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

Annotations are minimal (only openWorldHint), so the description carries the behavioral burden. It adds value beyond annotations: indicator-coverage scope, macro-vs-POI exclusion boundary, and a detailed pricing/cost model (per_data_unit = region × indicator × date version, billed on returned units, capped by the request). No contradiction with openWorldHint; return-data behavior is reasonably delegated to the output schema.

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 front-loaded: three sentences cover the core purpose, indicator coverage, exclusions, and typical queries, followed by a structured pricing block. Every sentence earns its place; the pricing JSON is slightly verbose but operationally necessary for cost-aware tool selection.

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 moderate complexity (3 params, multiple query modes, output schema present, 150+ siblings), the description is largely complete. It differentiates well against poi_data_* and other gov_data_* tools, and the output schema covers return shape. Minor gap: the query-mode semantics (point/rank/list etc.) appear only in the schema, not the description.

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% with rich per-parameter semantics: versions documents soft-date constraint and version_mismatch behavior, gov_names explains scope semantics per query mode and extraction fallback, and input_text provides intent and an example. The description adds typical query phrasing but no meaning beyond the schema, 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 action ('查询...宏观指标') with a clear resource (regional urban facility and public service supporting macro indicators: kindergarten/medical configuration completeness, accessibility, public facility management). Explicitly distinguishes from siblings: it is not POI counts ('不是超市/医院等 POI 个数...请用兴趣点数量指标') nor store details ('请用 poi_data_*'), which is critical given the large poi_data_* sibling family.

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?

Provides explicit when-to-use guidance via typical queries ('某区幼儿园配置完备度、公共设施配套较好的城市') and explicit when-not-to-use guidance with named alternatives (兴趣点数量指标 for counts, poi_data_* for store details). The schema further adds per-query-mode semantics for gov_names (point/compare/rank/list/filter/peer_rank), so the agent has clear routing signals.

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