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maykonlong

LinkedIn MCP Server

by maykonlong

linkedin_search_jobs

Search LinkedIn job vacancies using keywords and location filters to discover relevant employment opportunities.

Instructions

Pesquisa vagas de emprego no LinkedIn por palavras-chave e localização.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsYesPalavras-chave da busca de vaga (ex: "Desenvolvedor Node.js")
locationNoLocalização (opcional, padrão "Brasil")
Behavior2/5

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

No annotations are provided, so the description must carry the behavioral transparency burden. It only restates the search purpose and does not disclose the return format, pagination, authentication needs, or any side effects. The read-only nature is implied by 'pesquisa' but not explicitly confirmed.

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 a single, concise sentence that front-loads the action and resource. No wasted words, and it is perfectly sized for the tool's simplicity.

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?

Given the simple tool (2 parameters, no output schema), the description is largely complete. It states the purpose and maps to the parameters. It could mention the return type, but that is not required for a straightforward search operation.

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?

The schema provides full descriptions for both parameters (keywords and location with default 'Brasil'). The description mentions keywords and location, but adds no new semantics beyond what the schema already documents, so a 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?

The description clearly states 'Pesquisa vagas de emprego no LinkedIn' (searches LinkedIn job postings), with a specific verb (search), resource (jobs), and parameters (keywords and location). It distinguishes from sibling tools, which are all about profile updates and content publishing.

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?

Usage is clearly implied: this is the only search tool among siblings, so a user would know to use it for finding jobs. However, there is no explicit 'use when' statement or mention of alternatives, which would make it fully explicit.

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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