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 mupengi-bot/mupengism --skill kmonggit clone --depth 1 https://github.com/mupengi-bot/mupengismWrote 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/mupengi-bot/mupengism/kmong)<a href="https://agentmods.dev/skills/mupengi-bot/mupengism/kmong"><img src="https://agentmods.dev/badge/skills/mupengi-bot/mupengism/kmong/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/mupengi-bot/mupengism/kmong"><img src="https://agentmods.dev/badge/skills/mupengi-bot/mupengism/kmong.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 | $0.00000 | $0.00719 |
| Opus 5 | $0.00000 | $0.00360 |
| Sonnet 5 | $0.00000 | $0.00144 |
| Haiku 4.5 | $0.00000 | $0.00072 |
Grade A, and why
kmong 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 10d 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
크몽 자동화 스킬 🐧
가입 프로세스 (OpenClaw 브라우저)
1. 회원가입
1. browser open → https://kmong.com
2. 회원가입 클릭 (ref: 회원가입 링크)
3. 구글 로그인 선택 (구글 로고 버튼)
4. 구글 계정 선택 → "계속" 클릭
5. "전문가로 활동" 선택
6. 전체 동의 체크 → "가입완료"
2. 본인인증 (PASS SMS)
1. "휴대폰 본인인증" 클릭 → 팝업 탭 열림
2. 팝업 탭 targetId 확인 (tabs 조회)
3. 통신사 라디오 선택: evaluate로 클릭
- document.querySelectorAll('input[type=radio]')[0].click() // SKT
- [1] = KT, [2] = LGU+
4. 전체동의: document.querySelectorAll('input[type=checkbox]')[0].click()
5. "문자(SMS)로 인증하기" 클릭
6. 이름, 생년월일(6자리), 주민번호 7번째, 전화번호, 보안문자 입력
7. 보안문자는 screenshot으로 읽기
8. "확인" → SMS 인증번호 입력 → "확인"
9. 메인 탭에서 판매 약관 동의 → "전문가 등록 완료"
3. 주의사항
- 체크박스 ref가 안 먹을 때:
evaluate로document.querySelectorAll('input[type=checkbox]')[0].click() const/let사용 불가 —var또는 선언 없이 사용- 세미콜론으로 여러 문장 연결 불가 — 한 문장씩 evaluate
- PASS 인증 팝업은 별도 탭 — tabs 조회로 targetId 확인 필요
- 보안문자(캡차)는 screenshot 찍어서 이미지로 읽기
4. 프로필 설정
1. 닉네임 변경: "편집" 버튼 → 텍스트 전체선택(Meta+a) → 새 닉네임 입력 → "저장"
2. 전문분야: "서비스를 제공할 분야를 선택하세요" 클릭
3. 소개: "소개 작성하기" 클릭
4. 서비스 등록: "서비스 등록하기" 클릭
5. 서비스 등록 팁
- 제목: SEO 키워드 포함 (예: "AI 챗봇 개발 | 학생회 조직 관리 자동화")
- 가격: 3단계 (스탠다드/디럭스/프리미엄)
- 설명: 500자 이상, 구체적 결과물 명시
- 카테고리: IT·프로그래밍 > 챗봇 개발 / 업무 자동화
계정 정보
- 이메일: Configure in
~/.secrets/kmong.env - 닉네임: Configure in workspace settings
- 프로필: https://kmong.com/@[your-username]
🐧 Built by 무펭이 — 무펭이즘(Mupengism) 생태계 스킬
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.
- 10d ago First seen · 62 lines · 0 tokens per session scan A 96dc969f8729
kmong is a skill published in the GitHub repository mupengi-bot/mupengism (10 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 719 tokens. 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 2026-08-31.
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