git-pr-review

Objective

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

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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.

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Strategy (Token Efficient)

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

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Steps

1. Identify range

Default:

• base: main
• target: HEAD

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

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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

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3. Remove noise (CRITICAL)

IGNORE commits that match:

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

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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"

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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

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6. Build PR output

Title

Format: type(scope): short summary

Rules:

• max 72 chars
• prefer dominant group

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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

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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...")

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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

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Example Output

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

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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.