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

No annotations exist, so the description carries the full burden. It usefully discloses that the result is an approximation rather than an exact figure, and the 'PRO.' marker hints at a subscription gate. It says nothing about output shape, precision limits, or what happens with out-of-range salaries or unknown postcodes.

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?

A single front-loaded sentence framed as the question it answers, with the key qualifier 'approximate percentile' up front. No filler, no restatement of the tool name beyond the tier marker.

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 5-parameter, unannotated tool with no output schema, the description leaves gaps: it does not say what the response looks like (a percentile value, a band, a range), nor explain the subscription/token prerequisite beyond 'PRO.' The core intent is conveyed, but not everything needed to call and interpret it confidently.

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 60%: measure, pattern, and access_token are documented in the schema, but the two required parameters (postcode, salary) have no descriptions. The description implicitly ties salary to 'local pay distribution' and postcode to locality, which partially compensates, but adds no format or unit details for either.

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 states a specific computation: locating a given salary within the local pay distribution for a postcode, returning an approximate percentile. That is a clear verb-and-resource combination an agent can act on. It does not, however, distinguish itself from siblings like salary_percentiles or area_salary, leaving the agent to infer the difference.

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?

Usage is only implied by the question phrasing: it fits evaluating a concrete offer (salary + postcode). There is no explicit when-to-use, no when-not-to-use, and no pointer to salary_percentiles or area_salary for alternative needs. The 'PRO.' prefix signals a paid tier but offers no routing guidance.

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