Financial Modeling Prep 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 states the tool accesses historical data via an API and supports trend analysis, but it doesn't mention critical behaviors like whether it's read-only, rate limits, authentication requirements, data freshness, error handling, or output format. For a data retrieval tool with zero annotation coverage, this is a significant gap in transparency.

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 concise and well-structured in two sentences: the first states the core functionality, and the second adds analytical context. It avoids redundancy and is front-loaded with the primary purpose. While efficient, it could be slightly more informative without sacrificing brevity.

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 (historical data retrieval with multiple parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like safety, performance, or output structure, which are crucial for an agent to use the tool effectively. The description alone is insufficient for confident tool invocation.

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 all four parameters (sector, from, to, exchange) with examples. The description adds no additional parameter semantics beyond what the schema provides, such as explaining optionality or interactions between parameters. However, since schema coverage is high, the baseline score of 3 is appropriate as 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: 'Access historical price-to-earnings (P/E) ratios for various sectors' and 'Analyze how sector valuations have evolved over time.' It specifies the resource (sector P/E ratios) and the action (access/analyze historical data). However, it doesn't explicitly differentiate from sibling tools like 'getHistoricalIndustryPE' or 'getSectorPESnapshot,' which likely serve related but distinct purposes.

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. It mentions analyzing long-term trends but doesn't specify prerequisites, limitations, or when other tools (e.g., 'getHistoricalSectorPerformance' or 'getSectorPESnapshot') might be more appropriate. This lack of comparative context leaves the agent with insufficient direction.

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