SupplyGraph.AI Data

Enterprise Change Reputation Favorability

enterprise_change_reputation_favorability

基于具体企业名称，按企业查询声誉品牌方面的周期变化，用于查询获奖情况与媒体研报社交非负面口碑占比。不用于媒体报道量、平台热度等知名度指标。涉及指标/类型：企业获奖数量（不同等级）；媒体舆情健康度（非负面占比）；机构研报评价口碑（非负面占比）；网络社交平台口碑（非负面占比）不包含：非本分类指标；按园区/产业链批量筛企业名单典型问法：中国比亚迪股份有限公司企业获奖数量（不同等级）；美国Tesla, Inc.媒体舆情健康度（非负面占比）；日本丰田自动车株式会社机构研报评价口碑（非负面占比）

Pricing: {"unit": "credits", "billing_model": "per_run", "per_run": 40, "unit_description": "optional"}

Input Schema

TableJSON Schema

Name	Required	Description	Default
`company_name`	Yes	企业名称，如「比亚迪股份有限公司」「Tesla, Inc.」。
`country_name`	Yes	国家名称，如「中国」「美国」「Japan」「China」。

Output Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes	Text or Markdown response generated by the agent. Returned for completed results as well as in-progress, failed, cancelled, or waiting-user messages.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedAug 19, 2026

TDQS

A4/5.0

Behavior3/5

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

注释仅提供openWorldHint，描述说明查询的是“周期变化”但未明确返回格式、分页或权限要求。虽然有输出schema补充，但描述本身对行为细节披露有限，未与注释矛盾。

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

Conciseness5/5

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

描述结构清晰，采用分点列出包含指标、不包含项和典型问法，首句直接点明功能，无冗余，符合最佳实践。

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，描述无需解释返回，但工具涉及多种指标，描述已具体列举，并提供典型问法，足以支持正确使用，完整度良好。

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覆盖100%，参数company_name和country_name在schema中已有描述，描述中提供了示例值但没有额外解释参数语义，基线3分，未显著增补。

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?

描述明确指定了动词“查询”和资源“企业声誉品牌周期变化”，并列举了具体指标（获奖数量、媒体舆情健康度等），与兄弟工具如enterprise_change_reputation_awareness等清楚区分，且说明了不包含的内容。

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?

明确说明使用场景（按企业查询声誉品牌周期变化）和不适用场景（媒体报道量、平台热度），并提供了典型问法，但未直接列举替代工具，不过通过不包含项间接区分了其他工具。

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

B3.2/5.0

Disambiguation4/5

Most tools have clearly distinct purposes, with consistent scopes (e.g., chain_* vs park_* vs company_* vs gov_data_*). The list/num pairs are clearly differentiated. A few overlapping concepts exist (e.g., company_patent vs enterprise_change_innovation) but descriptions clarify the angle. Some typos (company_randomin_spection) don't cause ambiguity.

Naming Consistency4/5

Naming follows a mostly predictable snake_case pattern with prefixes indicating domain (chain_, park_, company_, enterprise_change_, gov_data_, poi_data_, business_surrounding_, cbd_surrounding_). Most tools use <prefix>_<entity>_<action> or <prefix>_<subject>. A few outliers (sg_chokepoint, tariff_calc, corporate_exception_report) deviate but are few and recognizable.

Tool Count1/5

With 198 tools, this is far beyond any reasonable scope for a single server. It exceeds even the 'extreme mismatch' threshold of 50+ tools. The large number makes selection and discoverability challenging, despite good internal organization.

Completeness4/5

The tool surface covers a vast range of enterprise data, regional macro stats, POI details, supply chain analysis, and tariffs. It appears to cover the primary domain comprehensively, with only minor potential gaps (e.g., no direct tool for company debt ratings or specific product catalogs, but these are addressed via enterprise_change_* and company_* tools).

Resources

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