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

Annotations already declare readOnly/openWorld=false, so safety is covered; the description adds real substance on top: the exact thresholds used (3x usual time-to-close, 30-day repost window), that examples are named and filtered on stated pay topping $60K, and the free-tier boundary against the paid row-level API. It omits any mention of rate limits, auth, or coverage/lag of the underlying careers-site crawl.

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 and free of filler, but the first sentence is a long clause-heavy run-on ("how many live roles have been open at least 3x longer than that same employer usually takes to close a role (stuck)") that takes effort to parse. Little waste, but the structure could be broken up without losing content.

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 3-parameter read tool with no output schema and annotations covering the safety profile, the description covers source, metrics, thresholds, filtering scope, and the free-vs-paid split well. Gaps are secondary: no indication of data recency, result size, or what fields the named examples carry.

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 baseline is 3. The description does add one genuine constraint the schema does not state: results are "nationally or for one state and one industry," implying a single state and single industry per call rather than a list. The min_pay filter and the $60K example-pay floor are related but the description does not clarify how they interact.

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 resource and metric pair: counts of roles open 3x longer than the employer's usual close time (stuck) and roles reposted in the last 30 days, sourced from employers' careers sites. An agent can tell this is a labor-market signal tool, not a job search. It never differentiates itself from siblings like hiring_market or job_openings_index, so the boundary is only implied by the metric definitions.

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?

Names an audience ("recruiter or staffing firm") and implies a use case (finding roles that aren't filling), and states that free counts/examples are returned while the row-level list comes from the separate Hiring Signals API. It gives no explicit when-to-use versus hiring_market, job_openings_index, or compare_job_posting, and no exclusions.

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