Read LinkedIn Job

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds useful context about 'current visible' (implying hidden/inactive jobs may not be retrievable) and what is included in the response. However, it does not disclose error behavior or authorization requirements beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the core action ('Read one current visible LinkedIn job by numeric ID') and continues with a clear list of what is included. Every phrase earns its place with no redundant or vague wording.

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

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

The tool is simple with a rich output schema and strong annotations, so the description does not need to explain return values in detail. It covers the main data components and the visibility constraint, but the lack of context_id/request_id explanation is a notable gap. Given the required nature of these parameters, a more complete description would address them.

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

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

The schema has 0% description coverage, so the description carries full responsibility for explaining parameters. It explains that job_id is a numeric ID, but context_id and request_id are completely unexplained. The description fails to clarify their purpose, leaving a significant semantic gap for the agent.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool reads a specific LinkedIn job by numeric ID, and enumerates exactly what is included (header metadata, application method, hiring-team identities, About section). This distinguishes it from sibling search tools like linkedin.jobs.search, which find jobs rather than fetch one by ID.

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

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

The description implies usage when you have a numeric job ID and need detailed job information, but it does not explicitly contrast with siblings like linkedin.jobs.search or state when NOT to use this tool. There is no mention of alternatives or exclusions, leaving the agent to infer the right context.

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