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

With no annotations provided, the description fully carries the burden. It discloses data source, what fields are included, what is dropped (operator comments) and not served (rating artwork), refresh cadence, and cost per call. It also clarifies the stable key (FHRSID), giving agents a clear behavioral model.

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?

The description is a single dense paragraph but remains readable and front-loaded with the core purpose. It packs many details without excessive verbosity. Slight room for improvement in breaking up the field list, but it is efficiently structured.

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?

Given the complexity (20 parameters, no output schema, no annotations), the description provides a solid overview but misses parameter-specific semantics, pagination usage, and the exact response structure. It does not explain how page/per_page work or what the returned object looks like beyond a field list. For a tool this complex, more detail is needed for safe invocation.

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 description coverage is 0%, so the description must explain parameter semantics, but it only mentions 'q' (searches all text fields) and that filters combine with AND. The other 19 parameters (postcode, scheme_type, rating_value, hygiene_score_min/max, etc.) are not individually explained, leaving agents to infer their meaning from names alone. This is a significant gap for a high-parameter tool.

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 clearly identifies the tool as a query for UK food hygiene ratings from the FSA, listing the specific data fields and the scheme's geographic scope. It distinguishes itself from sibling tools that cover other UK datasets (companies, tenders, etc.) by naming the exact domain.

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 explains filter behavior ('Filters combine with AND; q searches all text fields') and notes the daily refresh, which sets expectations for freshness. However, it does not explicitly contrast with sibling tools or state when to choose this over others, though the domain is unambiguous.

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