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

The description goes beyond the sparse openWorldHint annotation by disclosing list-not-count behavior, single-region constraint, category restrictions, and per-data-unit billing details. It does not mention return format, permissions, or rate limits, but the output schema covers return structure.

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 efficient and front-loaded with the core purpose, scope, and exclusions. The appended pricing block is relevant but adds density at the end; no filler sentences are present.

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?

The description covers purpose, scope coverage, negative constraints, typical questions, and billing context, while the output schema handles return values. It could name a specific sibling count tool for stronger alternatives, but the reference is sufficient.

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 documents all 4 parameters with 100% coverage, so the description does not need to add much. It reinforces single-region semantics and input_text extraction, but these are also in the schema; baseline 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?

First sentence explicitly states the action and resource: querying a detailed list of education/culture POIs within a city or district administrative scope. It also distinguishes itself from sibling POI tools by listing covered subtypes (schools, museums, libraries, science museums) and explicitly excluding count queries.

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 states when to use the tool: when there is a clear city/district name and a request for POI details. It also provides a clear exclusion—answers for counts are refused and routed to '兴趣点数量指标'—plus typical question formats to guide invocation.

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