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vibe-code-auditor

vibe-code-auditor

Audit AI-generated or rapidly-prototyped code for structural flaws, hallucinated imports, fragility, and production risks before committing or handing off. Use when code was generated with AI assistance, evolved without deliberate architecture, or a prototype needs productionizing.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: vibe-code-auditor description: Audit AI-generated or rapidly-prototyped code for structural flaws, hallucinated imports, fragility, and production risks before committing or handing off. Use when code was generated with AI assistance, evolved without deliberate architecture, or a prototype needs productionizing. allowed-tools: Read, Grep, Glob, Bash metadata: triggers: vibe code, AI-generated code, prototype review, production ready, hallucinated imports, code audit, rapid iteration, is this production ready, audit this code related-skills: code-reviewer, security-reviewer, architect-review, systematic-debugging, verification-before-completion domain: quality role: specialist scope: review output-format: report last-reviewed: "2026-03-15"

Iron Law

NO FINDINGS WITHOUT CODE EVIDENCE — every issue must cite file and line number (or structural location for snippets). Do not speculate about code you have not read.

Vibe Code Auditor

Overview

AI-generated and rapidly-prototyped code that "works" may contain hallucinated imports, missing library versions, architectural fragility, and production risks that are invisible during casual review.

This skill is the pre-commit gate for AI-assisted code — it runs before code-reviewer and security-reviewer to catch AI-specific artifacts first.

Core distinction from code-reviewer: code-reviewer assumes production-intent code. This skill assumes prototype/AI-generated code and specifically checks for hallucinated APIs and prototype-to-production gaps.

When to Use

  • Code was generated or heavily assisted by AI tools
  • The system evolved without a deliberate architecture ("vibe coded")
  • A prototype needs to be productionized
  • Code works but feels fragile or inconsistent
  • You suspect hallucinated imports or API mismatches
  • Preparing a project for long-term maintenance or team handoff

Pre-Audit Checklist

Before beginning, confirm:

  • Input received: Source code or files are present
  • Scope defined: snippet / single file / multi-file system
  • Context noted: State assumptions if context is missing (e.g., "Assuming NestJS web API")

Quick Scan (first 60 seconds):

  • Count files and lines of code
  • Identify language(s) and framework(s)
  • Spot obvious red flags: hardcoded secrets, bare excepts, TODOs, commented-out code
  • Note entry points and data flow direction

Pattern Recognition Shortcuts:

PatternLikely IssueQuick Check
eval(), exec(), os.system()Security criticalSearch for these strings
except: or except Exception:Silent failuresGrep for bare excepts
password, secret, key, token in codeHardcoded credentialsSearch + check if literal string
if DEBUG, debug=TrueInsecure defaultsCheck config blocks
Functions >50 linesMaintainability riskCount lines per function
Nested if >3 levelsComplexity hotspotVisual scan
No tests in repoQuality gapLook for test_ / *.spec.ts files
Direct SQL string concatSQL injectionSearch for f"SELECT or + "SELECT
HTTP client calls without timeoutProduction riskCheck fetch/axios/requests calls
while True without breakUnbounded loopSearch for infinite loops

Audit Dimensions

Evaluate across all 7 dimensions. For each finding: dimension, title, location (file:line), severity, explanation, recommendation.

1. Architecture & Design

  • Separation of concerns violations (business logic inside route handlers)
  • God objects or monolithic modules
  • Tight coupling with no abstraction boundary
  • Missing or blurred system boundaries (DB queries scattered across layers)
  • Circular dependencies or import cycles

2. Consistency & Maintainability

  • Naming inconsistencies (get_user vs fetchUser vs retrieveUserData)
  • Mixed paradigms without justification
  • Copy-paste logic (3+ repetitions = extract)
  • Magic numbers or strings without constants

3. Robustness & Error Handling

  • Missing input validation on entry points
  • Bare except or catch-all handlers that swallow failures silently
  • Unhandled edge cases (empty collections, null/None, zero values)
  • No retry logic for transient failures
  • Missing timeouts on blocking operations

4. Production Risks

  • Hardcoded configuration values (URLs, credentials, timeouts)
  • Missing structured logging or observability hooks
  • N+1 query patterns or unbounded loops
  • Blocking I/O in async contexts
  • No health checks or readiness endpoints

5. Security & Safety

  • Unsanitized user input to databases, shells, or eval
  • Credentials, API keys, or tokens in source code
  • Insecure defaults (DEBUG=True, permissive CORS)
  • SQL injection (string concatenation in queries)
  • Missing authentication/authorization checks

6. Dead or Hallucinated Code (AI-specific — unique to this skill)

  • Imports that do not exist in the declared dependencies
  • References to APIs, methods, or fields that do not exist in the library version used
  • Type annotations that contradict actual usage
  • Comments describing behavior inconsistent with the code
  • Unreachable code blocks (after return, raise, or break in all paths)
  • Feature flags or conditionals that are always true/false

7. Technical Debt Hotspots

  • Deep nesting (>3-4 levels)
  • Boolean flag parameters controlling function behavior
  • Functions with 5+ parameters without a config object
  • Missing type hints for complex functions
  • No documentation for public APIs

Calibration by Code Size

Input sizeFocus
Snippet (<100 lines)Security, robustness, obvious bugs only
Single file (100-500 lines)Add architecture and maintainability
Multi-file system (500+ lines)Full audit across all 7 dimensions

Output Format

Produce the audit report in this exact structure. If a section has no findings, write "None identified."

Audit Report

Input: [file name(s) or "code snippet"] Assumptions: [list any assumptions about context or environment] Quick Stats: [X files, Y lines of code, Z language/framework]

Executive Summary

In 3-5 bullets:

- [CRITICAL/HIGH] Most severe issue
- [CRITICAL/HIGH] Second most severe issue
- [MEDIUM] Notable pattern
- Overall: Deployable as-is / Needs fixes / Requires major rework

Critical Issues (Must Fix Before Production)

For each issue:

[CRITICAL] Short descriptive title
Location: filename.ts, line 42
Dimension: Architecture / Security / Robustness / etc.
Problem: What is wrong and why it is dangerous.
Fix: Minimum change required.
Code Fix (if applicable):
  // Before: ...
  // After: ...

High-Risk Issues

Same format as Critical, tag [HIGH].

Maintainability Problems

Same format, tag [MEDIUM] or [LOW].

Production Readiness Score

Score: XX / 100

Scoring algorithm:

Start at 100
CRITICAL issue: -15 (security CRITICAL: -20)
HIGH issue: -8
MEDIUM issue: -3
Pervasive pattern (3+ similar issues): -5 additional
Floor: 0, Ceiling: 100
RangeMeaning
0-30Not deployable
31-50High risk — significant rework required
51-70Low-stakes / internal only with close monitoring
71-85Production-viable with targeted fixes
86-100Production-ready

Refactoring Priorities

Top 3-5 changes in impact order:

1. [P1 - Blocker] Fix title — addresses [CRITICAL #1] — effort: S/M/L — prevents [specific failure]
2. [P2 - Blocker] Fix title — addresses [CRITICAL #2] — effort: S/M/L
3. [P3 - High] Fix title — addresses [HIGH #1] — effort: S/M/L

Effort: S = <1 day, M = 1-3 days, L = >3 days

Behavior Rules

  • Ground every finding in actual code. Do not speculate.
  • Report file:line for every finding. For snippets, describe structurally (e.g., "inside processPayment()").
  • Do not flag style preferences unless they cause ambiguity or bugs.
  • Flag unconfirmed security issues as "unconfirmed — verify" rather than omitting or overstating.

Post-Audit Next Steps

Finding TypeNext Skill
Deep security vulnerabilities foundsecurity-reviewer — full OWASP deep-dive
Architectural anti-patterns foundarchitect-review — distributed systems assessment
Tests missing across codebasetest-driven-development — Red-Green-Refactor cycle
Duplicate logic patterns founddedup-code-agent — systematic deduplication
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