get_new_job_ids

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. While it describes the core operation (retrieving job IDs from LinkedIn pages), it lacks important behavioral details such as authentication requirements, rate limits, error handling, pagination mechanics, or what constitutes 'new' job IDs. The description is functional but incomplete for a tool that interacts with an external service.

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 appropriately sized with three clear sections (purpose, args, returns) and front-loaded with the main functionality. The Args and Returns sections are helpful but slightly redundant with the purpose statement. Every sentence contributes value, though minor tightening is possible.

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 tool's complexity (interacting with LinkedIn, pagination, no output schema, and no annotations), the description is minimally adequate but has significant gaps. It explains what the tool does and its parameters but lacks details about authentication, rate limits, error conditions, return format specifics, or what distinguishes 'new' job IDs. The description meets basic requirements but doesn't fully address the operational context.

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 compensates well by explaining both parameters: 'url' is described as 'The URL to search for jobs in LinkedIn' and 'num_pages' as 'The number of pages to retrieve ids from'. It adds meaningful context beyond the bare schema, though it doesn't specify URL format requirements or page number constraints.

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 verbs ('gets', 'retrieved from', 'exploring') and resources ('new job ids', 'LinkedIn url', 'number of pages'). It distinguishes from siblings by focusing on job ID retrieval rather than CV adaptation, raw metadata fetching, or URL generation for job searches.

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 clear context for when to use this tool (to get job IDs from LinkedIn URLs with pagination), but doesn't explicitly state when not to use it or name specific alternatives among the sibling tools. The context is sufficient for basic usage decisions.

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