Agent skill

code-review

Run `codex review` plus PAL `codereview` (via the `pal-mcporter` skill) against a git base ref, then merge both outputs into one prioritized, actionable review.

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/development/code-review-prateek-dotfiles

SKILL.md

Code Review

When to use

Use when you have a local git repo and a base ref to diff against (e.g. upstream/main, origin/master, or a commit SHA) and you want a single merged review from:

  • codex review
  • PAL codereview (run via pal-mcporter)

Inputs

  • path: repo root directory (prefer absolute)
  • compare_to: git ref to compare against (e.g. upstream/main)
  • extra (optional): focus areas (perf, security, tests, API, etc.)

Workflow

1) Ensure the base ref exists locally

  • cd <path>
  • If compare_to is a remote ref like upstream/main, ensure it’s present:
    • git fetch <remote> <branch>

2) Run Codex review + PAL codereview (parallel)

These two passes are independent once compare_to exists locally, so run them in parallel to reduce wall-clock time.

  • Codex review (capture as codex_review):
    • cd <path> && codex review --base "<compare_to>"
    • Note: the current codex review CLI does not accept a custom prompt when --base is used; run it without a prompt.
  • PAL review via MCPorter (capture as pal_review):
    • bash "<path-to-pal-mcporter-skill>/scripts/pal" -o markdown codereview --step "Review changes vs <compare_to>. <extra>" --step-number 1 --total-steps 1 --next-step-required false --findings "" --model auto --review-validation-type internal --review-type quick --severity-filter all --focus-on "<extra>"

Implementation note (when tool-parallelism is available): use multi_tool_use.parallel to run two functions.exec_command calls concurrently (one for codex review, one for pal ... codereview).

3) Merge feedback into one review

  • Deduplicate overlapping findings; reconcile disagreements (call them out explicitly).
  • Prioritize into:
    • Blockers (must fix): correctness, security, data loss, breaking API/ABI, missing tests, CI failures.
    • High-signal improvements: maintainability, performance, edge cases, observability.
    • Nits: style/consistency (only if low-noise).
  • End with a short verification checklist (tests to run, manual steps, rollout risk).

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