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LinkedIn Person Profile

linkedin_person_details
Read-only

Get a LinkedIn person's profile by profile URL, public slug or member URN. Returns name, headline, about, location, follower and connection counts, open-to-work status, and the experience, education, skills, certifications, languages, honors, publications, volunteering and projects sections. Use linkedin_person_posts for their posts. Billed $0.006 per request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesLinkedIn profile URL, public slug (e.g. reidhoffman), or member URN (ACoAA...)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=true), so the bar is lower. The description still adds real operational context: the billing rate ($0.006 per request) and a full enumeration of returned profile sections, which tells the agent what to expect without an output schema.

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?

Two tightly packed sentences: the return contents are front-loaded, the sibling routing and pricing follow. Every clause carries information and nothing is wasted.

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

Completeness5/5

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

No output schema exists, yet the description inventories the returned fields thoroughly, names the alternative for posts, and discloses per-request cost. For a single-parameter read tool, an agent has everything needed to call it and interpret the result.

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?

With one parameter and 100% schema description coverage, the schema already documents that url accepts a profile URL, public slug, or member URN. The description repeats those accepted identifier forms without adding syntax examples, validation rules, or fallback behavior, so baseline 3 applies.

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?

States a specific verb (Get) and resource (a LinkedIn person's profile) and enumerates the returned sections, so the agent knows exactly what this returns versus sibling tools like linkedin_company_details or linkedin_job_details. It is clearly distinguishable from linkedin_person_posts, which it names explicitly.

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?

Directs the agent to linkedin_person_posts for a person's posts, which is a useful exclusion among many LinkedIn siblings. However, it gives no guidance on when to reach for this versus search_linkedin or search_linkedin_companies, so the routing is only partially covered.

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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