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

With no annotations, the description carries the burden of behavioral disclosure. It explains what the tool returns and that it supports filters, which is useful, but it does not mention pagination behavior, rate limits, authentication requirements, or how the 25-per-page limit behaves. The description is accurate but leaves some operational behavior undisclosed.

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?

Two sentences with no filler: the primary action is front-loaded, followed by return fields and filter capabilities, then a use-case signal. Every clause adds value without repetition or bloat.

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 description covers the main return fields, filter dimensions, and a practical use case, which is strong given that all parameters are fully documented in the schema. It does omit pagination details and the relationship with companion tools like linkedin_job_details or search_linkedin_companies, but the schema and sibling names partially compensate. Overall it is nearly complete for an agent selecting this tool.

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?

Schema coverage is 100%, so the schema already documents all parameter meanings and defaults. The description adds context by grouping filter types and by tying the tool to hiring/expansion/funding signals, but it does not add parameter-level detail beyond the schema. Baseline 3 is appropriate.

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 searches LinkedIn job listings by keyword, naming the specific resource and primary action. It lists return fields and filters, which makes its function obvious. It does not explicitly contrast with sibling tools like linkedin_job_details or search_linkedin_companies, so it falls short of full sibling differentiation.

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 when to use the tool: for job searches by keyword with filtering and for hiring/expansion/funding signals. It does not explicitly state when not to use it or mention alternatives such as linkedin_job_details for retrieving a specific job's details. The context is present but not fully articulated.

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