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BACH-AI-Tools

LinkedIn Data API MCP Server

get_job_details

Fetches comprehensive LinkedIn job details, including required skills and company information. Provide a job ID to retrieve full data.

Instructions

Get the full job details, including the job skills and the company information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesExample value: 40909940544090994054
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only describes a read operation but omits important details like authentication requirements, rate limits, or potential large payloads. The description is minimal and lacks transparency.

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 concise sentence without wasted words. It could be slightly improved by structuring the output components separately, but overall it is efficient.

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?

Given the simple input (one required parameter) and no output schema, the description adequately states what the tool returns (job details, skills, company info). However, it lacks specificity about the output structure or potential constraints, leaving some ambiguity.

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 one parameter ('id') described only by an example value. The tool's description mentions the output (skills, company info) but adds no extra meaning to the parameter beyond what the schema provides. Baseline 3 is appropriate.

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 verb 'Get' and the resource 'full job details', and specifies that it includes job skills and company information. This distinguishes it from sibling tools like 'get_company_jobs' or 'search_jobs', though it could be more explicit.

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?

The description provides no guidance on when to use this tool versus alternatives such as 'search_jobs', 'get_company_jobs', or 'get_company_details'. It assumes the agent already has a job ID and gives no context about prerequisites or excluded use cases.

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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