AutoRAG-Research: Command for Claude Code

.claude/commands/wrap-up.md

wrap-up is a command for Claude Code from NomaDamas/AutoRAG-Research. It costs 22 tokens per session (808 once invoked), scanned A, original, Apache-2.0.

A command that writes a summary comment for an existing GitHub pull request. A pull request is a proposed set of code changes submitted for review.

In plain words
What is it for?
Use it after creating a pull request to verify it exists, review its changes, and post a concise decision summary.
Why use it?
It gathers the pull request details, code differences, commit history, and conversation context so the final summary explains the problem, solution, and human decisions.

Command for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

This is NomaDamas/AutoRAG-Research's own configuration. It tells Claude Code how to work on AutoRAG-Research itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything AutoRAG-Research configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/NomaDamas/AutoRAG-Research/main/.claude/commands/wrap-up.md
Clone the repo
git clone --depth 1 https://github.com/NomaDamas/AutoRAG-Research

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 wrap-up

README.md
[![agentmods](https://agentmods.dev/badge/commands/nomadamas/autorag-research/wrap-up/github.svg)](https://agentmods.dev/commands/nomadamas/autorag-research/wrap-up)
Your own site
<a href="https://agentmods.dev/commands/nomadamas/autorag-research/wrap-up"><img src="https://agentmods.dev/badge/commands/nomadamas/autorag-research/wrap-up/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 wrap-up

Your own site · 80×15
<a href="https://agentmods.dev/commands/nomadamas/autorag-research/wrap-up"><img src="https://agentmods.dev/badge/commands/nomadamas/autorag-research/wrap-up.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 22 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 808 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 $0.00022 $0.00808
Opus 5 $0.00011 $0.00404
Sonnet 5 $0.00004 $0.00162
Haiku 4.5 $0.00002 $0.00081

Measured 9d ago against content hash c6ce712e49ae, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

wrap-up 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 9d 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.

.claude/commands/wrap-up.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/wrap-up -- PR Decision Summary

Analyze the current PR and post a comment summarizing:

  1. What problem this PR solves and how
  2. What key decisions the human made during the process

Step 1: Verify PR Exists

Run:

gh pr view --json number,url,title,body,headRefName,baseRefName

If fails, exit:

No PR found on the current branch. Create a PR first.

Extract PR_NUMBER, PR_URL, PR_TITLE, PR_BODY, BASE_REF.

Step 2: Gather Context

Run these in parallel:

gh pr diff --stat
git log {BASE_REF}..HEAD --pretty=format:"%h %s" --reverse
git log {BASE_REF}..HEAD --pretty=format:"%h%n%B---" --reverse
gh pr diff
git remote get-url origin

Store:

  • DIFF_STAT -- file change summary
  • COMMIT_LOG -- one-line commit history
  • COMMIT_DETAILS -- full commit messages
  • FULL_DIFF -- complete diff
  • OWNER_REPO -- parsed from remote URL (handle HTTPS and SSH)

Step 3: Analyze the Session Conversation

You have access to the current conversation history. Review it carefully.

3a. Problem and Solution

  • What triggered this work? (issue, bug, feature request, refactoring)
  • What was the core technical challenge?
  • What approach was taken?
  • What are the key conceptual changes? (not a file list)

3b. Human Decisions (Human-in-the-Loop)

Scan the conversation for moments where the human:

  • Chose between alternatives -- "Use A instead of B"
  • Rejected a suggestion -- "No, don't do that because..."
  • Added constraints -- "It must work with X", "Don't change Y"
  • Made design calls -- naming, architecture, scope
  • Scoped the work -- "Only do X for now", "Skip Y"
  • Corrected course -- "Actually, change direction to..."

Focus on decisions that shaped the outcome. Ignore trivial approvals.

Step 4: Write the Comment

Compose in English:

## PR Wrap-up

### What problem does this PR solve and how?

**Problem**: {1-3 sentences describing the problem/motivation}

**Solution**: {2-5 sentences describing the approach and key changes. Be specific about WHAT changed and WHY.}

### Key Decisions (Human-in-the-Loop)

{List only important decisions. Each explains WHAT was decided and WHY.}

- **{decision_topic}**: {what was decided} -- {why / what was the alternative}
- ...

---
*Generated by `/wrap-up`*

Read the full file on GitHub · 108 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. 9d ago First seen · 108 lines · 22 tokens per session scan A c6ce712e49ae

Subscribe to this mod's changes

wrap-up is a command published in the GitHub repository NomaDamas/AutoRAG-Research (148 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 22 tokens to every session and 808 once invoked, about $0.0001 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.