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TWSE MCP Server

TWSE MCP Server

by twjackysu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_company_governance_info

Retrieve corporate governance details for TWSE-listed companies using stock codes to analyze board structures, shareholder rights, and compliance information.

Instructions

Obtain corporate governance information for a listed company based on its stock code.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "code": "<code>"
    },
    "name": "get_company_governance_info"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states 'obtain' which implies a read operation, but doesn't disclose behavioral traits like rate limits, authentication needs, data freshness, or what 'corporate governance information' entails (e.g., board details, regulations). This is a significant gap for a tool with no annotation coverage.

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?

Single sentence, front-loaded with the core action and resource, no wasted words. It efficiently conveys the purpose without unnecessary elaboration, making it easy for an agent to parse quickly.

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

Completeness3/5

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

Given no annotations, 0% schema coverage, but an output schema exists (so return values are documented elsewhere), the description is incomplete. It covers basic purpose but lacks behavioral context, parameter details, and usage guidelines, making it adequate only with reliance on structured fields like the output schema.

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?

The description adds that the 'code' parameter is a 'stock code' for a 'listed company', which provides context beyond the schema's generic 'Code' title and 0% coverage. However, it doesn't specify format (e.g., ticker symbol, ISIN) or examples, leaving gaps. With one parameter and low schema coverage, this is minimally adequate.

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 states the verb 'obtain' and the resource 'corporate governance information for a listed company', specifying it's based on a stock code. It distinguishes from siblings by focusing on governance info rather than financials, news, or other company data, though it doesn't explicitly name alternatives.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives like get_company_profile or get_company_board_info, which might overlap. The description implies usage for governance info but lacks explicit context or exclusions, leaving the agent to infer based on sibling names alone.

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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