TWSE MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the return fields but does not mention critical traits like whether the data is real-time or historical, update frequency, rate limits, authentication needs, or potential errors. This leaves significant gaps for a tool with rich output.

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 well-structured and front-loaded with the core purpose, followed by a bulleted list of return fields. Every sentence earns its place, though the bullet list is detailed but necessary for clarity. It avoids redundancy and is efficiently sized.

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?

Given the complexity of financial data, no annotations, and an output schema (implied by context signals), the description is partially complete. It explains the return values well but lacks behavioral context (e.g., data freshness, limitations). For a tool with no parameters and rich output, it meets minimum viability but has clear gaps.

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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on output semantics by detailing the return fields, adding value beyond the schema. However, it could slightly improve by clarifying data formats (e.g., date format).

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 clearly states the specific action ('Get top 20 stocks') and resource ('by trading volume in the centralized market'), distinguishing it from siblings that focus on different data like abnormal stocks, block trades, or company-specific information. It precisely defines the scope and output.

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 provides no guidance on when to use this tool versus alternatives, such as for real-time vs. historical data, or how it differs from other volume-related tools like 'get_daily_market_trading_info'. It lacks explicit context or exclusions for usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.