Vllm Pr Desc Generator

vllm-pr-desc-generator

Generate a vLLM-style PR description from code changes and save to ./outputs/.

Take ./references/example-pr-desc.md as a style reference for the output.

Workflow

1. Parse PR number — extract from URL or direct number
2. Fetch PR data — run scripts/fetch_pr_data.py
3. Read the JSON — load into context
4. Analyze code changes — understand the diff, purpose, and impact
5. Generate PR description — write vLLM-format description
6. Save — write to ./outputs/pr--desc.md
7. Confirm — tell the user the output path

Step 1: Parse PR Number

Extract `` from user input. Accepted formats:

• https://github.com/vllm-project/vllm/pull/12345 → 12345
• vllm PR 12345 or PR #12345 → 12345
• Plain number 12345 → 12345

For PRs from other repos (e.g., vllm-project/vllm-ascend), adjust the --repo flag in the fetch script accordingly. Default repo is vllm-project/vllm.

Step 2: Fetch PR Data

python3 /Users/shanshan-shen/.claude/skills/vllm-pr-desc-generator/scripts/fetch_pr_data.py  \
    --output /tmp/vllm_pr_.json

Optional flags:

• --token — GitHub PAT (not needed if gh CLI is authenticated)
• --max-diff-chars — limit diff size (default 80 000)

Step 3: Analyze Code Changes

Read /tmp/vllm_pr_.json. Focus on:

• diff and files: Understand what code changed, which modules are affected
• pr.title: Infer the PR category prefix (e.g., [Feature], [BugFix], [Misc], [CI/Build], [Doc])
• pr.body: Check if the author already provided context or linked issues
• issue_comments / review_comments: Extract reviewer feedback, design decisions, test suggestions

Categorize the change type:

• Feature: New functionality, new model support, new API
• BugFix: Correctness fix, crash fix, regression fix
• Refactor: Code reorganization without behavior change
• Performance: Optimization, memory reduction, throughput improvement
• Docs: Documentation only
• CI/Build: Build system, CI pipeline, dependency changes

Step 4: Generate PR Description

Write the description following the vLLM PR template. The output MUST include these sections:

## Purpose

### Key Changes

## Test Plan

## Test Result

## (Optional) Documentation Update

Writing Guidelines

• Purpose section: Lead with the problem/motivation, then describe the solution approach. Be specific — "Fix OOM when loading large MoE models" is better than "Fix a bug".
• Key Changes: Group by module. Use bold for file/class names. Each bullet should be self-contained and informative.
• Test Plan: Provide concrete, copy-pasteable commands. Include model names, flags, and expected behavior.
• Test Result: Prefer tables for quantitative results. For bug fixes, describe the before/after behavior.
• Language: Match the PR title language. If title is in English, write in English. If Chinese, write in Chinese. Default to English.
• Tone: Technical, concise, factual. No filler words.

Step 5: Save Output

Save to /Users/shanshan-shen/.claude/skills/vllm-pr-desc-generator/outputs/pr--desc.md.

Tell the user the file path and briefly summarize what the PR does.

Authentication

• gh CLI available (recommended): script auto-detects, no token needed
• No gh CLI: pass --token with repo scope
• No auth: unauthenticated REST API used; rate limit applies (60 req/hr)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: shen-shanshan
• Source: shen-shanshan/vllm-dev-skills
• License: Apache-2.0
• Homepage: https://zhuanlan.zhihu.com/p/2031696581678866733

Install and usage instructions live in the source repository linked above.