SupplyGraph.AI Data

Enterprise Change Competitor Moves

enterprise_change_competitor_moves

基于具体企业名称，按企业查询市场竞争方面的周期变化，用于查询竞争对手在补贴处罚、渠道、新品、技术与定价上的动向。不用于查询本企业自身产品或经营指标。涉及指标/类型：竞争对手是否获得政府补贴或受到处罚；竞争对手是否拓展了新的销售渠道；竞争对手是否有新产品发布；竞争对手是否有新的技术进展；竞争对手是否调整了产品或服务的价格不包含：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竞争对手是否获得政府补贴或受到处罚；美国Tesla, Inc.竞争对手是否拓展了新的销售渠道；日本丰田自动车株式会社竞争对手是否有新产品发布

Pricing: {"unit": "credits", "billing_model": "per_run", "per_run": 50, "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

A3.9/5.0

Behavior4/5

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

Annotations provide only openWorldHint=true, which the description complements by detailing the types of competitor movements covered (subsidies/penalties, channels, new products, tech, pricing) and explicitly excluding non-classified indicators. This goes beyond the annotation to set expectations about the tool's scope. It does not disclose hypothetical retry behavior, but the description adds meaningful behavioral scope context that is not redundant with annotations.

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?

The description is moderately sized, with a clear opening statement, a bullet-like list of covered indicators, an exclusions section, and examples. It fronts the purpose first and keeps exclusions concise. The pricing block is informational, not the core description. It is appropriately structured and not wasteful, though the metric list could be condensed.

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?

Given the tool's complexity: it involves multiple metric categories, and it has an output schema (still present in context signals) and 100% parameter coverage. The description covers the metrics, exclusions, and typical queries, making it complete for selection and basic invocation. It does not specify return structure or pagination, but the presence of an output schema lessens that burden. The description is adequate for an agent to decide and call.

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?

Schema description coverage is 100%: both parameters (company_name and country_name) have descriptive type and format info in the schema, with examples like '比亚迪股份有限公司' and '中国'. The description reinforces the company focus (specific enterprise name) but adds little beyond the schema's inherent semantics, like requesting exact formats or handling of aliases. It earns a baseline 3 given the schema fully covers the parameters.

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

Purpose4/5

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

The description clearly identifies the tool as specific to querying competitor dynamics (subsidies/penalties, channels, new products, technology, pricing) for a given enterprise name. It specifies the verb 'query' and the resource (competitor market changes), and the scope is clearly delimited to competitors excluding the own enterprise. Although it doesn't explicitly contrast with sibling tools like enterprise_change_business_strategy or company_competing, the scope statement sufficiently distinguishes its purpose for competitor-focused market changes.

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?

The description provides explicit scope boundaries: it is for competitor market changes, not for the company's own products or operational metrics, and it excludes aggregated listings by park/industry chain like enterprise_change_external_policy or chain_company_list. It also includes typical example queries with country/company names to illustrate usage. It stops short of explicitly naming alternative tools, but the boundaries are clear.

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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