PR Review

SkillSecurity

Review a PR for correctness, security, code quality, and testing issues. TRIGGER when user asks to review a PR, check PR quality, or give feedback on a PR.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the PR Review skill

What this skill tells your AI

The instructions your AI receives, as published by hidorakai002/ai-workspace-archive in ai_agent_frameworks/major_frameworks/AutoGPT/.claude/skills/pr-review/SKILL.md and read by ahel’s review.

Find the PR

gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT
gh pr view {N}

Read the PR description

Before reading code, understand the why, what, and how from the PR description:

gh pr view {N} --json body --jq '.body'

Every PR should have a Why / What / How structure. If any of these are missing, note it as feedback.

Read the diff

gh pr diff {N}

Fetch existing review comments

Before posting anything, fetch existing inline comments to avoid duplicates:

gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments --paginate
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews

What to check

Description quality: Does the PR description cover Why (motivation/problem), What (summary of changes), and How (approach/implementation details)? If any are missing, request them — you can't judge the approach without understanding the problem and intent.

Correctness: logic errors, off-by-one, missing edge cases, race conditions (TOCTOU in file access, credit charging), error handling gaps, async correctness (missing await, unclosed resources).

Security: input validation at boundaries, no injection (command, XSS, SQL), secrets not logged, file paths sanitized (os.path.basename() in error messages).

Code quality: apply rules from backend/frontend CLAUDE.md files.

Architecture: DRY, single responsibility, modular functions. Security() vs Depends() for FastAPI auth. data: for SSE events, : comment for heartbeats. transaction=True for Redis pipelines.

Testing: edge cases covered, colocated *_test.py (backend) / __tests__/ (frontend), mocks target where symbol is used not defined, AsyncMock for async.

Output format

Every comment must be prefixed with 🤖 and a criticality badge:

TierBadgeMeaning
Blocker🔴 **Blocker**Must fix before merge
Should Fix🟠 **Should Fix**Important improvement
Nice to Have🟡 **Nice to Have**Minor suggestion
Nit🔵 **Nit**Style / wording

Example: 🤖 🔴 **Blocker**: Missing error handling for X — suggest wrapping in try/except.

Post inline comments

For each finding, post an inline comment on the PR (do not just write a local report):

# Get the latest commit SHA for the PR
COMMIT_SHA=$(gh api repos/Significant-Gravitas/AutoGPT/pulls/{N} --jq '.head.sha')

# Post an inline comment on a specific file/line
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments \
  -f body="🤖 🔴 **Blocker**: <description>" \
  -f commit_id="$COMMIT_SHA" \
  -f path="<file path>" \
  -F line=<line number>

Signals

GitHub stars
35
Forks
13
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
pr-review-hidorakai002
Source
github.com/hidorakai002/ai-workspace-archive