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/test-audit/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/test-audit)<a href="https://agentmods.dev/skills/paperclipai/paperclip/test-audit"><img src="https://agentmods.dev/badge/skills/paperclipai/paperclip/test-audit/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/test-audit"><img src="https://agentmods.dev/badge/skills/paperclipai/paperclip/test-audit.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 | $0.00055 | $0.00852 |
| Opus 5.5 | $0.00022 | $0.00341 |
| Sonnet 5.5 | $0.00011 | $0.00170 |
| Haiku 4.5 | $0.00006 | $0.00085 |
Grade A, and why
test-audit 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 5d 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Audit
Reduce execution and maintenance cost while preserving meaningful failure detection. Investigate aggressively; delete only with evidence. Retaining an area after review is a valid result. This skill is self-contained; upstream attribution is in NOTICE.md.
Choose the scope
- Focused cleanup: follow this entry point and read the candidate evidence guide before editing.
- Multiple owners, agents, or PRs: also read CAMPAIGN.md. Declare whether the work is a targeted sweep or an exhaustive subsystem audit.
- Validation and cost claims: read references/validation.md.
- Paperclip commands, invariants, and delivery: read references/paperclip.md alongside repository instructions.
Decision gate
For every proposed removal, answer:
- Which observable contract and plausible regression do the assertions cover?
- Which retained file/case detects that regression through the responsible production code? Otherwise, why is the assertion vacuous or contract retired?
- Does this candidate uniquely cover a transport, permission, lifecycle, storage boundary, platform, default, or other independent failure mode?
- What improves: executions, fixtures, processes, maintenance, or runtime?
Prefer the smallest test that reaches the code responsible for the contract. A broader suite is not automatically stronger proof. Similarity, size, slowness, or suspected AI authorship alone never justify deletion.
Prevent new duplication
Apply this gate to tests added or changed during gardening:
- Name the regression that existing proof misses. Extend an appropriate owner or table before adding another suite; another layer needs a distinct risk.
- Exercise the responsible production behavior. Do not add a mock that supplies the result being asserted or a production hook solely for convenient testing.
- Check observable outcomes that survive behavior-preserving refactors. A negative case must reach its named guard with otherwise valid inputs.
What ships with it
6 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.
- 5d ago Changed · +5 lines 5944c84f8afd
- 11d ago First seen · 79 lines · 55 tokens per session scan A d25690311967
test-audit is a skill published in the GitHub repository paperclipai/paperclip (107,044 stars, last pushed today), licensed MIT. It adds 55 tokens to every session and 852 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 2026-10-14.
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