MCP.Market

pr-review skill

by Significant-Gravitas·Significant-Gravitas/AutoGPT·188k stars

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.

A100/100content scan

Is the pr-review skill safe?

Clean: nothing in its files matched our rules. We read 1 file in the folder on 2026-11-04.

No findings.

Install the pr-review skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description. 

git clone --depth 1 https://github.com/Significant-Gravitas/AutoGPT.git /tmp/AutoGPT
mkdir -p ~/.claude/skills
cp -r /tmp/AutoGPT/.claude/skills/pr-review ~/.claude/skills/pr-review
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

PR 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 and root AGENTS.md, including its "User-facing copy" section (text a person reads says workflow, never agent or graph).

Design system (frontend): hold changed code under autogptplatform/frontend/src//.{tsx,ts,css} to the rules in docs/engineering/design-system.md. pnpm lint fails new violations (raw palette classes, hex colours, dark: classes, legacy imports, restyled primitives, reason-less suppressions) and any file whose count goes over its entry in scripts/eslint-rules/design-system-baseline.json; grandfathered counts at or below the baseline pass. Review what lint cannot see: a raised baseline count for a file that was not moved, renamed or split, a colour swapped to a role with a different value (pixels change), global CSS for DOM we render as JSX, a repeated class string that should be a variant, and missing before/after screenshots for changes to src/components/, globals.css or tailwind*.ts.

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:

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>

More skills from Significant-Gravitas/AutoGPT

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  • Aperf-compareShared measurement recipe for AutoGPT performance work. Compares a baseline and a candidate in Sentry (two releases, two environments such as preview pr-<n> deploys, or two time windows) per transaction: count, p50/p95/p99, failure rate, and a trace-clustered bootstrap verdict of faster / slower / no detectable change / not enough data, with exit codes agents can branch on. Works for span duration, web vitals (measurements.lcp) or any numeric span field. TRIGGER when an agent needs to show a change made the backend or frontend faster or slower, compare a preview against a control or dev, check a release after merge on dev or prod, or check for regressions.
  • Apr-addressAddress PR review comments and loop until CI green and all comments resolved. TRIGGER when user asks to address comments, fix PR feedback, respond to reviewers, or babysit/monitor a PR.
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