Git Pr Review

Objective

Create a clean, objective pull request description by analyzing commit history between base and current branch.

When to Use

Use this skill when you need to generate a structured pull request description based on commit history, especially for maintaining consistency and reducing manual effort.

Strategy (Token Efficient)

1. DO NOT scan full diffs initially
2. START with commit messages only
3. ONLY inspect diffs if intent is unclear

Steps

1. Identify range

Default:

• base: main
• target: HEAD

Command: git log --no-merges --pretty=format:"%h|%s" main..HEAD

2. Pre-process commits

For each commit:

• Extract type if exists:
  • feat, fix, refactor, chore, docs, test
• If missing:
  • infer from message keywords:
    • "add", "create" → feat
    • "fix", "bug" → fix
    • "refactor", "improve" → refactor

3. Remove noise (CRITICAL)

IGNORE commits that match:

• merge
• typo / docs only
• lint / format
• console.log removal
• comments only
• minor rename

4. Group by domain (VERY IMPORTANT)

Cluster commits by feature/module:

Heuristic:

• Same keyword → same group
• Same folder/file pattern → same group

Example:

• auth.service + auth.controller → "authentication"
• payment + checkout → "payment flow"

5. Conditional diff inspection (ONLY if needed)

ONLY run: git show

IF:

• commit message is vague ("update stuff")
• or grouping is unclear

Goal:

• extract intent, NOT code details

6. Build PR output

Title

Format: type(scope): short summary

Rules:

• max 72 chars
• prefer dominant group

Description Format (STRICT)

Summary

1–2 lines explaining the purpose

Changes

Grouped bullet points:

• :

Technical Notes (optional)

Only if relevant:

• migrations
• env vars
• breaking changes

Impact

• user impact or system impact
• risks if any

Output Rules

• Max ~120–180 words total
• No repetition of commit messages
• No low-level code explanation
• No fluff
• No emojis
• No generic phrases ("this PR does...")

Limitations

• Relies on commit message quality; vague commits may reduce accuracy
• Does not deeply analyze code changes unless necessary
• Grouping heuristics may not perfectly reflect complex feature boundaries
• Assumes a relatively clean commit history without excessive noise

Example Output

Title: feat(auth): implement JWT authentication and session handling

Summary

Adds authentication flow and resolves session persistence issues.

Changes

• authentication: added JWT middleware and login flow
• session: fixed expiration handling
• user: refactored user service logic

Impact

Improves security and fixes inconsistent login behavior.