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 commerce-automation-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/commerce-automation-audit)<a href="https://agentmods.dev/skills/modu-ai/moai-cowork/commerce-automation-audit"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-cowork/commerce-automation-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/commerce-automation-audit"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-cowork/commerce-automation-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00406 | $0.03317 |
| Opus 5 | $0.00203 | $0.01658 |
| Sonnet 5 | $0.00081 | $0.00663 |
| Haiku 4.5 | $0.00041 | $0.00332 |
Grade A, and why
commerce-automation-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 7d 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 — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
커머스 자동화 진단·로드맵 (Commerce Automation Audit)
개요
이커머스 셀러가 자기 매장의 운영 자동화 가능성을 자체 진단하고 우선순위·로드맵을 자동 생성하는 컨설팅용 스킬.
책임 한 줄: 셀러 현황 입력 → 6대 영역 진단 + 자동화 우선순위 점수 + 3 Phase 로드맵 + 5 KPI 목표치 + HITL 검수 지점 자동 생성.
6대 커머스 업무 영역
| 영역 | 질문 | 주요 업무 | ROI |
|---|---|---|---|
| A 상품 운영 | "무엇을 팔 것인가" | 상품 소싱·등록·이미지·상세페이지·카테고리 | 중 |
| B 가격 & 프로모션 | "얼마에, 어떻게 팔 것인가" | 원가 분석·마진 계산·할인 정책·쿠폰·이벤트 | 중 |
| C 주문 & 정산 | "주문 처리와 대금 수취" | 주문 수집·송장 발행·취소/반품/교환·정산·매칭 | 🏆 최고 ROI (30-50% 절감) |
| D 재고 & 물류 | "재고를 어디에 얼마나 둘 것인가" | 실시간 재고·안전재고·발주·입출고·배송사 연동 | 중 |
| E 마케팅 & 고객 | "고객을 데려오고 유지" | 광고 집행·퍼포먼스 마케팅·CRM·문의·리뷰 | 중 |
| F 데이터 & 경영 | "잘 되고 있는지 판단" | KPI 모니터링·손익·성과 분석·전략 의사결정 | 높음 |
자동화 유형 3분류
| 유형 | 정의 | 자동화 전략 | 도구 예시 |
|---|---|---|---|
| ① 반복형 (Repetitive) | 사람이 같은 일을 반복 — 데이터 입력·복사·정기 리포트 | RPA / Workflow | Zapier, Make, UiPath, Power Automate |
| ② 판단형 (Judgment) | 규칙·기준으로 결정 — 카테고리 분류·이상 거래·발주량 | Rule Engine + AI | Drools, AWS SageMaker, Custom Python |
| ③ 창의형 (Creative) | 기획·전략·카피 — 이벤트 기획·상세페이지 문구 | AI Copilot | ChatGPT, Claude, GPT-4 |
자동화 설계 4단계 프로세스
[STEP 1] 업무 나열 (List Up)
- 모든 업무를 표준 포맷으로 나열
- 업무명 / 주기 / 소요시간 / 입력(Input) / 출력(Output) / 사람이 개입하는 이유
↓
[STEP 2] 유형 분류 (Categorize)
- 나열된 업무를 3가지로 분류
- ① 반복형 ② 판단형 ③ 창의형
↓
[STEP 3] 우선순위 점수 (Scoring)
- ROI 기반 점수 = (빈도 × 시간 × 오류비용) ÷ 복잡도
- 예외 발생 비율이 높은 업무는 '복잡도' 점수를 높게 설정
↓
[STEP 4] 방식 결정 (Decision)
- High: RPA / API 연동 즉시 적용
- Mid: Rule Engine + AI 검토 후 진행
- Low: AI Copilot 보조만 (완전 자동화 어려운 창의형)
자동화 준비도 체크리스트 (HARD)
다음 5종 중 미달 항목이 있으면 자동화 도입 전 선행 작업 필수:
| 점검 항목 | 준비도 기준 | 미달 시 선행 작업 |
|---|---|---|
| 데이터 구조화 | 주문/상품/재고 DB 정규화 완료 | ERD 재설계 + 마이그레이션 |
| API 연동 가능성 | 주요 쇼핑몰 API 키 확보 | 파트너십 협의 or 크롤링 대체 |
| 프로세스 표준화 | 동일 업무의 처리 방식 통일 | SOP 문서화 + 교육 |
| 권한 체계 | 시스템 간 인증 자동화 가능 | SSO 구축 or API 토큰 관리 |
| 예외 처리 정책 | 자동화 실패 시 대응 매뉴얼 | Fallback 프로세스 설계 |
Pro Tip: "엑셀 → 쇼핑몰 등록" 자동화 전에 엑셀 템플릿 표준화가 80% 더 중요. 부서마다 다른 엑셀 양식을 통일하는 게 자동화 성공의 핵심.
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.
- 7d ago First seen · 215 lines · 406 tokens per session scan A 8f0c3bae4143
commerce-automation-audit is a skill published in the GitHub repository modu-ai/moai-cowork (300 stars, last pushed 8d ago), licensed Apache-2.0. It adds 406 tokens to every session and 3,317 once invoked, about $0.0020 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 2026-09-03.
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