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 konamgil/mandu --skill mandu-mcp-verifygit clone --depth 1 https://github.com/konamgil/manduWrote 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/konamgil/mandu/mandu-mcp-verify)<a href="https://agentmods.dev/skills/konamgil/mandu/mandu-mcp-verify"><img src="https://agentmods.dev/badge/skills/konamgil/mandu/mandu-mcp-verify/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/konamgil/mandu/mandu-mcp-verify"><img src="https://agentmods.dev/badge/skills/konamgil/mandu/mandu-mcp-verify.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 | $0.00066 | $0.02068 |
| Opus 5 | $0.00033 | $0.01034 |
| Sonnet 5 | $0.00013 | $0.00414 |
| Haiku 4.5 | $0.00007 | $0.00207 |
Grade A, and why
mandu-mcp-verify 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.
How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mandu MCP Verify
편집 직후 / 생성 직후 / pre-commit 에서 도는 표준 검증 루프. 핵심은 "하나의 ate 파이프라인 + guard + 구조 진단" 을 병렬 fast path 로 먼저 돌리고, 실패했을 때만 세분 도구로 drill-down 하는 것.
Trigger
- 파일 편집 직후 (특히
app/,spec/,src/shared/contracts/) mandu_generate완료 직후 (create-flow 가 자동 전이)- "check 해줘", "제대로 된 거야?", "괜찮아?"
- stop-hook / pre-commit 자동 실행
- 사용자가 명시적으로 "verify", "validate", "검증"
Fast Path (병렬, 기본값)
네 도구는 서로 독립. 병렬 호출.
┌─────────────────────────────┐
│ mandu.ate.auto_pipeline │ ← Tier-0: extract/generate/run/heal 전부
├─────────────────────────────┤
│ mandu_guard_check │ ← Tier-1: 아키텍처 규칙 위반 스캔
├─────────────────────────────┤
│ mandu.lint │ ← 가드레일-lint: 코드 품질 스캔 (oxlint)
├─────────────────────────────┤
│ mandu_doctor │ ← Tier-0: 구조/import/location 진단
└─────────────────────────────┘
네 개를 parallel 호출
인자 예:
mandu.ate.auto_pipeline({
repoRoot: ".",
oracleLevel: "standard",
useImpactAnalysis: true, // 변경된 라우트만 대상
autoHeal: false // heal 은 별도 단계
})
mandu_guard_check({ repoRoot: "." })
mandu.lint({ typeAware: false }) // oxlint 미설치 시 조용히 skip
mandu_doctor({ repoRoot: "." })
네 응답을 수집하고 pass/fail 매트릭스를 만든다:
| 도구 | pass | fail 의 의미 |
|---|---|---|
ate.auto_pipeline |
테스트 통과 + 계약 일치 | 테스트 실패 또는 impact 드리프트 |
guard_check |
레이어/금지 import 위반 없음 | 아키텍처 규칙 위반 |
lint |
oxlint error 0 | error 1+ (warning 은 informational) |
doctor |
파일 위치 / import 정상 | 구조 결함 |
네 개 모두 green → verify 종료. 사용자에게 압축 요약 제시.
Drill-Down (실패 시에만)
fast path 가 빨간 항목을 돌려주면 그 카테고리별로만 drill-down. 세 종류가 다 실패했다고 모든 drill-down 을 돌리지 말고, 응답에 들어온 카테고리만.
Guard 실패
mandu_guard_explain({ violationId }) ← 먼저: 왜 위반인지 설명
→ (자동 수정 가능하면) mandu_guard_heal({ autofix: true, violationIds: [...] })
→ (수동 수정이면) 사용자에게 수정 지시 후 fast path 재실행
ATE 실패 (테스트 실패 / 힐 후보 있음)
mandu.ate.feedback({ runId }) ← 힐 후보의 카테고리/우선순위
→ mandu.ate.apply_heal({ runId, healIndex, createBackup: true })
→ fast path 의 ate.auto_pipeline 재실행
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 · 183 lines · 66 tokens per session scan A 3a77a2ef1e77
mandu-mcp-verify is a skill published in the GitHub repository konamgil/mandu (46 stars, last pushed 14d ago), licensed MPL-2.0. It adds 66 tokens to every session and 2,068 once invoked, about $0.0003 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.
Other skills, from other repositories
bug-fix
A structured bug-fixing workflow that takes a problem from reproduction and evidence-based cause finding through approval, implementation, testing, and cleanup.
error-collection
A structured record of confirmed engineering mistakes, their root causes, and checks that prevent them from returning. It uses evidence from real application behavior, not just successful builds.
flaky-test-triage
Use when a test passes and fails intermittently, behaves differently by order, machine, runtime, timing, or retry, or when the user asks to reduce test flakiness. Gather repeatable evidence, isolate nondeterminism, and repair the causal dependency without weakening test intent.
test-debugger
Use when a test fails, flakes, hangs, or gives an unexpected result. Reproduce the failure with the narrowest package-local command, distinguish test defects from product defects and environment issues, and only implement a fix when the user authorizes changes.
bug-fixing
Fix defects in the Composio SDK repository with focused reproduction, root-cause analysis, regression tests, and narrow verification. Use when the user reports a bug, failing test, CI regression, runtime defect, or incorrect SDK behavior. Do not use for new feature design or broad refactors.
typescript-testing
Select and run TypeScript SDK verification for packages, examples, type checks, linting, builds, Vitest suites, and runtime E2E tests. Use when adding tests, diagnosing TypeScript CI, choosing a focused test command, or validating TypeScript package changes. Do not use for Python-only checks.