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ChimbuezeDavid

Universal LinkedIn MCP Server

add_skill

Add a skill to your LinkedIn profile securely using your authenticated account. Specify the skill name to update your profile instantly.

Instructions

Add a skill to your own LinkedIn profile.

Security Notice: Strictly locked to your authenticated account (/in/me).

Args: skill_name: The name of the skill (e.g. 'Model Context Protocol (MCP)', 'Python', 'FastAPI').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skill_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It adds a valuable security/scope constraint that goes beyond the schema, but does not mention duplicate handling, whether it overwrites existing skills, or what happens if the user is not authenticated.

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 extremely compact: one sentence for the operation, one security notice, and one parameter definition. Every part earns its place and is front-loaded appropriately.

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

Completeness4/5

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

For a simple one-parameter mutation tool with an output schema present, the description provides enough to invoke it correctly: what it does, the security scope, and the parameter format. Slightly more detail about duplicate/error behavior would be nice, but the low complexity keeps the gap minor.

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?

Schema description coverage is 0%, and the description fully compensates by naming the single parameter, explaining it as 'The name of the skill', and giving concrete examples like 'Model Context Protocol (MCP)', 'Python', and 'FastAPI'. It adds meaningful guidance beyond the raw schema's title.

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 the specific action (add), resource (skill), and target (your own LinkedIn profile). The resource clearly distinguishes it from sibling tools like add_education, add_experience, and add_project.

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?

The description provides clear context that this tool operates only on the authenticated user's own profile via the explicit 'Strictly locked to your authenticated account (/in/me)' notice. It does not explicitly name alternative tools or conditions, but the scope is clear enough to avoid misuse.

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