Borrowing it
Nothing to install: this file belongs to chals-go/kakaocloud-openapi-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/chals-go/kakaocloud-openapi-mcp/main/.claude/skills/kakaocloud-mcp-orchestrator/SKILL.mdgit clone --depth 1 https://github.com/chals-go/kakaocloud-openapi-mcpWrote 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/chals-go/kakaocloud-openapi-mcp/kakaocloud-mcp-orchestrator)<a href="https://agentmods.dev/skills/chals-go/kakaocloud-openapi-mcp/kakaocloud-mcp-orchestrator"><img src="https://agentmods.dev/badge/skills/chals-go/kakaocloud-openapi-mcp/kakaocloud-mcp-orchestrator/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/chals-go/kakaocloud-openapi-mcp/kakaocloud-mcp-orchestrator"><img src="https://agentmods.dev/badge/skills/chals-go/kakaocloud-openapi-mcp/kakaocloud-mcp-orchestrator.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 | $0.00097 | $0.02097 |
| Opus 5 | $0.00048 | $0.01048 |
| Sonnet 5 | $0.00019 | $0.00419 |
| Haiku 4.5 | $0.00010 | $0.00210 |
Grade A, and why
kakaocloud-mcp-orchestrator 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 12d 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
카카오클라우드 MCP 오케스트레이터
카카오클라우드 OpenAPI 문서를 수집하고 MCP 서버를 개발하는 전체 파이프라인을 조율하는 통합 스킬.
실행 모드: 서브 에이전트
에이전트 구성
| 에이전트 | 에이전트 정의 | 역할 | 스킬 | 출력 |
|---|---|---|---|---|
| api-researcher | .claude/agents/api-researcher.md |
API 문서 크롤링/구조화 | api-research | _workspace/01_api_research/ |
| mcp-developer | .claude/agents/mcp-developer.md |
MCP 서버 구현 | mcp-development | 프로젝트 루트 소스코드 |
| mcp-tester | .claude/agents/mcp-tester.md |
MCP 도구 검증 | - | _workspace/03_test_results/ |
워크플로우
Phase 0: 컨텍스트 확인
_workspace/디렉토리 존재 여부를 확인한다- 실행 모드를 결정한다:
_workspace/미존재 → 초기 실행. Phase 1로 진행_workspace/존재 + 사용자가 부분 수정 요청 → 부분 재실행. 해당 에이전트만 재호출- "API 추가 수집" → api-researcher만 재호출
- "MCP 코드 수정" → mcp-developer만 재호출
- "테스트 다시" → mcp-tester만 재호출
_workspace/존재 + 새 전체 실행 요청 →_workspace/를_workspace_{timestamp}/로 이동 후 Phase 1 진행
- 기존 프로젝트 소스코드(src/) 존재 여부도 확인하여 mcp-developer에게 전달한다
Phase 1: 준비
- 사용자 입력을 분석한다:
- 전체 서비스 수집인지 특정 서비스만인지 파악
- MCP 서버 기술 스택 선호도 확인 (TypeScript/Python, 기본값: TypeScript)
- 특별한 요구사항 파악
_workspace/디렉토리를 생성한다- 입력 분석 결과를
_workspace/00_input/requirements.md에 저장한다
Phase 2: API 문서 수집
api-researcher 에이전트를 호출하여 카카오클라우드 OpenAPI 문서를 수집한다.
Agent(
description: "카카오클라우드 API 문서 수집",
prompt: "<api-researcher.md의 역할 설명>
api-research 스킬(.claude/skills/api-research/SKILL.md)을 읽고 따르라.
조사 대상: <Phase 1에서 결정된 서비스 목록>
출력 위치: _workspace/01_api_research/
이전 산출물이 있다면 읽고 개선점을 반영하라.",
model: "opus"
)
완료 확인:
_workspace/01_api_research/summary.md존재 확인- 최소 1개 이상의 서비스 JSON 파일 존재 확인
- 수집 실패 서비스가 있다면 기록 확인
Phase 3: MCP 서버 개발
mcp-developer 에이전트를 호출하여 MCP 서버를 구현한다.
Agent(
description: "카카오클라우드 MCP 서버 구현",
prompt: "<mcp-developer.md의 역할 설명>
mcp-development 스킬(.claude/skills/mcp-development/SKILL.md)을 읽고 따르라.
API 스펙 데이터: _workspace/01_api_research/
기술 스택: <Phase 1에서 결정된 스택>
요구사항: _workspace/00_input/requirements.md
프로젝트 루트에 MCP 서버 코드를 생성하라.
기존 코드가 있다면 읽고 수정/개선하라.",
model: "opus"
)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 199 lines · 97 tokens per session scan A 8b7e43eebb84
kakaocloud-mcp-orchestrator is a skill published in the GitHub repository chals-go/kakaocloud-openapi-mcp (1 stars, last pushed 4mo ago), licensed MIT. It adds 97 tokens to every session and 2,097 once invoked, about $0.0005 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 2026-08-31.
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