Financial Modeling Prep MCP Server

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. It states the tool provides 'average executive compensation data' and 'insights for comparing executive pay by industry,' but lacks details on data sources, update frequency, limitations (e.g., industry coverage), or response format. For a data-fetching tool with zero annotation coverage, this is insufficient.

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 two sentences and avoids unnecessary fluff, but it could be more front-loaded with core functionality. Phrases like 'Gain access to' and 'essential insights' are somewhat verbose without adding critical information, though overall it remains reasonably concise.

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 (benchmark data retrieval), lack of annotations, and no output schema, the description is incomplete. It does not explain what the output contains (e.g., data structure, metrics included) or any prerequisites (e.g., industry selection). For a tool with one parameter but significant contextual needs, this is inadequate.

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 one parameter ('year') clearly documented in the schema. The description does not add any parameter-specific information beyond what the schema provides, such as valid year ranges or default behavior. With high schema coverage, the baseline score of 3 is appropriate.

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: 'Gain access to average executive compensation data across various industries' and 'provides essential insights for comparing executive pay by industry.' It specifies the verb ('gain access to') and resource ('executive compensation data'), but does not explicitly differentiate it from its sibling tool 'getExecutiveCompensation' (which appears to fetch specific compensation rather than benchmarks).

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 comparing executive pay by industry but does not specify when to choose this benchmark tool over other compensation or industry analysis tools in the sibling list, such as 'getExecutiveCompensation' or 'getIndustryPerformanceSnapshot.'

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