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LinkedIn Sales & Navigator MCP Server

by adityaidev

get_profile_details

Retrieve comprehensive LinkedIn profile data including work experience, education history, and professional skills using a public identifier.

Instructions

Get detailed profile information including experience, education, and skills

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
public_identifierYesThe LinkedIn public identifier / vanity URL slug
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states it's a read operation ('Get'), but lacks behavioral details like authentication requirements, rate limits, data freshness, or error conditions. For a tool accessing external data without annotation coverage, this is a significant gap.

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?

Single sentence, front-loaded with the core action, efficiently lists included data types without redundancy. Every word earns its place, making it easy to scan and understand quickly.

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?

For a tool with no annotations, no output schema, and multiple sibling tools, the description is incomplete. It doesn't clarify scope (e.g., whether it returns all profile sections or a subset), differentiate from similar tools, or address behavioral aspects like permissions or limitations, leaving gaps for an AI agent.

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%, with the single parameter 'public_identifier' documented as 'The LinkedIn public identifier / vanity URL slug'. The description adds no additional parameter context beyond implying it fetches LinkedIn profiles, which is already inferred from the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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 verb 'Get' and the resource 'detailed profile information', specifying the included data types (experience, education, skills). It distinguishes from generic 'get_profile' by emphasizing detail level, though doesn't explicitly contrast with siblings like 'get_profile_experience' or 'get_profile_skills'.

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 on when to use this tool versus alternatives like 'get_profile' (likely basic info), 'get_profile_experience' (specific section), or 'get_own_profile' (self-access). The description implies comprehensive details but doesn't specify prerequisites 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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