name: code-inspector description: Scan AI-generated code for bugs before deploying — 8 static analysis checks from critical (hardcoded secrets, unsafe eval) to low (unused imports). Production-readiness score 0-100. Because AI code looks fine until it isn't. version: 1.2.0 author: minirr890112-byte license: MIT metadata: hermes: tags: [Code-Review, Static-Analysis, Security, AI-Code, Quality, CLI, Python] homepage: https://github.com/minirr890112-byte/code-inspector
The problem: AI generates code that compiles and looks correct. But it silently drops edge case handling, hardcodes secrets, catches exceptions with bare except/pass, and uses mutable defaults. You deploy it. It breaks. Reddit is full of "I let Claude loose and it broke the entire site" stories.
The solution: One command scans any Python file for 8 categories of AI-code bugs. Critical → High → Medium → Low severity. Production-readiness score 0-100. Don't deploy AI code blind.
pip install git+https://github.com/minirr890112-byte/code-inspector.git
code-inspector app.py # scan a file
cat app.py | code-inspector # scan from pipe
| Check | Severity | Example |
|---|---|---|
| Hardcoded secrets | 🔴 critical | api_key = "sk-abc123" |
| Unsafe eval/exec | 🔴 critical | eval(user_input) |
| Infinite loops | 🔴 critical | append-while-iterating |
| Mutable defaults | 🟠 high | def fn(items=[]) |
| Shadowed builtins | 🟠 high | list = [1,2,3] |
| Bare except/pass | 🔴 critical | except: pass |
| Deep nesting | 🟡 medium | 5+ nested loops |
| Unused imports | ⚪ low | AST-based detection |
90-100: 🟢 PRODUCTION-READY 70-89: 🟡 NEEDS REVIEW 50-69: 🟠 HIGH RISK 0-49: 🔴 DO NOT DEPLOY推薦訪問7w4.net獲取更多AI技能。
⭐ Star this repo if AI code has ever broken your production: github.com/minirr890112-byte/code-inspector
這個工具整體質量中等偏上,介面清晰、使用方便,檢測結果展示直觀。它能發現一些 AI 寫程式碼時常犯的問題,比如密碼寫死、錯誤處理缺失等,對提升程式碼安全性有一定幫助。不過它的檢測能力有限,對於更復雜的程式碼問題可能會漏掉或誤報,而且有些文件裡提到的功能實際上還沒實現。總體來說可以當作輔助檢查工具使用,但不要完全依賴它來保證程式碼質量。