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

Annotations already indicate readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds value by specifying the returned fields (company name, full address, contact phone, website, business category, review metrics) and the default yield ('20+ leads per query'). This goes beyond annotations, though it doesn't address potential limitations like data freshness or rate limits.

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 compact and well-structured: it leads with the core action, lists the output fields, and concludes with practical use cases. Every sentence serves a purpose and there is no redundancy or filler.

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 moderately complex tool with four parameters, no output schema, and existing annotations, the description is fairly complete. It covers the purpose, output, and use cases. It could enhance completeness by noting data source caveats or how results scale, but the current details (return fields, default 20+) provide a solid understanding.

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 100%, so the schema already fully documents all four parameters. The description merely summarizes 'business category and geography', adding little beyond the schema. The baseline for full coverage is 3, and the description doesn't elevate it with additional details or nuances.

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 the tool's function: extract B2B lead lists from Google Maps by business category and geography. It specifies the resource (Google Maps), the output (company name, address, phone, website, etc.), and the context (sales prospecting, market research, vendor lists), effectively distinguishing it from siblings like search_local_businesses and validate_emails.

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 explicitly names use cases: 'Use for sales prospecting, market research, or building vendor lists.' This provides clear context for when to use the tool, though it does not explicitly mention alternatives or exclusions. The sibling tools exist, but the description doesn't say when to prefer one over the other, so it falls short of a full 5.

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