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Find LinkedIn from X handle

find_linkedin_from_x_handle
Read-only

The LinkedIn profile of the person behind any X (Twitter) handle, not just the user's own. Use when they give an @handle or an x.com link and ask for that person's LinkedIn, or who they are professionally. Pass context (who they likely are, e.g. 'VC at a16z') when the handle could belong to several people. confidence is out of 10; present linkedin_url as a match only when confident is true, and otherwise say it is a guess or that no match was found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
handleYesThe X handle, with or without @, or an x.com / twitter.com profile URL.
contextNoOptional hint about who the person is, to tell apart common handles.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so safety is covered. The description goes further and discloses the return surface (linkedin_url, confidence on a 0-10 scale, a confident boolean) and how to hedge when confidence is low, which is meaningful behavioral context. It omits any note on resolution failure modes or latency, so not a 5.

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?

Front-loads the core capability, then usage, then output-handling guidance, with no filler. It runs a bit long in a single breath and the output-presentation sentence overlaps with what an output schema would normally carry, but every sentence carries actionable information.

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?

With no output schema, the description is the only source explaining what comes back (linkedin_url, confidence, confident) and how to interpret it. Combined with the usage trigger and ambiguity guidance, an agent has everything needed to invoke and report 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 both parameters are already documented in the schema. The description's mention of accepted handle formats and when to supply context mainly restates the schema rather than adding syntax or format detail. Baseline 3 is appropriate.

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 and resource: resolving the LinkedIn profile of the person behind an X handle. The clause 'not just the user's own' carves it out from the sibling get_twitter_profile / get_my_tweets territory, so an agent can distinguish it without opening the schema.

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

Usage Guidelines5/5

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

Explicit trigger conditions are given ('when they give an @handle or an x.com link and ask for that person's LinkedIn, or who they are professionally'), plus a concrete rule for the optional context parameter when the handle is ambiguous. It even prescribes downstream behavior based on the confidence flag.

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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