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

With no annotations, the description carries the full burden; it does disclose the returned statistics (10th-90th percentile, mean, median) and that results are scoped to a postcode area. It says nothing about read-only semantics, pricing/access-tier implications beyond 'PRO', rate limits, or error behavior for an invalid postcode.

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 that packs the tier marker and the returned metrics efficiently. It is terse but every clause carries information.

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 6-parameter data-query tool with no annotations and no output schema, the description covers the returned metrics and dimensions but omits the auth/token prerequisite and any hint of output shape. Adequate, not complete.

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 67%, above the 50% threshold, so the schema largely documents the parameters. The description echoes the dimension names (pattern, measure, sex, basis) but adds no format detail beyond what the schema already says; access_token semantics live only in the schema.

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 (percentile + mean/median pay for a postcode's area) with the breakdown dimensions, so an agent knows exactly what data it returns. The 'PRO' prefix signals a paid-tier endpoint. It does not, however, distinguish itself from siblings like area_salary or compare_areas.

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 gives no when-to-use guidance, no exclusions, and never names area_salary, compare_areas, or offer_check as alternatives. Usage is only implied by the data it returns.

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