FinanceKit MCP

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

Annotations provide readOnlyHint=true, indicating this is a safe read operation. The description adds behavioral context by specifying the data source (SPDR sector ETFs) and the ranking aspect (by return), which isn't covered by annotations. However, it doesn't disclose other traits like rate limits, authentication needs, or detailed output behavior (though output schema exists). With annotations covering safety, the description adds moderate value.

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 highly concise and front-loaded: it states the core purpose in the first sentence, adds detail in the second, and provides usage guidance in the third. Every sentence earns its place by delivering essential information without redundancy or fluff, making it easy for an agent to parse quickly.

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 moderate complexity (ranking performance), rich annotations (readOnlyHint), and the presence of both input and output schemas, the description is mostly complete. It covers purpose, data source, and usage context. The output schema likely handles return values, so the description doesn't need to explain them. A minor gap is lack of explicit differentiation from siblings, but overall it provides sufficient context for an agent to use the tool effectively.

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, with the 'period' parameter well-documented (default: '3mo', options: '1mo', '3mo', '6mo', '1y'). The description doesn't add any parameter-specific information beyond what the schema provides, such as explaining the impact of different periods on rankings. Baseline score of 3 is appropriate since the schema handles parameter documentation effectively.

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: 'Sector performance ranking via SPDR sector ETFs' and 'Returns performance of all 11 GICS sectors ranked by return.' It specifies the verb (ranking/returns), resource (SPDR sector ETFs/GICS sectors), and scope (all 11 sectors). However, it doesn't explicitly differentiate from sibling tools like 'market_overview' or 'risk_metrics' that might also provide sector-related data.

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 clear context for when to use this tool: 'Useful for identifying market leadership and rotation trends.' This gives a specific use case (market analysis and trend identification). It doesn't explicitly state when not to use it or name alternatives among siblings, but the context is sufficiently clear for an agent to infer applicability.

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