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

Annotations already cover readOnly, idempotent, open-world, and non-destructive traits, so the bar is lower. The description adds genuinely new operational context: a free daily allowance followed by $0.0005 USDC per call via x402, which is exactly the kind of cost/rate information annotations cannot express.

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?

Two tight sentences with the resource scope front-loaded and the pricing caveat second. No filler; each 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?

An output schema exists, so return values need not be described, and the description still previews the returned fields. Scope, filter, and cost model are covered; the only gap is explicit routing relative to the many per-dataset siblings.

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?

With a single parameter at 100% schema description coverage, the schema already documents 'q' with an example. The description's 'optional text filter' restates this without adding format or matching semantics (e.g. substring vs exact), so the baseline 3 applies.

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 (every planning.data.gov.uk dataset) and enumerates the fields returned (name, typology, entity count, licence), making clear it is a catalog/index tool. It distinguishes itself reasonably from the per-dataset siblings (e.g. uk-planning__ancient-woodland) by scope, but never explicitly frames itself as the discovery entry point for those tools.

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 scope word 'Every ... dataset' implies this is the enumeration/discovery tool, and the mention of an 'optional text filter' hints at narrowing large result sets. However, there is no explicit when-to-use versus the per-dataset siblings or uk-planning__entity, and no exclusion guidance.

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