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joaovaleri

linkedin-mcp

by joaovaleri

linkedin_add_education

Add an education entry to your LinkedIn profile by specifying school, degree, field, dates, and more.

Instructions

Add an education entry to the LinkedIn profile

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldNoField of study
gradeNoGrade/GPA
degreeNoDegree type (e.g. 'Bacharelado', 'MBA')
schoolYesSchool/university name
endYearNoEnd year
startYearNoStart year
descriptionNoActivities and societies
Behavior2/5

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

No annotations exist, so the description carries full burden. It only states the action, but does not disclose any side effects, permission requirements, or behavior if the entry already exists. Basic transparency is present but insufficient for a mutation tool.

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?

The description is a single sentence, very concise. It is front-loaded with the purpose. However, it could benefit from a brief note on parameter usage without being verbose.

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?

With 7 parameters and no output schema, the description is minimal. It does not explain what the tool returns, any constraints like startYear before endYear, or the mandatory school field requirement (though schema has required). Completeness is low for a tool of this complexity.

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 already documents each parameter. The description adds no additional meaning or usage context for the parameters, meeting the baseline.

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 tool adds an education entry to the LinkedIn profile. The verb 'Add' and resource 'education entry' are specific, and it distinguishes from many sibling add_* tools. However, it does not specify that it adds to the logged-in user's profile.

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 linkedin_add_experience or linkedin_add_certification. No prerequisites or context for usage are provided.

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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