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get_job_details

Fetch full job details from any LinkedIn job listing URL, including description, requirements, and company info.

Instructions

Fetch full details for a specific LinkedIn job listing URL.

Args: url: Full LinkedIn job URL (e.g. https://www.linkedin.com/jobs/view/1234567890).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only describes the fetch operation and does not mention authentication requirements, failure modes, rate limits, or what 'full details' includes.

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 short and front-loaded, with no filler. The core action comes first, and the single parameter is explained in one clear line.

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?

This is a simple one-parameter tool and the URL format is fully documented, so it is minimally viable for invocation. However, with no annotations and no output schema, an agent receives no information about required session state or the returned structure, which is a notable gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the schema only labels the parameter as 'Url', so the description fully compensates by defining the expected value as a full LinkedIn job URL and providing a concrete example format.

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 states a specific action ('Fetch full details') and a precise resource ('specific LinkedIn job listing URL'), clearly distinguishing it from sibling tools like search_jobs or easy_apply. The concrete URL example further anchors what the tool operates on.

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 is given about when to choose this tool over alternatives such as search_jobs. The URL requirement implies a use case, but the description does not state selection criteria, prerequisites, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.