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get_linkedin_profile

Extract LinkedIn profile data including headline, about section, and experience to automatically populate CVs and resumes with professional information.

Instructions

Get LinkedIn profile summary (headline, about, experience)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The main handler function for the 'get_linkedin_profile' tool. It checks for LINKEDIN_PROFILE_URL environment variable and returns a text content explaining limitations and alternatives due to LinkedIn's restrictions on automated access.
    async def get_linkedin_profile() -> list[TextContent]:
        """Get LinkedIn profile (limited due to LinkedIn restrictions)."""
        if not LINKEDIN_PROFILE_URL:
            return [TextContent(
                type="text",
                text="LinkedIn profile URL not configured. Set LINKEDIN_PROFILE_URL"
            )]
        
        output = f"""LinkedIn Profile Summary:
    
    Profile URL: {LINKEDIN_PROFILE_URL}
    
    Note: LinkedIn restricts automated access to profiles. For best results:
    1. Ensure your profile is set to public
    2. Manually copy key achievements to wins.md
    3. Or use LinkedIn's official API with proper authentication
    
    Alternative: Create a linkedin.md file with your profile summary, recent posts, and achievements."""
        
        return [TextContent(type="text", text=output)]
  • Registration of the 'get_linkedin_profile' tool in the list_tools() function, including its name, description, and empty input schema.
    Tool(
        name="get_linkedin_profile",
        description="Get LinkedIn profile summary (headline, about, experience)",
        inputSchema={
            "type": "object",
            "properties": {}
        }
    ),
  • The input schema for the tool, which is an empty object (no parameters required).
    inputSchema={
        "type": "object",
        "properties": {}
    }
  • Dispatch/registration in the call_tool handler that routes calls to the get_linkedin_profile function.
    elif name == "get_linkedin_profile":
        return await get_linkedin_profile()
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states what data is retrieved but doesn't mention authentication requirements, rate limits, data freshness, or what happens if no profile exists. This leaves significant behavioral gaps for a data retrieval tool.

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?

The description is appropriately concise with a single sentence that efficiently communicates the core functionality. It's front-loaded with the main purpose and lists specific data components without unnecessary elaboration.

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 tool's simplicity (0 parameters, no output schema, no annotations), the description covers the basic purpose adequately. However, for a data retrieval tool, it should ideally mention authentication or data source context, especially with no output schema to clarify return values.

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?

The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a baseline score of 4 for not adding unnecessary information.

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?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('LinkedIn profile summary'), listing key components (headline, about, experience). However, it doesn't differentiate from sibling tools since there are no other LinkedIn-related tools in the sibling list, so it can't demonstrate sibling differentiation.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, and with no similar tools in the sibling list, there's no explicit comparison or usage context provided.

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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