Borrowing it
Nothing to install: this file belongs to NomaDamas/AutoRAG-Research. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/NomaDamas/AutoRAG-Research/main/.claude/skills/refactor/SKILL.mdgit clone --depth 1 https://github.com/NomaDamas/AutoRAG-ResearchWrote 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/nomadamas/autorag-research/refactor)<a href="https://agentmods.dev/skills/nomadamas/autorag-research/refactor"><img src="https://agentmods.dev/badge/skills/nomadamas/autorag-research/refactor/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/nomadamas/autorag-research/refactor"><img src="https://agentmods.dev/badge/skills/nomadamas/autorag-research/refactor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00067 | $0.04318 |
| Opus 5.5 | $0.00027 | $0.01727 |
| Sonnet 5.5 | $0.00013 | $0.00864 |
| Haiku 4.5 | $0.00007 | $0.00432 |
Grade A, and why
refactor 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 — 521 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/refactor -- 3-Agent PR Code Review Debate
You orchestrate a PR code review debate with 3 reviewer agents (Red/White/Green). Follow these 10 steps exactly.
Step 1: Verify PR Exists
Run:
gh pr view --json number,url,title,body,headRefName,baseRefName
If the command fails, exit immediately:
No PR found on the current branch. Create a PR first.
Extract and remember these values:
PR_NUMBER-- the PR numberPR_URL-- the PR URLPR_TITLE-- the PR titleHEAD_REF-- head branch nameBASE_REF-- base branch name
Step 2: Gather PR Diff and Context
Run these commands (in parallel where possible):
gh pr diff
gh pr diff --stat
git rev-parse HEAD
git remote get-url origin
Store results as:
FULL_DIFF-- the full diff outputDIFF_STAT-- the diff stat summaryHEAD_SHA-- current HEAD commit SHAOWNER_REPO-- parse the remote URL to extractOWNER/REPO(handle both HTTPS and SSH formats)
If FULL_DIFF is empty, exit immediately:
Nothing to review. The PR diff is empty.
Step 3: Create Team and Spawn 3 Reviewers (Parallel)
3a. Create the team
TeamCreate(team_name="pr-review-{PR_NUMBER}")
3b. Create 3 tracking tasks
Create one task per reviewer:
- "Red Reviewer: Devil's Advocate analysis"
- "White Reviewer: Neutral Judge analysis"
- "Green Reviewer: Approval Advocate analysis"
3c. Spawn 3 reviewer agents in a SINGLE message (parallel)
Use the Task tool three times in the same message. Each agent:
subagent_type:"general-purpose"team_name:"pr-review-{PR_NUMBER}"mode:"bypassPermissions"
Build each agent's prompt by filling in the appropriate role template below with FULL_DIFF, DIFF_STAT, PR_TITLE, and file list from diff stat.
Agent names and roles:
| Name | Role |
|---|---|
red-reviewer |
Devil's Advocate -- always opposes, attacks security/race conditions/hidden assumptions |
white-reviewer |
Neutral Judge -- risk = probability x impact, pragmatic tradeoffs |
green-reviewer |
Approval Advocate -- champions strengths, only flags genuinely critical issues |
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 · 521 lines · 67 tokens per session scan A abb3fa698d63
refactor is a skill published in the GitHub repository NomaDamas/AutoRAG-Research (151 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 67 tokens to every session and 4,318 once invoked, about $0.0003 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 2026-08-30.
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