paperclip: Skill for Claude Code

.agents/skills/pr-report/SKILL.md

pr-report is a skill for Claude Code, Codex from paperclipai/paperclip. It costs 39 tokens per session (1,111 once invoked), scanned A, original, MIT.

A detailed report for reviewing a pull request, branch, or large code contribution. It explains how the change works, compares its design where needed, and ends with a recommendation.

In plain words
What is it for?
Use it for deep pull-request reviews, design explanations, system comparisons, merge recommendations, or standalone HTML and Markdown reports.
Why use it?
A diff alone can hide how a change affects the wider system. This produces a structured explanation that separates technical design problems from questions about product scope.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is paperclipai/paperclip's own configuration. It tells Claude Code and Codex how to work on paperclip 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 paperclip configures →

About the project

Paperclip is a Node.js server and React application for coordinating AI agents as a business team, with goals, organizational roles, budgets, governance, and work tracking in one interface. It is used by people managing multiple agents or autonomous agent organizations across tools such as OpenClaw, Claude Code, Codex, and Cursor. The catalogue includes skills, agents, an MCP add-on, and an instruction for working with Paperclip.

paperclipai/paperclip · 80,206 stars · on GitHub · paperclip.ing

Reuse

Borrowing it

Nothing to install: this file belongs to paperclipai/paperclip. 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/paperclipai/paperclip/master/.agents/skills/pr-report/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/paperclipai/paperclip

Made for: Claude Code, Codex.

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 pr-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/paperclipai/paperclip/pr-report/github.svg)](https://agentmods.dev/skills/paperclipai/paperclip/pr-report)
Your own site
<a href="https://agentmods.dev/skills/paperclipai/paperclip/pr-report"><img src="https://agentmods.dev/badge/skills/paperclipai/paperclip/pr-report/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 pr-report

Your own site · 80×15
<a href="https://agentmods.dev/skills/paperclipai/paperclip/pr-report"><img src="https://agentmods.dev/badge/skills/paperclipai/paperclip/pr-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,111 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. Third-party audits
  • Snyk warn 7 Sept 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00039 $0.01111
Opus 5 $0.00019 $0.00556
Sonnet 5 $0.00008 $0.00222
Haiku 4.5 $0.00004 $0.00111

Measured 9d ago against content hash d4abb3074956, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

pr-report 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.

.agents/skills/pr-report/SKILL.md · 202 lines

How it starts

The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PR Report Skill

Produce a maintainer-grade review of a PR, branch, or large contribution.

Default posture:

  • understand the change before judging it
  • explain the system as built, not just the diff
  • separate architectural problems from product-scope objections
  • make a concrete recommendation, not a vague impression

When to Use

Use this skill when the user asks for things like:

  • "review this PR deeply"
  • "explain this contribution to me"
  • "make me a report or webpage for this PR"
  • "compare this design to similar systems"
  • "should I merge this?"

Outputs

Common outputs:

  • standalone HTML report in tmp/reports/...
  • Markdown report in report/ or another requested folder
  • short maintainer summary in chat

If the user asks for a webpage, build a polished standalone HTML artifact with clear sections and readable visual hierarchy.

Resources bundled with this skill:

  • references/style-guide.md for visual direction and report presentation rules
  • assets/html-report-starter.html for a reusable standalone HTML/CSS starter

Workflow

1. Acquire and frame the target

Work from local code when possible, not just the GitHub PR page.

Gather:

  • target branch or worktree
  • diff size and changed subsystems
  • relevant repo docs, specs, and invariants
  • contributor intent if it is documented in PR text or design docs

Start by answering: what is this change trying to become?

2. Build a mental model of the system

Do not stop at file-by-file notes. Reconstruct the design:

  • what new runtime or contract exists
  • which layers changed: db, shared types, server, UI, CLI, docs
  • lifecycle: install, startup, execution, UI, failure, disablement
  • trust boundary: what code runs where, under what authority

For large contributions, include a tutorial-style section that teaches the system from first principles.

3. Review like a maintainer

Findings come first. Order by severity.

Prioritize:

  • behavioral regressions
  • trust or security gaps
  • misleading abstractions
  • lifecycle and operational risks
  • coupling that will be hard to unwind
  • missing tests or unverifiable claims

Read the full file on GitHub · 202 lines

Files

What ships with it

2 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.

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 · 202 lines · 39 tokens per session scan A d4abb3074956

Subscribe to this mod's changes

pr-report is a skill published in the GitHub repository paperclipai/paperclip (80,206 stars, last pushed yesterday), licensed MIT. It adds 39 tokens to every session and 1,111 once invoked, about $0.0002 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.