Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add modu-ai/moai-cowork --skill doc-data-auditgit clone --depth 1 https://github.com/modu-ai/moai-coworkWrote 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/modu-ai/moai-cowork/doc-data-audit)<a href="https://agentmods.dev/skills/modu-ai/moai-cowork/doc-data-audit"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-cowork/doc-data-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/modu-ai/moai-cowork/doc-data-audit"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-cowork/doc-data-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 | $0.00057 | $0.00414 |
| Opus 5.5 | $0.00023 | $0.00166 |
| Sonnet 5.5 | $0.00011 | $0.00083 |
| Haiku 4.5 | $0.00006 | $0.00041 |
Grade A, and why
doc-data-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 17d 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.
What it actually says
문서·수치 검수
원본을 수정하지 않고 산출물과 제공된 자료를 대조한다.
- 통계마다 식별 가능한 출처와 기준 시점을 확인한다. 공공데이터의 원천 진위까지 필요한 경우
moai-analyst:data-provenance-audit기준으로 별도 확인한다. - 차트·SVG 라벨·표·요약문의 값, 단위, 축 범위와 날짜가 원자료와 일치하는지 확인한다. 합계·증감률·평균·단위 변환을 다시 계산한다.
- 파일 확장자와 실제 형식, 공문서의 수신·본문·붙임, 번호와 날짜 표기가 목적에 맞는지 확인한다.
- 주민등록번호·연락처·개인 주소·계좌번호가 불필요하게 노출됐는지 확인한다. 자료 조회·파싱 실패를 추정값으로 채우지 않았는지 본다.
보고서는 판정(PASS/FAIL/미확인), 확인 자료, 수치별 재계산, 심각도·위치·근거가 있는 발견, 미검증 항목으로 작성한다. 원자료가 없으면 정합성을 PASS로 판정하지 않는다. 독립된 검수자를 실행하지 않았다면 독립 감사라고 부르지 않는다.
Claude의 data-auditor 에이전트와 목적이 겹친다. ChatGPT 플러그인에서는 이 스킬이 발견 가능한 진입점이다.
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.
- 17d ago Changed · +1 lines 84024c857fd0
- 28d ago First seen · 20 lines · 57 tokens per session scan A 60edbd49b930
doc-data-audit is a skill published in the GitHub repository modu-ai/moai-cowork (311 stars, last pushed 15d ago), licensed Apache-2.0. It adds 57 tokens to every session and 414 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 2026-09-26.
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