leonvanzyl/agentic-coding-starter-kit/review-pr

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Review pull requests with complexity-adaptive depth — spawning deep-dive agents for medium and complex PRs. Use this skill when the user says "review this PR", "review PR #123", "check this pull request", "give me a code review", or wants feedback on a PR before merging. Also use when the user says "/review-pr" or pastes a GitHub PR URL. Requires the GitHub CLI (gh).

Install

npx vskill@latest install leonvanzyl/agentic-coding-starter-kit/review-pr

SKILL.md

Review Pull Request

Review pull requests with a depth that matches their complexity. Simple PRs get a direct review; complex PRs get parallel deep-dive agents analyzing security, performance, and architecture.

Arguments

The user should provide PR number(s) or URL(s). If none provided, ask for them.

Instructions

Step 1: Retrieve PR Details

Use the GitHub CLI to get the full picture:

bash
gh pr view {pr_number} --json title,body,files,additions,deletions,commits,author,reviews,comments
gh pr diff {pr_number}
Step 2: Assess Complexity

Score the PR based on:

  • Number of files changed
  • Lines added/removed
  • Number of commits
  • Whether changes touch core/architectural files

Simple (direct review, no agents):

  • 5 or fewer files AND 100 or fewer lines AND single author

Medium (1-2 deep-dive agents):

  • 6-15 files, OR 100-500 lines, OR 2 contributors

Complex (up to 3 deep-dive agents):

  • More than 15 files, OR more than 500 lines, OR more than 2 contributors, OR touches core architecture
Step 3: Analyze

For Simple PRs: review directly — read the diff, check for issues, provide feedback.

For Medium/Complex PRs: spawn deep-dive agents in parallel using the Agent tool with subagent_type: "deep-dive". Each agent gets a focused area:

  • Agent 1 — Code Quality: conventions, patterns, maintainability, test coverage
  • Agent 2 — Security: input validation, auth checks, injection risks, data exposure
  • Agent 3 — Architecture (Complex only): design patterns, separation of concerns, performance implications, backwards compatibility

Each agent receives the PR diff and description and returns a structured review.

Step 4: Vision Alignment

Read the project's README.md and CLAUDE.md to understand the application's purpose. Assess whether the PR aligns with the project's intended direction. Flag significant deviations — not as a blocker, but as a consideration for the reviewer.

Step 5: Safety Assessment

Provide an overall assessment:

  • Safe to merge: no significant issues found
  • Merge with caution: minor issues that should be noted but aren't blocking
  • Needs changes: issues that should be fixed before merging

Include a risk level (low/medium/high) with justification.

Step 6: Report

Structure the review as:

## PR Review: #{pr_number} — {title}
### Complexity: {Simple|Medium|Complex}
{Brief justification}
### Summary
{2-3 sentence overview of what the PR does}
### Issues Found
{Grouped by severity: high → medium → low}
- **{severity}**: {file:line} — {description}
### Improvements Suggested
{Optional improvements ranked by importance and implementation complexity}
### Vision Alignment
{Does this PR align with the project's direction?}
### Verdict: {Safe to merge | Merge with caution | Needs changes}
Risk level: {low|medium|high}
{Brief justification}

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

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