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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, so the safety profile is covered. The description usefully adds data provenance ('measured from employers' own careers sites'), the free-summary vs paid-full-report boundary, and the async states ('building' with retry_after_seconds, 'not_held' with market_now). It does not state rate limits, coverage gaps, or freshness beyond the retry hint.

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?

Front-loaded with the tool's purpose, and the return-state details are valuable. However, roughly forty words are spent enumerating industries and job titles, which is bulk padding that slows the agent without changing its decision; the prose is also a single run-on sentence.

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?

With no output schema, the description carries the return-value burden and does so: pay range in market, count of employers hiring, competitor detail in the full report, and the 'building'/'not_held' status payloads with retry_after_seconds. Only minor gaps remain, such as geography of the benchmark (mentioned as 'within 25 miles' only in the building case) and any pagination or size limits.

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 only 50% (city, title, employer are undocumented), but the description compensates by explaining identification strategies: job_url (careers-site link or veritahire.com/j/ link), job_id, or employer + title (+ city, state). It adds the fallback logic the schema itself does not express, going beyond the baseline for half-covered schemas.

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 the resource precisely (competitive hiring report / pay-range benchmarking for one posting) and scopes it to US postings that are 'not filling.' It distinguishes itself from the sibling request_full_report by labeling itself the 'free summary' and describing what the full report adds. The verb is implicit (it is a read/report tool) and the long industry/occupation enumeration dilutes the headline, keeping it from a 5.

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 a clear usage condition ('for ... a job posting that is not filling') and points at the alternative path (request_full_report for the full paid report, first one free). It does not address when an agent should prefer get_job or search_live_jobs instead, so exclusions are missing.

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