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

Annotations are sparse (only openWorldHint), so the description carries the transparency burden. It discloses important behavioral context: the query is limited to public opinion/safety perception, excludes physical monitoring and POI details, and describes the pricing model (per data unit, credits, capped by request). This adds meaningful business and scope behavior beyond the minimal annotation.

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 concise and front-loaded: the first sentence explains what the tool does, followed by coverage, exclusions, and a typical question. The additional pricing block is slightly long but still directly useful for an agent to assess cost behavior. No 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?

Given the full input schema, output schema, and the annotation openWorldHint, the description is quite complete. It covers purpose, scope, exclusions, typical queries, and pricing, which is sufficient for an agent to select and initialize the tool. Minor ambiguity remains in '請用生态环境' not exactly matching a sibling ID.

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% and all three parameters include detailed descriptions in the schema, so the description need not repeat them. The main description adds no extra parameter-level semantics, thus the baseline 3 is appropriate per the rubric.

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 purpose: '查询地区舆情与安全感知宏观指标' (query macro public opinion and safety perception indicators), lists the exact coverage areas, and provides typical questions. It also differentiates itself from siblings by explicitly excluding environmental physical monitoring and POI details.

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 tells users when NOT to use the tool: '空气质量等请用生态环境' and '不含...POI 明细', directly pointing to alternative tool categories. It also provides typical question phrasing to help select correct intent. However, it does not name the exact sibling tool IDs (e.g., gov_data_environment), only a coarse name, so a slight gap.

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