search_jobs

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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions the output format ('structured, LLM-ready Markdown report') and time filtering ('hours_old'), but lacks details on rate limits, authentication needs, data sources, pagination, error handling, or what 'latest' means operationally. This leaves significant gaps for a tool with 5 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 appropriately sized and front-loaded, starting with the core purpose. The 'Args:' section is well-structured but slightly verbose; every sentence adds value, though it could be more streamlined. No redundant information is present, making it efficient for understanding.

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 5 parameters with 0% schema coverage and no annotations, the description does a fair job explaining inputs and output format. However, it lacks details on behavioral aspects like rate limits or error handling. The presence of an output schema means return values don't need explanation, but overall completeness is adequate with clear gaps.

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 description coverage is 0%, so the description must compensate. It adds meaning by explaining each parameter's purpose with examples (e.g., 'job_titles: The roles you are looking for'), default values, and constraints (e.g., 'max_results: 1-10', 'hours_old: default 48, max 168'). This clarifies semantics beyond the bare schema, though it doesn't cover all nuances like format specifics.

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 for 'latest jobs and internships' and returns them as a 'structured, LLM-ready Markdown report.' It specifies the verb (search), resource (jobs/internships), and output format. However, with no sibling tools mentioned, there's no opportunity to differentiate from alternatives, preventing a perfect score.

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 no guidance on when to use this tool versus other methods or tools. It mentions supporting 'multiple titles and locations' but doesn't specify prerequisites, exclusions, or alternative approaches. Without siblings, it could implicitly be the go-to for job searches, but explicit usage context is missing.

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