FinanceMCP

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While the description mentions what data can be obtained, it doesn't disclose important behavioral traits like whether this is a read-only operation, potential data volume issues (though hinted in schema), rate limits, authentication requirements, or error conditions. The description is purely functional without behavioral context.

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, efficient Chinese sentence that clearly states the tool's purpose and lists available data types. It's appropriately sized and front-loaded with the main purpose. There's no wasted verbiage, though it could potentially be structured better for readability with bullet points or clearer organization.

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 tool has 5 parameters, no annotations, and no output schema, the description is somewhat incomplete. While it states what data can be obtained, it doesn't address important contextual aspects like response format, data volume considerations (though hinted in schema), error handling, or performance characteristics. For a data retrieval tool with multiple parameters and no output schema, more completeness would be helpful.

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?

With 100% schema description coverage, the schema already documents all 5 parameters thoroughly. The description doesn't add any parameter semantics beyond what's in the schema - it doesn't explain parameter relationships, provide examples of parameter combinations, or clarify edge cases. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 tool's purpose: '获取公募基金全面数据' (get comprehensive public fund data) and lists specific data types including fund lists, fund managers, net asset values, dividends, and holdings. It provides a specific verb ('获取' - get) and resource ('公募基金全面数据' - comprehensive public fund data), but doesn't explicitly distinguish this tool from sibling tools like 'fund_manager_by_name' which appears to be a more specialized tool.

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 implies usage context by listing the data types available, but doesn't provide explicit guidance on when to use this tool versus alternatives like 'fund_manager_by_name'. There's no mention of when not to use this tool or clear comparison with sibling tools. The usage context is somewhat implied through the data_type parameter options.

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