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 data-workflowgit 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/data-workflow)<a href="https://agentmods.dev/skills/modu-ai/moai-cowork/data-workflow"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-cowork/data-workflow/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/data-workflow"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-cowork/data-workflow.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 | $0.00067 | $0.00497 |
| Opus 5.5 | $0.00027 | $0.00199 |
| Sonnet 5.5 | $0.00013 | $0.00099 |
| Haiku 4.5 | $0.00007 | $0.00050 |
Grade A, and why
data-workflow 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
데이터 작업 경로 선택
- 데이터 분야, 지역·대상, 기간, 산출물, 성공 기준을 확인한다. 필수 입력이 빠지면 현재 런타임의 질문 채널로 묻고, 질문할 수 없는 하위 실행에서는 누락값을 blocker로 반환한다.
- KOSIS·공공데이터는
data-public, 실거래가는data-realestate, 법원 경매는data-court-auction, 종목 데이터는data-stock, 건축물 자료는data-building-ledger지침을 따른다. 사용자가 준 CSV·Excel은data-explorer로 점검한 뒤 필요한 경우data-visualizer로 시각화한다. - 현재 세션에서 필요한 데이터 연결 도구가 실제로 노출되는지 확인한다. 연결이 없으면
연결 불가, 조회했지만 결과가 없으면[NOT_FOUND]와 조회 범위를 기록한다. 어느 경우에도 값을 만들어 채우지 않는다. 대체 자료를 찾을 때는 원래 요청과 출처·기준 시점이 다른지 밝힌다. - 공개 수치에는 통계표 ID, 공시 접수번호, 데이터셋 이름 또는 질의 조건을 연결한다. 원자료의 값·날짜·단위를 표와 차트로 옮길 때 다시 대조하고, 개인 식별 정보가 불필요하게 노출되지 않게 한다.
- 중요한 수치가 포함된 결과는
data-provenance-audit기준으로 대조한다. 같은 주체가 수행한 확인은 독립 감사라고 부르지 않는다. 결과에는 실제 조회 경로와 미검증 항목을 함께 적는다.
Claude의 data-analyst 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 c1e11e3fbff0
- 28d ago First seen · 17 lines · 67 tokens per session scan A 9e12334ddb67
data-workflow is a skill published in the GitHub repository modu-ai/moai-cowork (311 stars, last pushed 15d ago), licensed Apache-2.0. It adds 67 tokens to every session and 497 once invoked, about $0.0003 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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