Skip to main content
Glama
Godofdeath1709

pathpilot-mcp-server

get_linkedin_profile

Retrieve a user-authorized, normalized LinkedIn profile snapshot with declared skills, roles, education, certifications, and projects.

Instructions

Return user-authorized, normalized LinkedIn profile snapshot with declared skills, roles, education, certifications, and projects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
useDemoNoIf true, returns a normalized demo profile. Set false to attempt real LinkedIn connection.
profileRefNoOptional profile reference; uses demo profile by default in MVP.
Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits itself. It mentions 'user-authorized' but fails to mention the demo mode default (useDemo=true) or that real data requires setting useDemo=false. This omission is significant because it could mislead an agent into thinking real LinkedIn data is always returned.

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 a single, well-structured sentence that front-loads the action and resource. It lists relevant content types without unnecessary detail or verbosity, making it efficiently concise.

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

Completeness2/5

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

While the tool has only 2 parameters and no output schema, the description omits the crucial demo-mode behavior and does not explain potential failures (e.g., lack of authorization). The 'user-authorized' claim conflicts with the default demo behavior, leaving a significant gap for an AI agent to select and invoke the tool correctly.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema fully explains both parameters (useDemo and profileRef). The description does add context about the output contents but does not elaborate on parameter meanings or edge cases, so it aligns with the baseline of 3.

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 the tool returns a LinkedIn profile snapshot with specific content areas (skills, roles, education, certifications, projects). It uses a strong verb+resource structure and is distinct from sibling tools that analyze or compare data.

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?

No guidance is provided on when to use this tool versus siblings like analyze_evidence_profile or compare_profile_and_repository_skills. The description does not mention alternatives or exclusions, leaving usage context implied at best.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Godofdeath1709/pathpilot-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server