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

Annotations cover readOnly and openWorld, so the safety profile is already set. The description adds genuinely useful behavioral context beyond annotations: the cost model (1 credit per 10 records, minimum 1) and the data freshness/scope ('live postings'). Return format and pagination behavior are left to the output schema.

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?

Three tight sentences, front-loaded with purpose, then filterable dimensions, then cost and the recommended sizing workflow. Every sentence earns its place with no redundancy.

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?

For a 19-param search tool with an output schema and full schema coverage, the description covers purpose, filter dimensions, cost, and the facets workflow. An agent has what it needs to call it correctly; only sibling differentiation (nearby/companies) is thin.

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 19 parameters thoroughly. The description lists a subset of filters (title, company, location, department, remote, provider, job family) but adds no syntax or semantics beyond what the schema provides, so baseline 3 applies.

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?

States a specific verb (Search) and resource (jobs dataset / live postings) with clear scope (crawled from every discovered company ATS board). It distinguishes itself from the facets sibling but does not clarify how it differs from nearby siblings like datasets_jobs_nearby or datasets_jobs_companies.

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?

Gives an explicit workflow recommendation: 'use datasets_jobs_facets to size a query first,' which names the alternative and the condition for using it. There is no explicit when-not guidance, but the context is clear enough for an agent.

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