smithery.ai

review:peer

Review a pull request when requested by a peer. Use when reviewing PRs, providing code review feedback, or analyzing proposed changes. Supports GitHub and GitLab. Pass --triage to summarize a PR and estimate its review effort without reviewing it.

Installation

$ npx skills add https://smithery.ai

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Skill metadata

Parsed from SKILL.md frontmatter.

Allowed toolsBash(gh:*), Bash(glab:*), Bash(git log:*), Bash(git diff:*), Bash(git show:*), Bash(git branch:*), Bash(git fetch:*), Bash(git checkout:*), Bash(git remote:*), Bash(git rev-parse:*), Bash(git cat-file:*), Bash(git status:*), Bash(jq:*), mcp__github, WebFetch, Skill(review:code), Bash(bun ${CLAUDE_SKILL_DIR}/scripts/:*)

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 5,363 B
  • docs SUMMARY.md 174 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Peer Review

Assist me in reviewing this PR: $ARGUMENTS

Context

Your own login as the reviewer (see [tone.md](tone.md) for how to address each party). Whichever platform applies resolves. The other reads unavailable.

  • GitHub user: !gh api graphql -f query='{viewer{login}}' --jq .data.viewer.login 2>/dev/null | grep . || echo "unavailable"
  • GitLab user: !glab api user 2>/dev/null | jq -r .username 2>/dev/null | grep . || echo "unavailable"

Arguments

  • --triage: assess the PR for sequencing instead of reviewing it (see [Triage Mode](#triage-mode)). Default: off, which runs the full review workflow below.

Triage Mode

When --triage is set, stay read-only and assess the PR for sequencing. Gather just enough to judge scope: the PR body, the diff stat, and the files touched. Then report two things and stop.

  • What the PR changes, in one line.
  • The estimated review effort on the same scale step 4 uses for review:code (low, medium, high, xhigh), with one-line reasoning.

Guardrails

  • Must check with me before submitting. Show file comments and review comment.
  • Don't insist on commenting on every PR. Propose approving with no comment if everything looks good.
  • Do match my writing style. You're commenting as me, not a generic AI assistant.
  • Do ask me about ambiguous code rather than guessing.
  • Don't run interpreter one-liners for library introspection. Read the source or fetch the docs.

Workflow

  1. Research - Gather context and identify participants (see [research.md](research.md))
  2. Context - Determine review context using repository visibility. Private repositories use [corporate](references/corporate.md) defaults. Public repositories use [open-source](references/open-source.md) defaults. Check visibility via the platform API (gh api repos/OWNER/REPO --jq .visibility or glab api projects/ENCODED_PATH | jq .visibility). If ambiguous, ask me.
  3. Review - Examine changed files and existing comments
  4. Delegate - Run review:code for code-quality analysis. review:code reads the local diff, so run gh pr checkout first if not already on the PR branch. Summarize the diff (rough line count, files touched, sensitive areas) and signals from the PR body, propose an effort level with one-line reasoning, and confirm via AskUserQuestion before invoking. Skip the call for trivial PRs (docs-only, dep bumps). Effort heuristics:

- low: docs-only, dep bumps, config tweaks, trivial fixes (<50 lines) - medium: typical features or fixes, single module, ~50–500 lines - high: large refactors, multi-module, public API or schema changes, ~500–2000 lines - xhigh: security-sensitive (auth, payments, data access), breaking changes, migrations, or a change with extreme blast radius

  1. Think - Evaluate along two axes. Requirement fulfillment: does the change deliver what was asked (see [requirements.md](requirements.md))? Code quality: evaluate against priorities (see [priorities.md](priorities.md)) and smells (see [smells.md](smells.md)), incorporating review:code findings. Keep the axes separate so a clean diff does not mask a missed requirement.
  2. Map - Write the proposed comments to a JSON file (id, path, startline, endline, side, comment_type, content per comment), then map each to a platform position:

``bash bun ${CLAUDESKILLDIR}/scripts/mapping.ts map --platform <github|gitlab> \ --comments <path> --diff <path> --commit <head-sha> ``

GitLab also needs --base and --start from the MR diff_refs. The CLI runs the in-diff pre-check and returns { payloads, dropped }. An anchor outside a diff hunk lands in dropped (GitHub rejects it with 422 "Line could not be resolved"), so surface those to me and re-anchor rather than losing them. Skip this step when approving with no comments.

  1. Post - Show me the mapped set, then on my go post as one batch and choose Approve / Comment / Request Changes based on severity. GitHub: a pending review submitted as a batch. GitLab: draft notes published together.

See [tone.md](tone.md) for comment style guidelines.

Service Support

This skill assumes GitHub. For GitLab merge requests, load gitlab:merge-request for the submission workflow; use draft-note.ts submit to publish draft notes with an optional summary and review decision.

Comments post through the programmatic path (mcp__github / gh / glab). On follow-up, resolve addressed threads natively on the platform: review-threads.ts for GitHub, the resolve flow in gitlab:merge-request for GitLab.