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 'real-time market data' and listing return metrics (e.g., 52-week range, P/E ratio), which goes beyond annotations. However, it lacks details on rate limits, data freshness, or error handling, leaving behavioral gaps despite the annotations.

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 and efficiently expands in the second sentence with key return details. Every sentence adds value without redundancy, making it appropriately concise and well-structured for quick understanding.

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 low complexity (1 parameter), high schema coverage (100%), annotations (readOnlyHint), and presence of an output schema, the description is mostly complete. It covers purpose, key return metrics, and real-time nature. However, it could slightly improve by mentioning data sources or limitations, but gaps are minor in this context.

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?

Schema description coverage is 100%, with the parameter 'symbol' fully documented in the schema. The description does not add any parameter-specific details beyond what the schema provides (e.g., no examples beyond 'AAPL, MSFT, TSLA' or format constraints). Baseline score of 3 is appropriate as the schema carries the full burden.

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 specific verbs ('Get') and resources ('current stock price, change, volume, and key metrics for a ticker'), distinguishing it from siblings like 'price_history' (historical data) or 'company_info' (fundamental data). It explicitly mentions real-time market data, which sets it apart from tools focused on other asset classes or timeframes.

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 specifying 'real-time market data' and listing metrics like price and P/E ratio, which helps differentiate it from siblings such as 'price_history' (historical) or 'technical_analysis' (indicators). However, it does not explicitly state when not to use this tool or name alternatives, leaving some ambiguity compared to tools like 'multi_quote' for multiple symbols.

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