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.
npx skills add shen-shanshan/vllm-dev-skills --skill atom-review-prgit clone --depth 1 https://github.com/shen-shanshan/vllm-dev-skillsWrote 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/atom-review-pr)<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.
<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>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 | $0.00059 | $0.12570 |
| Opus 5.5 | $0.00024 | $0.05028 |
| Sonnet 5.5 | $0.00012 | $0.02514 |
| Haiku 4.5 | $0.00006 | $0.01257 |
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 2mo 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 — 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.
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.
- 2mo ago First seen · 583 lines · 59 tokens per session scan A 7b7ac06367d0
review-pr is a skill published in the GitHub repository shen-shanshan/vllm-dev-skills (31 stars, last pushed yesterday), licensed Apache-2.0. It adds 59 tokens to every session and 12,570 once invoked, about $0.0002 per session on Opus 5.5. 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.
review-pr compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| review-prshen-shanshan/vllm-dev-skills | Skill | 31 | yesterday | Apache-2.0 | A | 59 | Claude Code |
| github-review-prfeiskyer/claude-code-settings | Skill | 1.7k | yesterday | MIT | A | 90 | Claude Code |
| huggingface-llm-trainerwaybarrios/opencode-power-pack | Skill | 551 | 4d ago | MIT | A | 65 | Claude Code |
| runpodericrisco/rsc-harness | Skill | 503 | 2d ago | MIT | A | 114 | Claude Code, Codex |
| huggingface-vision-trainerwaybarrios/opencode-power-pack | Skill | 551 | 4d ago | MIT | A | 48 | Claude Code |
| plan-eng-reviewGCWing/BitFun | Skill | 2.1k | 2mo ago | MIT | A | 116 | Claude Code, Codex |
| rag-code-reviewlyonzin/knowledge-rag | Skill | 301 | yesterday | MIT | A | 83 | Claude Code, Codex |