company_equity_pledge基于明确指定的企业名称，查询该企业涉及的股权出质信息，包括登记编号、状态、出质人、质权人、股权出质登记日期、出质人证件号码、质权人证件号码、股权出质目标公司、股权出质数额等。
Pricing: {"unit": "credits", "billing_model": "per_run", "per_run": 0.2}
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | 指定返回第几页结果，从 1 开始，默认 1；与 limit 配合使用。 | |
| limit | No | 指定单次请求最多返回的记录数，默认 20，最大 100。 | |
| company_name | Yes | 企业名称（必填）。用于查询该企业的股权出质信息。示例：通威股份有限公司 |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description includes useful behavioral context such as pricing per run and the read-only '查询' (query) intent, but it does not explicitly disclose side effects, rate limits, or permission requirements. With only openWorldHint in annotations, the description carries more burden, but it still leaves some transparency gaps.
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 a single focused sentence followed by a clear pricing line. It is reasonably compact, though the long enumeration of returned fields partly duplicates information that would be present in the output schema.
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?
The tool has a clear purpose, full parameter documentation, and an output schema, so the description is largely complete for invocation. It could be improved by explicitly contrasting with sibling tools like company_equity_freeze, but overall it provides enough context.
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 the schema already documents company_name, page, and limit with meaningful descriptions. The description adds little beyond restating the core company_name requirement; it does not substantially enhance parameter understanding.
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 uses a specific verb ('查询'/'query') and identifies a precise resource ('股权出质信息'/'equity pledge information') with a detailed list of returned fields. It clearly distinguishes from the sibling tool company_equity_freeze by focusing on '出质' (pledge) rather than '冻结' (freeze).
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 clearly states the prerequisite that a specific enterprise name must be provided ('基于明确指定的企业名称'), giving the agent a clear condition for when to invoke the tool. It does not explicitly name alternatives or when-not-to-use scenarios, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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 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.
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.
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).