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

With no annotations provided, the description carries the full behavioral disclosure burden. It usefully discloses the data source ('OpenStreetMap open data') and the credit cost ('$1.00 per 1,000 businesses'), which are genuinely helpful operational facts. However, it does not describe response shape, pagination, credit deduction timing, or any other runtime behavior beyond it being a lookup.

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 only two sentences with no filler. The primary purpose is front-loaded, and the second sentence adds two distinct, valuable facts (data source and pricing). Every clause earns its place.

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 straightforward lookup tool with a fully documented parameter schema, the description covers the essential purpose, output content, data source, and cost. It lacks an explicit statement of return format, but that is largely inferable from 'with website, phone and address.' Given the absence of an output schema, slightly more detail about result structure would make it fully 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 description coverage is 100%, so the baseline is 3. The description's mention of 'town and trade' maps directly to the location and categories parameters, and the output fields echo what the search returns, but it adds no substantive parameter semantics beyond what the schema already documents.

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 states a specific action ('Find businesses'), the core filters ('by town and trade'), and the returned data ('website, phone and address'). It also gives concrete category examples, making the tool's purpose unmistakable and distinct from sibling lead tools like leads_find_contacts or leads_verify_domains.

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 implies when to use the tool (when you need local businesses by trade) but provides no explicit guidance about alternatives or exclusions. It does not mention that leads_find_contacts might be more appropriate for finding individual contacts, or that leads_verify_domains handles domain verification. The usage context is clear only by inference.

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