self-critique

Self-Critique Skill

Implements the "confessions" pattern: after completing work, an independent model (Gemini) reviews it, so the author model's blind spots don't go unchallenged. The reviewer returns structured issues (category, severity, location, suggested fix) and an overall confidence score.

When to Use

• After completing a significant code change
• Before committing to version control
• When uncertain about an implementation decision
• As a periodic audit pass over recent work

Setup (one-time)

1. Get a Gemini API key from https://aistudio.google.com/apikey
2. Store it:

   mkdir -p ~/.config/ai-dev-tools
   echo "your-api-key-here" > ~/.config/ai-dev-tools/gemini_api_key
   chmod 600 ~/.config/ai-dev-tools/gemini_api_key
   

   Or set the GEMINI_API_KEY environment variable.
3. Optional: override the reviewer model with GEMINI_MODEL (pin exact model IDs — floating aliases can silently change behavior).

How to Use

Paths resolve against your ai-dev-tools checkout (see the AI_DEV_TOOLS_DIR convention in skills/README.md).

After completing a task, run the critique script with a description of what was done:

python3 "${AI_DEV_TOOLS_DIR:-.}/skills/self-critique/gemini_critique.py" \
  --task "Implemented user authentication" --files src/auth.py src/middleware.py

Or for a git-based review of recent changes:

python3 "${AI_DEV_TOOLS_DIR:-.}/skills/self-critique/gemini_critique.py" \
  --git-diff HEAD~1 --task "Recent changes"

Focus the critique on one dimension:

python3 "${AI_DEV_TOOLS_DIR:-.}/skills/self-critique/gemini_critique.py" \
  --task "Caching layer" --files cache.py --focus security

Add --json for machine-readable output. The script exits non-zero if any critical-severity issue is found, so it can gate CI or pre-commit flows.

Critique Categories

1. Correctness - Logic errors, edge cases, off-by-one errors
2. Security - Vulnerabilities, injection risks, data exposure
3. Performance - Inefficiencies, N+1 queries, memory leaks
4. Maintainability - Code clarity, naming, documentation gaps
5. Completeness - Missing tests, error handling, validation