Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/shen-shanshan/vllm-dev-skills/vllm-pr-desc-generator)<a href="https://agentmods.dev/skills/shen-shanshan/vllm-dev-skills/vllm-pr-desc-generator"><img src="https://agentmods.dev/badge/skills/shen-shanshan/vllm-dev-skills/vllm-pr-desc-generator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/shen-shanshan/vllm-dev-skills/vllm-pr-desc-generator"><img src="https://agentmods.dev/badge/skills/shen-shanshan/vllm-dev-skills/vllm-pr-desc-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00118 | $0.01194 |
| Opus 5 | $0.00059 | $0.00597 |
| Sonnet 5 | $0.00024 | $0.00239 |
| Haiku 4.5 | $0.00012 | $0.00119 |
Grade A, and why
vllm-pr-desc-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- Parse PR number — extract from URL or direct number
- Fetch PR data — run
scripts/fetch_pr_data.py - Read the JSON — load into context
- Analyze code changes — understand the diff, purpose, and impact
- Generate PR description — write vLLM-format description
- Save — write to
./outputs/pr-<NUMBER>-desc.md - Confirm — tell the user the output path
Step 1: Parse PR Number
Extract <PR_NUMBER> from user input. Accepted formats:
https://github.com/vllm-project/vllm/pull/12345→12345vllm PR 12345orPR #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 <PR_NUMBER> \
--output /tmp/vllm_pr_<PR_NUMBER>.json
Optional flags:
--token <token>— GitHub PAT (not needed ifghCLI is authenticated)--max-diff-chars <N>— limit diff size (default 80 000)
Step 3: Analyze Code Changes
Read /tmp/vllm_pr_<PR_NUMBER>.json. Focus on:
diffandfiles: Understand what code changed, which modules are affectedpr.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 issuesissue_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
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 111 lines · 118 tokens per session scan A dc55c919fcb2
vllm-pr-desc-generator is a skill published in the GitHub repository shen-shanshan/vllm-dev-skills (17 stars, last pushed 3d ago), licensed Apache-2.0. It adds 118 tokens to every session and 1,194 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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