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check_vetting_status

Check the security vetting status of an uploaded skill version using version ID and API key to monitor approval progress.

Instructions

Check the security vetting status of an uploaded skill version. / 업로드 스킬의 보안 검수 상태 확인. upload_skill 결과에서 받은 version_id와 API 키가 필요합니다.

Args: version_id: 스킬 버전 ID (upload_skill 결과의 version_id 또는 vetting_job_id) api_key: 개발자 API 키 (스킬 소유자만 조회 가능)

Returns: 검수 상태 메시지

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
version_idYes
api_keyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main handler for check_vetting_status tool. Calls _get_auth to the vetting-status API endpoint, parses the vetting_status field, and returns a formatted status message with icons for approved/rejected/pending etc.
    @mcp.tool()
    @_log_tool
    def check_vetting_status(version_id: str, api_key: str) -> str:
        """
        Check the security vetting status of an uploaded skill version. / 업로드 스킬의 보안 검수 상태 확인.
        upload_skill 결과에서 받은 version_id와 API 키가 필요합니다.
    
        Args:
            version_id: 스킬 버전 ID (upload_skill 결과의 version_id 또는 vetting_job_id)
            api_key: 개발자 API 키 (스킬 소유자만 조회 가능)
    
        Returns:
            검수 상태 메시지
        """
        result = _get_auth(f"/v1/skills/versions/{version_id}/vetting-status", api_key)
        if result.get("status") == "error":
            return f"❌ 조회 실패: {result.get('message')}"
    
        vetting = result.get("vetting_status", "unknown")
        status_icon = {
            "approved": "✅ 승인",
            "officially_approved": "✅ 공식 승인",
            "caution": "⚠️ 주의 (수동 검토 필요)",
            "rejected": "❌ 거부",
            "pending": "⏳ 검수 중",
        }.get(vetting, f"❓ {vetting}")
    
        lines = [
            f"검수 상태: {status_icon}",
            f"버전 ID: {version_id}",
        ]
    
        if result.get("job_id"):
            lines.append(f"Job ID: {result['job_id']}")
            lines.append(f"Job 상태: {result.get('job_status', 'N/A')}")
        if result.get("started_at"):
            lines.append(f"시작: {result['started_at']}")
        if result.get("finished_at"):
            lines.append(f"완료: {result['finished_at']}")
        if result.get("error_msg"):
            lines.append(f"오류: {result['error_msg']}")
    
        return "\n".join(lines)
  • The tool is registered via the @mcp.tool() decorator on line 789, which is the FastMCP decorator that registers the function as an MCP tool.
    @mcp.tool()
  • The _get_auth helper function used by check_vetting_status to make an authenticated GET request with X-API-KEY header to the skill store API.
    def _get_auth(path: str, api_key: str, params: dict = None) -> dict:
        """API 키 인증이 필요한 GET 요청."""
        url = SKILL_STORE_URL + path
        if params:
            url += "?" + urllib.parse.urlencode({k: v for k, v in params.items() if v is not None})
        req = urllib.request.Request(url, headers={"X-API-KEY": api_key})
        try:
            with urllib.request.urlopen(req, timeout=10) as resp:
                return json.loads(resp.read().decode())
        except urllib.error.HTTPError as e:
            body = e.read().decode()
            try:
                body = json.loads(body).get("message", body)
            except Exception:
                pass
            return {"status": "error", "message": f"HTTP {e.code}: {body}"}
        except Exception as e:
            return {"status": "error", "message": str(e)}
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must carry full behavioral burden. Mentions ownership restriction and return is a status message, but does not explicitly state this is a read-only operation or describe side effects, rate limits, or failure modes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is short and front-loaded with purpose. Bilingual content adds length but remains efficient. Every sentence provides needed information; no fluff. Could be slightly more concise by dropping one language.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With output schema available, description does not need full return details, but it only mentions '검수 상태 메시지' vaguely. It covers core usage but lacks mention of output schema or potential errors. For a simple 2-param tool, it is acceptable but incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Explains both parameters beyond schema: version_id as coming from upload_skill result (or vetting_job_id) and api_key as developer API key. This adds meaningful context beyond the basic schema titles. However, format details are lacking.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'Check the security vetting status of an uploaded skill version' with verb+resource. However, it does not distinguish from sibling tools like check_draft_status or get_vetting_result, missing explicit differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Specifies prerequisites: version_id from upload_skill result and api_key. Mentions only skill owner can query. Provides clear context for when to use but omits alternatives or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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