🎁 Get the FREE AI Skills Starter Guide — Subscribe →
BytesAgainBytesAgain
BytesAgain › Skills › vibe-check
🦀 ClawHub

vibe-check

by @tkuehnl

Audit code for "vibe coding sins" — patterns that indicate AI-generated code was accepted without proper review. Produces a scored report card with fix sugge...

Versionv0.2.1
Downloads1,716
#legal
TERMINAL
clawhub install vibe-check

📖 About This Skill

name: vibe-check version: 0.1.1 description: Audit code for "vibe coding sins" — patterns that indicate AI-generated code was accepted without proper review. Produces a scored report card with fix suggestions. author: Anvil AI tags: [code-quality, code-review, ai-audit, vibe-coding, linting, security, python, typescript, javascript, discord, discord-v2]

🎭 Vibe Check

Audit code for "vibe coding" — AI-generated code accepted without proper human review. Get a scored report card with specific findings and fix suggestions.

Trigger

Activate when the user mentions any of:

  • "vibe check"
  • "vibe-check"
  • "audit code"
  • "code quality"
  • "vibe score"
  • "check my code"
  • "review this code for vibe coding"
  • "code review"
  • "vibe audit"

    • Instructions

    1. Determine the Target

    Ask the user what code to analyze. Accepted inputs:

  • Single file: app.py, src/utils.ts
  • Directory: src/, ., my-project/
  • Git diff: last N commits, staged changes, or branch comparison

    • 2. Run the Analysis

    # Single file or directory
bash "$SKILL_DIR/scripts/vibe-check.sh" TARGET
    With fix suggestions
    
bash "$SKILL_DIR/scripts/vibe-check.sh" --fix TARGET
    Git diff (last 3 commits)
    
bash "$SKILL_DIR/scripts/vibe-check.sh" --diff HEAD~3
    Staged changes with fixes
    
bash "$SKILL_DIR/scripts/vibe-check.sh" --staged --fix
    Save to file
    
bash "$SKILL_DIR/scripts/vibe-check.sh" --fix --output report.md TARGET

    3. Present the Report

    The output is a Markdown report. Present it directly — it's designed to be screenshot-worthy.

    Discord v2 Delivery Mode (OpenClaw v2026.2.14+)

    When the conversation is happening in a Discord channel:

  • Send a compact summary first (grade, score, file count, top 3 findings), then ask if the user wants the full report.
  • Keep the first message under ~1200 characters and avoid wide Markdown tables in the first response.
  • If Discord components are available, include quick actions:
    • - Show Top Findings - Show Fix Suggestions - Run Diff Mode
  • If components are not available, provide the same follow-ups as a numbered list.
  • Prefer short follow-up chunks (<=15 lines per message) when sending the full report.

    • Quick Reference

    | Command | Description | |---------|-------------| | vibe-check FILE | Analyze a single file | | vibe-check DIR | Scan directory recursively | | vibe-check --diff | Check last commit's changes | | vibe-check --diff HEAD~5 | Check last 5 commits | | vibe-check --staged | Check staged changes | | vibe-check --fix DIR | Include fix suggestions | | vibe-check --output report.md DIR | Save report to file |

    Sin Categories (what it checks)

    | Category | Weight | What It Catches | |----------|:------:|-----------------| | Error Handling | 20% | Missing try/catch, bare exceptions, no edge cases | | Input Validation | 15% | No type checks, no bounds checks, trusting all input | | Duplication | 15% | Copy-pasted logic, DRY violations | | Dead Code | 10% | Unused imports, commented-out blocks, unreachable code | | Magic Values | 10% | Hardcoded strings/numbers/URLs without constants | | Test Coverage | 10% | No test files, no test patterns, no assertions | | Naming Quality | 10% | Vague names (data, result, temp, x), misleading names | | Security | 10% | eval(), exec(), hardcoded secrets, SQL injection |

    Scoring

  • A (90-100): Pristine code, minimal issues
  • B (80-89): Clean code with minor issues
  • C (70-79): Decent but lazy patterns crept in
  • D (60-69): Needs human attention
  • F (<60): Heavy vibe coding detected

    • Notes for the Agent

  • The report is the star. Present it in full — it's designed to look great.
  • After presenting, offer to run --fix mode if they didn't already.
  • Suggest the README badge: !Vibe Score
  • For large codebases, suggest focusing on specific directories or using --diff mode.
  • If no LLM API key is set, the tool falls back to heuristic analysis (less accurate but still useful).
  • Supported languages (v1): Python, TypeScript, JavaScript only.

    • References

  • scripts/vibe-check.sh — Main entry point
  • scripts/analyze.sh — LLM code analysis engine (with heuristic fallback)
  • scripts/git-diff.sh — Git diff file extractor
  • scripts/report.sh — Markdown report generator
  • scripts/common.sh — Shared utilities and constants

    • Examples

    Example 1: Audit a Directory

    User: "Vibe check my src directory"

    Agent runs: 

    bash "$SKILL_DIR/scripts/vibe-check.sh" src/

    Output: Full scorecard with per-file breakdown, category scores, and top findings.

    Example 2: Check with Fixes

    User: "Review this code for vibe coding and suggest fixes"

    Agent runs: 

    bash "$SKILL_DIR/scripts/vibe-check.sh" --fix src/

    Output: Scorecard + unified diff patches for each finding.

    Example 3: Git Diff Mode

    User: "Check the code quality of my last 3 commits"

    Agent runs: 

    bash "$SKILL_DIR/scripts/vibe-check.sh" --diff HEAD~3

    Output: Scorecard focused only on recently changed files.

    💡 Examples

    Example 1: Audit a Directory

    User: "Vibe check my src directory"

    Agent runs: 

    bash "$SKILL_DIR/scripts/vibe-check.sh" src/

    Output: Full scorecard with per-file breakdown, category scores, and top findings.

    Example 2: Check with Fixes

    User: "Review this code for vibe coding and suggest fixes"

    Agent runs: 

    bash "$SKILL_DIR/scripts/vibe-check.sh" --fix src/

    Output: Scorecard + unified diff patches for each finding.

    Example 3: Git Diff Mode

    User: "Check the code quality of my last 3 commits"

    Agent runs: 

    bash "$SKILL_DIR/scripts/vibe-check.sh" --diff HEAD~3

    Output: Scorecard focused only on recently changed files.