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dzigi00

LinkedIn Automation MCP Server

by dzigi00

Get Job Details

get_job_details
Read-only

Retrieve LinkedIn job posting details by job ID. Access role, company, location, and description to evaluate opportunities.

Instructions

Get job details for a specific job posting on LinkedIn.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesLinkedIn job ID (e.g., "4252026496", "3856789012")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

Annotations already declare readOnlyHint: true and openWorldHint: true, covering the safety profile. The description adds no extra behavioral context such as response details, rate limits, or access requirements—it simply restates the tool's action. It is consistent with annotations but does not go beyond them.

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, front-loaded sentence that directly states the tool's purpose. It contains no fluff, redundancy, or irrelevant details, making it an efficient and well-structured summary.

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 tool's simplicity (one well-documented parameter), existing annotations, and an output schema, the description is mostly complete for a read-only lookup. It does not explicitly mention any edge cases, access constraints, or how it relates to search_jobs, but these are not critical for basic use. Slight ambiguity in what 'job details' entails is mitigated by the output schema.

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 coverage is 100% with the job_id parameter fully documented, including examples. The description adds no additional parameter-level meaning, so the baseline score of 3 applies per the rubric for high schema coverage.

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 uses the specific verb 'Get' and clearly identifies the resource as 'job details for a specific job posting on LinkedIn'. This is distinct from broader search tools like search_jobs, establishing a clear purpose without ambiguity.

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

Usage Guidelines3/5

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

The description implies usage when a specific job_id is known but provides no explicit guidance on when to prefer this tool over siblings like search_jobs, nor does it mention any prerequisites or alternatives. The context is implied by the name and single parameter, but not explicitly stated.

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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