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

With no annotations provided, the description carries the full burden. It discloses the ordering logic (Derived from Wikipedia language coverage, rank 1 is most famous), which is a key behavioral trait. It also clarifies the filtering scope (worldwide, by country, by kind). It does not mention response format or error behavior, but the core semantics are transparent.

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 zero fluff. The first sentence delivers the core purpose and ranking logic; the second provides concrete query examples. It is front-loaded and every word 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?

Given the tool's simplicity (three optional parameters, no output schema), the description covers the essential functionality and use cases. It could mention the return format or behavior when no results are found, but the description is sufficiently complete for an AI agent to understand when and how to invoke it.

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?

The input schema already provides 100% parameter coverage with useful descriptions for kind, limit, and country. The description adds no extra parameter-level detail beyond reiterating the kinds and the optional nature (which the schema already includes). Since the schema does the heavy lifting, a baseline of 3 is appropriate.

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 returns 'the most famous places worldwide, in one country, or of one kind' with a specific ranking by Detourmap fame rank. It uses a concrete resource and distinguishes itself from sibling tools like places_near (nearby) and search_places (keyword search) by emphasizing the fame-based ordering and the three filtering dimensions.

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 frames the tool as the direct answer to specific natural-language queries like 'most famous <kind> in <country>' and 'what are the must-sees in <country>', giving strong usage context. It does not name alternatives or provide when-not-to-use guidance, but the use cases are clear enough to guide selection among siblings.

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