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selvin-paul-raj

LinkedIn MCP Server

get_recommended_jobs

Retrieve personalized job recommendations from LinkedIn to find relevant opportunities.

Instructions

Get your personalized recommended jobs from LinkedIn

Returns: List[Dict[str, Any]]: List of recommended jobs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations provided, so description must disclose behavior. It only mentions the action and return type, omitting any side effects, authentication needs, or rate limits. Minimal compared to the burden.

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?

Extremely concise (one line plus return type). No wasted words, but could benefit from a brief sentence on usage context.

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

Completeness3/5

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

Sufficient for a zero-parameter tool with output schema, but lacks any behavioral or usage context (e.g., what 'recommended' means, if results are sorted). Adequate but could be more helpful.

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?

Input schema has zero parameters, so baseline is 4. Description does not need to add parameter info; it correctly notes return type which is partially redundant with output schema but acceptable.

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?

Clearly states it retrieves personalized recommended jobs from LinkedIn, but does not explicitly differentiate from siblings like search_jobs, which could also be personalized. The verb 'get' and resource 'recommended jobs' are specific.

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 (e.g., search_jobs, get_job_details). The description only states what it does without context for selection.

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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