review-pr

review-pr is a skill for Claude Code from shen-shanshan/vllm-dev-skills. It costs 59 tokens per session (12,570 once invoked), scanned A, original, Apache-2.0.

A specialised review workflow for pull requests in ATOM, a software layer that provides AMD GPU kernel optimisations for AI model inference. It checks changes against ATOM's GPU, model, and integration requirements.

In plain words
What is it for?
Use it to fetch and review an ATOM pull request, inspect linked issues and prior comments, and assess kernel, model-coverage, dependency, and generated-code changes.
Why use it?
It helps catch changes that could break inference paths, model support, dispatch logic, performance assumptions, or dependencies on related projects.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: positional $N argument; mentions Claude Code.

Good fit Use it to fetch and review an ATOM pull request, inspect linked issues and prior comments, and assess kernel, model-coverage, dependency, and generated-code changes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/shen-shanshan/vllm-dev-skills/atom-review-pr
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add shen-shanshan/vllm-dev-skills --skill atom-review-pr
Clone the repo
git clone --depth 1 https://github.com/shen-shanshan/vllm-dev-skills

Made for: Claude Code.

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.

agentmods badge for review-pr

README.md
[![agentmods](https://agentmods.dev/badge/skills/shen-shanshan/vllm-dev-skills/atom-review-pr/github.svg)](https://agentmods.dev/skills/shen-shanshan/vllm-dev-skills/atom-review-pr)
Your own site
<a href="https://agentmods.dev/skills/shen-shanshan/vllm-dev-skills/atom-review-pr"><img src="https://agentmods.dev/badge/skills/shen-shanshan/vllm-dev-skills/atom-review-pr/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.

agentmods 80×15 button for review-pr

Your own site · 80×15
<a href="https://agentmods.dev/skills/shen-shanshan/vllm-dev-skills/atom-review-pr"><img src="https://agentmods.dev/badge/skills/shen-shanshan/vllm-dev-skills/atom-review-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 12,570 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00059 $0.12570
Opus 5 $0.00030 $0.06285
Sonnet 5 $0.00012 $0.02514
Haiku 4.5 $0.00006 $0.01257

Measured 7d ago against content hash 7b7ac06367d0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

review-pr 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 7d 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.

skills/vllm-rocm-pr-review/references/upstream/atom-review-pr-skill.md · 583 lines

How it starts

The opening of the file, as written. The whole thing — 583 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ATOM PR Review

ATOM is a ROCm/AMD GPU kernel optimization layer (MI300X/MI355X) that:

  • Consumes aiter ops (attention, MoE, GEMM, norm, quant)
  • Integrates with vLLM and SGLang as a plugin/backend
  • Provides custom MLA, sparse attention, TBO, and quantization fusion

A change here can break inference for all models using the affected kernel path.


Step 1 — Fetch

PR=$1
REPO="ROCm/ATOM"

gh pr view $PR --repo $REPO --json title,body,number,labels,files,author,reviews,comments > /tmp/pr_meta.json
gh pr diff $PR --repo $REPO > /tmp/pr.diff

# Linked issue
ISSUE=$(cat /tmp/pr_meta.json | python3 -c "
import json,re,sys
body = json.load(sys.stdin).get('body','') or ''
m = re.search(r'(?:fix|close|resolve)[s]?[: ]*#(\d+)', body, re.I)
print(m.group(1) if m else '')
")
[ -n "$ISSUE" ] && gh issue view $ISSUE --repo $REPO --json title,body > /tmp/pr_issue.json

# Prior reviewer comments (top-level)
cat /tmp/pr_meta.json | python3 -c "
import json,sys
d = json.load(sys.stdin)
for r in d.get('reviews',[]):
    b = (r.get('body','') or '').strip()
    if b: print(f'[REVIEW {r[\"author\"][\"login\"]}] {b[:200]}')
for c in d.get('comments',[]):
    b = (c.get('body','') or '').strip()
    if b: print(f'[COMMENT {c[\"author\"][\"login\"]}] {b[:200]}')
"

# Inline review comments (line-level — often more specific than top-level)
gh api "repos/$REPO/pulls/$PR/comments" | python3 -c "
import json,sys
comments = json.load(sys.stdin)
for c in comments:
    author = c.get('user',{}).get('login','')
    body = (c.get('body','') or '').strip()
    path = c.get('path','')
    line = c.get('line') or c.get('original_line','')
    if body and 'copilot' not in author.lower() and 'bot' not in author.lower():
        print(f'[INLINE {author}] {path}:{line}')
        print(f'  {body[:250]}')
" 2>/dev/null

Read the diff and PR body before proceeding.

Cross-file verification — before reporting any kernel/dispatch finding. The diff shows changed lines, not the whole story. Grep the entire symbol family (.cu + .cuh + .h, or the whole module), not just files in the diff — sync/fence/atomics or the "other half" of a scatter often live in a header, and dispatch/else-branch completeness must be read in the full function, not the hunk. A "no synchronization" or "missing branch" finding based only on the diff is how false positives happen.

Read the full file on GitHub · 583 lines

Changes

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.

  1. 7d ago First seen · 583 lines · 59 tokens per session scan A 7b7ac06367d0

Subscribe to this mod's changes

review-pr is a skill published in the GitHub repository shen-shanshan/vllm-dev-skills (17 stars, last pushed 2d ago), licensed Apache-2.0. It adds 59 tokens to every session and 12,570 once invoked, about $0.0003 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 2026-09-04.

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