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get_install_guide

Provides step-by-step installation instructions for a skill on a specific platform, enabling guided setup.

Instructions

Get step-by-step installation instructions for a skill on a specific platform. / 플랫폼별 스킬 설치 가이드.

Args: skill_id: 스킬 ID platform: 플랫폼 이름 - 'OpenClaw' | 'ClaudeCode' | 'ClaudeCodeAgentSkill' | 'CustomAgent' | 'Cursor' | 'GeminiCLI' | 'CodexCLI'

Returns: 단계별 설치 가이드 문자열

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skill_idYes
platformNoOpenClaw

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main handler function for the 'get_install_guide' tool. It calls the REST API endpoint /v1/skills/{skill_id}/install-guide with a platform parameter, then formats the response into a readable step-by-step installation guide string.
    def get_install_guide(skill_id: str, platform: str = "OpenClaw") -> str:
        """
        Get step-by-step installation instructions for a skill on a specific platform. / 플랫폼별 스킬 설치 가이드.
    
        Args:
            skill_id: 스킬 ID
            platform: 플랫폼 이름 - 'OpenClaw' | 'ClaudeCode' | 'ClaudeCodeAgentSkill' | 'CustomAgent' | 'Cursor' | 'GeminiCLI' | 'CodexCLI'
    
        Returns:
            단계별 설치 가이드 문자열
        """
        result = _get(f"/v1/skills/{skill_id}/install-guide", {"platform": platform})
        if result.get("status") == "error":
            return f"오류: {result.get('message')}"
    
        steps = result.get("steps", [])
        lines = [
            f"📋 [{platform}] 설치 가이드 — {result.get('skill_name', skill_id)}",
            f"설정 파일 경로: {result.get('config_path', 'N/A')}",
            "",
            "설치 단계:",
        ]
        for i, step in enumerate(steps, 1):
            if isinstance(step, dict):
                lines.append(f"  {i}. {step.get('description', step)}")
                if step.get("command"):
                    lines.append(f"     $ {step['command']}")
            else:
                lines.append(f"  {i}. {step}")
        return "\n".join(lines)
  • The tool is registered with MCP via the @mcp.tool() decorator on the get_install_guide function. The FastMCP instance 'mcp' is created at line 60-80.
    @mcp.tool()
    @_log_tool
    def get_install_guide(skill_id: str, platform: str = "OpenClaw") -> str:
        """
        Get step-by-step installation instructions for a skill on a specific platform. / 플랫폼별 스킬 설치 가이드.
    
        Args:
            skill_id: 스킬 ID
            platform: 플랫폼 이름 - 'OpenClaw' | 'ClaudeCode' | 'ClaudeCodeAgentSkill' | 'CustomAgent' | 'Cursor' | 'GeminiCLI' | 'CodexCLI'
    
        Returns:
            단계별 설치 가이드 문자열
        """
        result = _get(f"/v1/skills/{skill_id}/install-guide", {"platform": platform})
        if result.get("status") == "error":
            return f"오류: {result.get('message')}"
    
        steps = result.get("steps", [])
        lines = [
            f"📋 [{platform}] 설치 가이드 — {result.get('skill_name', skill_id)}",
            f"설정 파일 경로: {result.get('config_path', 'N/A')}",
            "",
            "설치 단계:",
        ]
        for i, step in enumerate(steps, 1):
            if isinstance(step, dict):
                lines.append(f"  {i}. {step.get('description', step)}")
                if step.get("command"):
                    lines.append(f"     $ {step['command']}")
            else:
                lines.append(f"  {i}. {step}")
        return "\n".join(lines)
  • The _get helper function is used by get_install_guide to make the REST API call to the Skill Store backend. It sends an HTTP GET with URL-encoded params and returns parsed JSON.
    def _get(path: str, params: dict = None) -> dict:
        url = SKILL_STORE_URL + path
        if params:
            url += "?" + urllib.parse.urlencode({k: v for k, v in params.items() if v is not None})
        try:
            with urllib.request.urlopen(url, timeout=10) as resp:
                return json.loads(resp.read().decode())
        except urllib.error.HTTPError as e:
            return {"status": "error", "message": f"HTTP {e.code}: {e.reason}"}
        except Exception as e:
            return {"status": "error", "message": str(e)}
  • The input schema is defined via function signature: skill_id (str, required) and platform (str, optional, default 'OpenClaw'). The valid platform values are documented in the docstring: OpenClaw, ClaudeCode, ClaudeCodeAgentSkill, CustomAgent, Cursor, GeminiCLI, CodexCLI. Return type is str.
    def get_install_guide(skill_id: str, platform: str = "OpenClaw") -> str:
        """
        Get step-by-step installation instructions for a skill on a specific platform. / 플랫폼별 스킬 설치 가이드.
    
        Args:
            skill_id: 스킬 ID
            platform: 플랫폼 이름 - 'OpenClaw' | 'ClaudeCode' | 'ClaudeCodeAgentSkill' | 'CustomAgent' | 'Cursor' | 'GeminiCLI' | 'CodexCLI'
    
        Returns:
            단계별 설치 가이드 문자열
        """
Behavior2/5

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

No annotations are provided, and the description lacks behavioral details such as side effects, authentication needs, or error handling. It only states the basic function and return type.

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

Conciseness5/5

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

The description is extremely concise with a clear purpose statement in two languages and a structured Args/Returns section. Every word adds value.

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?

Given the low complexity and presence of an output schema, the description covers basic parameter and return semantics but omits default values and usage context, which could improve completeness.

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?

With 0% schema description coverage, the description adds significant meaning by listing parameter names, brief explanations, and enumerated values for platform, compensated adequately.

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

Purpose5/5

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

The description clearly states it retrieves step-by-step installation instructions for a skill on a specific platform, distinguishing it from sibling tools like get_skill or download_skill.

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

Usage Guidelines3/5

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

The description implies usage for installation instructions, but does not explicitly state when to use or not use this tool, nor does it mention alternatives or prerequisites.

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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