level)

    Flow

    Step 1: External model independent audit
  → Full code to external API with detailed system prompt
  → Output: Report A
    Step 2: Agent independent audit (bug-audit or fallback)
  → Full bug-audit flow (or built-in fallback)
  → Output: Report B
    Step 3: Cross-compare
  → Both found       → 🔴 Confirmed high-risk (high confidence)
  → Only external    → 🟡 Agent verifies (possible false positive)
  → Only agent       → 🟡 External verifies (possible deep logic bug)
  → Contradictory    → ⚠️ Deep analysis, provide judgment
    Step 4: Adversarial testing
  → Ask external model to bypass discovered fixes
  → Validate fix robustness

    Adversarial Test Prompt

    You are a security researcher. The following security fixes were applied to a project.
For each fix, analyze:
1. Can the fix be bypassed? How?
2. Does the fix introduce new vulnerabilities?
3. Are there edge cases the fix doesn't cover?
Be adversarial and thorough. Output language: match the user's language.

    Report Format (all levels)

    # 🔍 Code Audit Report — [Project Name]

    Audit Level: L1 / L2 / L3
    

    📊 Overview
    

  • Files scanned: X
    • 

  • Issues found: X (🔴 Critical X | 🟠 High X | 🟡 Medium X | 🔵 Low X)
    • 

  • [L3 only] Cross-validation: Both agreed X | External only X | Agent only X | Conflict X
    • 🔴 Critical Issues
    

    1. [Issue Title]
    

  • File: path/to/file.js:42-55
    • 

  • Found by: External model / Agent / Both
    • 

  • Description: ...
    • 

  • Fix:
    • 
(code snippet)
    ✅ Highlights
    

  • [What's done well]
    •

    User Options

    Users can customize behavior by saying:

  • "only scan backend" / "只扫后端" → skip frontend files
  • "ignore LOW" / "忽略低级别" → filter out LOW severity
  • "output in English/Chinese" → control report language
  • "scan this PR" / "审这个PR" → fetch PR diff instead of full codebase
  • "skip external model" / "不用外部模型" → agent-only audit

    • Notes

    1. External API timeout: 120 seconds. On failure, skip that round — agent completes independently 2. Large projects: split into batches (backend → frontend → config) 3. Long reports: split across multiple messages, adapted to current channel 4. L2/L3 bug-audit execution strictly follows its own SKILL.md — no modifications or shortcuts 5. Hotspot file is ephemeral — overwritten each L1 run, not persisted 6. All secrets/keys must come from env vars or user config — never hardcoded in this skill

    ⚙️ Configuration

  • External model API (optional, for L1 Round 1 and L3): Any OpenAI-compatible endpoint.
    • - Set env vars: CODEX_REVIEW_API_BASE (default: https://api.openai.com/v1), CODEX_REVIEW_API_KEY, CODEX_REVIEW_MODEL (default: gpt-4o) - Works without this — falls back to agent-only audit
  • bug-audit skill (optional): Required for L2/L3. Without it, L2 uses a built-in fallback.
  • curl: For API calls (standard on macOS/Linux)

    • 📋 Tips & Best Practices

    1. External API timeout: 120 seconds. On failure, skip that round — agent completes independently 2. Large projects: split into batches (backend → frontend → config) 3. Long reports: split across multiple messages, adapted to current channel 4. L2/L3 bug-audit execution strictly follows its own SKILL.md — no modifications or shortcuts 5. Hotspot file is ephemeral — overwritten each L1 run, not persisted 6. All secrets/keys must come from env vars or user config — never hardcoded in this skill