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/doc-maintenance/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/doc-maintenance)<a href="https://agentmods.dev/skills/paperclipai/paperclip/doc-maintenance"><img src="https://agentmods.dev/badge/skills/paperclipai/paperclip/doc-maintenance/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/doc-maintenance"><img src="https://agentmods.dev/badge/skills/paperclipai/paperclip/doc-maintenance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- 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 | $0.00044 | $0.01615 |
| Opus 5 | $0.00022 | $0.00807 |
| Sonnet 5 | $0.00009 | $0.00323 |
| Haiku 4.5 | $0.00004 | $0.00161 |
Grade A, and why
doc-maintenance scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Doc Maintenance Skill
Detect documentation drift and fix it via PR — no rewrites, no churn.
When to Use
- Periodic doc review (e.g. weekly or after releases)
- After major feature merges
- When asked "are our docs up to date?"
- When asked to audit README / SPEC / PRODUCT accuracy
Target Documents
| Document | Path | What matters |
|---|---|---|
| README | README.md |
Features table, roadmap, quickstart, "what is" accuracy, "works with" table |
| SPEC | doc/SPEC.md |
No false "not supported" claims, major model/schema accuracy |
| PRODUCT | doc/PRODUCT.md |
Core concepts, feature list, principles accuracy |
Out of scope: DEVELOPING.md, DATABASE.md, CLI.md, doc/plans/, skill files, release notes. These are dev-facing or ephemeral — lower risk of user-facing confusion.
Workflow
Step 1 — Detect what changed
Find the last review cursor:
# Read the last-reviewed commit SHA
CURSOR_FILE=".doc-review-cursor"
if [ -f "$CURSOR_FILE" ]; then
LAST_SHA=$(cat "$CURSOR_FILE" | head -1)
else
# First run: look back 60 days
LAST_SHA=$(git log --format="%H" --after="60 days ago" --reverse | head -1)
fi
Then gather commits since the cursor:
git log "$LAST_SHA"..HEAD --oneline --no-merges
Step 2 — Classify changes
Scan commit messages and changed files. Categorize into:
- Feature — new capabilities (keywords:
feat,add,implement,support) - Breaking — removed/renamed things (keywords:
remove,breaking,drop,rename) - Structural — new directories, config changes, new adapters, new CLI commands
Ignore: refactors, test-only changes, CI config, dependency bumps, doc-only changes, style/formatting commits. These don't affect doc accuracy.
For borderline cases, check the actual diff — a commit titled "refactor: X" that adds a new public API is a feature.
Step 3 — Build a change summary
Produce a concise list like:
Since last review (<sha>, <date>):
- FEATURE: Plugin system merged (runtime, SDK, CLI, slots, event bridge)
- FEATURE: Project archiving added
- BREAKING: Removed legacy webhook adapter
- STRUCTURAL: New .agents/skills/ directory convention
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.
- 9d ago First seen · 200 lines · 44 tokens per session scan A e633cf4d7f3a
doc-maintenance is a skill published in the GitHub repository paperclipai/paperclip (80,206 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 1,615 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.
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