FinanceKit MCP

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

Annotations provide readOnlyHint=true, indicating a safe read operation. The description adds value by specifying the scope of data returned (e.g., company description, financial metrics) and implying it fetches comprehensive fundamental data, which goes beyond the annotation. It does not disclose rate limits, auth needs, or data freshness, but with annotations covering safety, this is acceptable.

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 front-loaded with the core purpose in the first sentence, followed by a bullet-like list of returned data in the second sentence. It is efficiently structured with no redundant information, and every sentence directly contributes to understanding the tool's functionality without waste.

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's complexity (single parameter, read-only operation), annotations cover safety, and an output schema exists (implied by context signals), the description is largely complete. It specifies the data returned and purpose, though it could briefly mention the output format or data sources for full completeness, but this is minor given the structured support.

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 100% description coverage, clearly documenting the 'symbol' parameter as a stock ticker. The description does not add any parameter-specific details beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the description does not compensate but also does not detract.

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 with a specific verb ('Get') and resource ('detailed company information'), listing specific data types like sector, financials, and valuation metrics. It distinguishes itself from sibling tools (e.g., 'stock_quote' for price data, 'technical_analysis' for chart patterns) by focusing on fundamental company data rather than market quotes or technical indicators.

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 by specifying the type of data returned (e.g., fundamental data), which suggests it should be used when detailed company analysis is needed. However, it does not explicitly state when to use this tool versus alternatives like 'stock_quote' for simple price info or 'sector_rotation' for broader sector trends, nor does it mention any exclusions or prerequisites.

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