search_jobs

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 describes the return format (job_ids) and mentions pagination behavior ('Maximum number of result pages to load'), which is valuable context. However, it doesn't disclose important behavioral aspects like rate limits, authentication requirements, or whether this is a read-only operation, leaving significant gaps for a tool with 9 parameters.

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 well-structured with a clear purpose statement, usage guidance, and organized parameter documentation. While appropriately sized for a tool with 9 parameters, the parameter explanations could be slightly more concise, but overall the structure is logical and front-loaded with the most important information.

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?

Given the complexity (9 parameters, no annotations, but with output schema), the description is mostly complete. It explains the purpose, usage workflow, and all parameters thoroughly. The existence of an output schema means the description doesn't need to explain return values, but it could better address behavioral aspects like authentication or rate limits for a LinkedIn search 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?

With 0% schema description coverage, the description fully compensates by providing comprehensive parameter documentation. Each of the 9 parameters is clearly explained with examples and valid values, including defaults for max_pages and easy_apply, and format guidance for comma-separated filters. This adds substantial meaning beyond what the bare schema provides.

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's purpose with specific verb ('Search for jobs') and resource ('on LinkedIn'), and distinguishes it from sibling tools by mentioning that it returns job_ids for use with get_job_details. This explicitly differentiates it from search_people and other sibling tools.

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 provides explicit guidance on when to use this tool versus alternatives by stating 'Returns job_ids that can be passed to get_job_details for full info,' which clearly indicates the relationship between search_jobs and get_job_details. This gives the agent clear direction on the workflow between these tools.

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