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query_gov_environment_index

gov_data_environment

查询地区生态环境宏观指标。覆盖:空气质量(AQI/PM)、优良天数、地表水等级、环保治理相关统计。不含舆情热度(请用舆情主题)或 POI 明细。典型问法:某区空气质量优良天数比例、PM2.5、空气质量最好的城市。

Pricing: {"unit": "credits", "billing_model": "per_data_unit", "meter": {"credits_per_unit": 1, "unit_description": "One data unit = one region × one indicator × one date version (example: Chengdu × permanent population × 2023). Charged by returned units after query, capped by the user request."}}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
versionsNo可选期望年份/日期软约束,如 ['2022'] 或 ['2022-12-01'];取数以库内真实版本为准,不一致时标注 version_mismatch。
gov_namesNo可选地区名列表。point/compare:目标地区;rank/list/filter:父级范围(如 ['四川省']/'成都市');peer_rank:目标地区(可另附上级);不传时尝试从 input_text 抽取。
input_textYes用户查询文本,描述「空气质量水质等环境指标」指标意图;支持点查、TOP/排名、多地对比、下级列表、阈值筛选、同级位次等。示例:武侯区空气质量优良天数比例

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A3.9/5.0
Behavior3/5

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

注解仅openWorldHint:true,描述补充了版本不一致时的标注行为(version_mismatch)和定价信息,但未说明读取权限、返回结构等。由于输出schema存在且描述有限,部分行为需依赖schema推断。

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

描述简洁,前两句清晰覆盖范围和典型问法,定价部分虽长但属必要信息,整体结构合理,无冗余。

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

有输出schema,描述已说明覆盖范围、排除项、版本标注,并提供典型问法,足以支持agent选择调用。售价信息可能额外消耗注意力,但不影响完整性。

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

输入schema对每个参数(versions, gov_names, input_text)提供了详细描述,覆盖率达100%,描述本身未额外补充参数语义,仅依赖schema即可满足需求,符合基线3。

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

明确声明查询地区生态环境宏观指标,列举覆盖范围(空气质量、优良天数、地表水等级、环保治理统计),并排除舆情和POI,清晰区分了兄弟工具(如gov_data_public_opinion, gov_data_poi_amenity)。动词'查询'与资源直接对应。

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

描述提供了典型问法示例,并明确指出'不含舆情热度(请用舆情主题)',给出了排除和替代方向。虽然未与其他gov_data工具逐一对比,但已足够指导使用场景。

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

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TDQS

B3/5.0
Disambiguation2/5

大量工具功能高度重叠,例如chain_*和park_*系列均为按不同筛选条件查询企业列表或数量,只是参数不同却拆分为独立工具;enterprise_change_*系列同样针对不同指标逐一拆分。虽然描述清楚各自区别,但代理面对198个工具时极易选错,且许多工具本质应合并为带参数的单一接口。

Naming Consistency3/5

多数工具采用snake_case加领域前缀(如chain_、park_、company_、gov_data_、poi_data_),但存在明显变体如company_certlist、company_randomin_spection(拼写异常)、corporate_exception_report、due_diligence_report、sg_chokepoint等,混用英文抽象名词与动词短语,整体模式可辨认但不统一。

Tool Count1/5

工具总数高达198个,远超合理范围(即使复杂领域也应控制在25个以内)。大量工具是同一逻辑的不同参数变体(如list/num、不同资质条件),完全可以通过参数化减少数量,严重冗余,代理难以有效浏览和选择。

Completeness4/5

工具覆盖领域广泛,包括企业信息、产业链分析、园区统计、地区宏观、POI明细、供应链风险、关税计算等,基本覆盖了商业数据查询的主要需求。虽缺少更新/删除等操作(但作为查询服务器可接受),且部分细分领域可能有遗漏,但整体功能较为完整。

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