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

Goes well past the read-only/idempotent annotations: it discloses the daily-register provenance, the exclusion of personal licences held by individuals, the cost (1 credit/call), and the unauthenticated rate limit (5-row preview, 20 calls/day). That is exactly the operational context an agent needs before invoking.

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 resource and scope, then record granularity, then provenance and cost. Dense but no filler; the two long sentences are information-heavy rather than padded.

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 usefully enumerates the return columns and the per-record_type keying, and it documents access limits. The remaining gap is parameter semantics, which is significant given 21 undocumented fields, but the coverage model is otherwise solid.

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% across 21 parameters, so the description must carry the load. It only explains q (searches all text fields) and that filters AND together; the meaning of city, postcode, outward_code, local_authority, licence_type, status, activities and the four date-bound params is left entirely unstated.

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 (Gambling Commission operating licences for Great Britain) and enumerates the covered licence categories, activities, dates and trading names. An agent can immediately distinguish this from sibling query_uk_* datasets such as query_uk_companies or query_uk_charities.

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?

"Filters combine with AND; q searches all text fields" tells the agent how to drive the query, and the credit/preview note signals the cost model of calling it. It stops short of explicit when-to-use-vs-alternative routing, though the dataset boundary makes that largely self-evident.

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