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Enterprise Change Business Strategy

enterprise_change_business_strategy

基于具体企业名称,按企业查询经营活动方面的周期变化,用于查询战略调整、业务转型及主营构成变化等。不用于行业层面的宏观战略研究。 涉及指标/类型:公司是否发布了重大战略调整或业务转型计划;核心业务范围是否发生调整;主营业务构成是否发生重大结构性变化;公司是否发布了重大战略方向调整的公告;战略方向是否有重大变化 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公司是否发布了重大战略调整或业务转型计划;美国Tesla, Inc.核心业务范围是否发生调整;日本丰田自动车株式会社主营业务构成是否发生重大结构性变化

Pricing: {"unit": "credits", "billing_model": "per_run", "per_run": 50, "unit_description": "optional"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_nameYes企业名称,如「比亚迪股份有限公司」「Tesla, Inc.」。
country_nameYes国家名称,如「中国」「美国」「Japan」「China」。

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText 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.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Beyond the openWorldHint annotation, the description discloses that this is a query tool focused on periodic enterprise changes, lists the exact types of indicators it covers, and specifies what it does not include. It does not describe pagination or response details, but the output schema exists and the read-only '查询' intent is clear.

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 organized with a clear lead sentence, an exclusions section, an indicator list, typical questions, and pricing. It front-loads the core purpose and avoids excessive fluff, though the indicator list is somewhat redundant with the opening sentence and the pricing block adds minor noise.

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?

For a two-parameter query tool with an output schema, the description is reasonably complete: it gives scope, exclusions, indicator types, and realistic example questions. It does not explicitly compare against near-neighbor enterprise_change_* siblings, but the stated scope is sufficient for basic selection and invocation.

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 coverage is 100%, with both country_name and company_name already described with concrete examples. The description adds typical question patterns that reinforce expected usage, but it does not provide substantial new parameter semantics beyond what the schema already offers.

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?

The description clearly states the tool queries enterprise-level periodic changes in business operations relating to strategic adjustments, business transformation, and main-business composition changes. It explicitly excludes industry-level macro strategy research and batch screening by park/industry chain, which distinguishes it from sibling tools.

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 usage context ('用于查询战略调整、业务转型及主营构成变化等') and clear exclusions ('不用于行业层面的宏观战略研究'; '不包含:非本分类指标;按园区/产业链批量筛企业名单'). However, it does not explicitly name alternative sibling tools, so the when-not guidance is present but not fully tied to alternatives.

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