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twjackysu

TWSE MCP Server

get_public_company_income_statement

Retrieve income statements for public companies by stock code. Automatically adapts to industry-specific financial reporting formats.

Instructions

Obtain comprehensive income statement for a public company based on its stock code. Automatically detects company industry and uses appropriate financial statement format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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 mentions automatic industry detection and format adaptation, which adds some behavioral context, but doesn't disclose critical traits like whether this is a read-only operation, potential rate limits, authentication requirements, data freshness, or error conditions. For a financial data tool with no annotations, this is insufficient.

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?

Two clear, efficient sentences with zero waste. The first states the core purpose, the second adds valuable behavioral detail about industry detection. Well-structured and appropriately sized for the tool's complexity.

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 the tool has an output schema (which handles return values), no annotations, and simple parameters, the description is minimally adequate. However, for a financial data retrieval tool with many sibling alternatives and no safety annotations, it should provide more context about data sources, update frequency, and usage boundaries to be truly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% with 1 parameter, but the description clarifies that 'code' refers to 'stock code' for a public company. This adds meaningful semantics beyond the bare schema, though it doesn't specify format (e.g., ticker symbol conventions) or provide examples. With 0% coverage and only 1 parameter, the description does compensate adequately.

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 resource 'comprehensive income statement for a public company', specifying it's based on stock code. It distinguishes from sibling 'get_company_income_statement' by specifying 'public company', though not explicitly contrasting with other financial tools like balance sheet or profitability analysis.

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 explicit guidance on when to use this tool versus alternatives like 'get_company_balance_sheet' or 'get_company_profitability_analysis'. The description mentions automatic industry detection and format adaptation, but doesn't provide context on prerequisites, limitations, or comparison with sibling tools.

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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