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.
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.
curl -O https://raw.githubusercontent.com/paperclipai/paperclip/master/.agents/skills/create-paperclip-bundled-skill/SKILL.mdgit clone --depth 1 https://github.com/paperclipai/paperclipWrote 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/paperclipai/paperclip/create-paperclip-bundled-skill)<a href="https://agentmods.dev/skills/paperclipai/paperclip/create-paperclip-bundled-skill"><img src="https://agentmods.dev/badge/skills/paperclipai/paperclip/create-paperclip-bundled-skill/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/paperclipai/paperclip/create-paperclip-bundled-skill"><img src="https://agentmods.dev/badge/skills/paperclipai/paperclip/create-paperclip-bundled-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- 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 | $0.00073 | $0.02675 |
| Opus 5 | $0.00036 | $0.01337 |
| Sonnet 5 | $0.00015 | $0.00535 |
| Haiku 4.5 | $0.00007 | $0.00267 |
Grade A, and why
create-paperclip-bundled-skill 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 13d 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 — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create a Paperclip Bundled Skill
Take source material — a tweet, a task description, a blog post, "make a skill
that does X" — and land it as a skill in the Paperclip skills catalog
(packages/skills-catalog/), delivered as a reviewed PR. The catalog is the
shelf every Paperclip company browses and installs from, so the bar is: correct
metadata, useful instructions, worked examples, and a clean validation run.
The core rule is FIND before MAKE: if a good skill already exists (in the catalog, in this repo, or published on GitHub), reference or adapt it instead of writing a duplicate from scratch.
When to use
- A human sends a tweet/link/idea and asks for it to become a Paperclip skill.
- A task asks to bundle an existing repo skill into the catalog.
- A task asks to add an external published skill to the catalog.
When not to use
- The skill is company-private (belongs in that company's library via the Skills UI/API, not the shipped catalog).
- You only need a repo-internal agent skill for working on Paperclip itself —
that goes in
.agents/skills/orskills/, with no catalog machinery.
Step 0 — Capture the source material
Understand exactly what the skill should teach before writing anything.
Tweets / X links. Use the xc CLI (X API client). Paperclip engineering
agent environments ship it preinstalled and pre-authenticated; it is not a
tool you install or mint credentials for yourself. Check availability before
relying on it:
command -v xc && xc whoami # on PATH and authenticated? if not, use the fallback below
xc get <post-url-or-id> --json # the post itself (conversation_id, author)
xc search 'conversation_id:<id>' --archive --json # rest of the thread (>7 days old needs --archive)
xc user <username> # author context
xc search '<topic keywords>' -n 30 # related discussion
If xc is not on PATH, is unauthenticated, or the account lacks read access
(the check above fails for any reason), delegate the
fetch to a teammate with X/Twitter access (e.g. the Content Strategist agent)
via a child issue: give them the URL and ask for full text of the post + thread
- any linked content.
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.
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.
- 13d ago First seen · 266 lines · 73 tokens per session scan A fd3861bf0e44
create-paperclip-bundled-skill is a skill published in the GitHub repository paperclipai/paperclip (80,500 stars, last pushed today), licensed MIT. It adds 73 tokens to every session and 2,675 once invoked, about $0.0004 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.
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