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 describes the tool as a retrieval API for bulk data, implying it's a read-only operation, but doesn't explicitly state this. It mentions 'annual earnings surprises' and 'quick analysis,' but lacks details on permissions, rate limits, pagination, error handling, or response format. For a tool with no annotations, this leaves significant gaps in understanding its behavior beyond basic purpose.

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 appropriately sized with three sentences that are front-loaded: the first sentence states the core purpose, the second elaborates on the data provided, and the third notes the value. There's minimal waste, though the third sentence ('offering valuable insights...') is somewhat generic and could be trimmed without losing essential information.

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 complexity of a bulk data retrieval tool with no annotations and no output schema, the description is incomplete. It covers the purpose and high-level data but lacks crucial context: it doesn't explain the return format (e.g., structure of the earnings surprises data), any limitations (e.g., number of companies, time ranges), or how to interpret results. For a tool with one parameter but potentially rich output, this leaves the agent under-informed.

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 (the 'year' parameter is described as 'Year to get earnings surprises for'), so the schema does the heavy lifting. The description adds no additional parameter semantics beyond implying the data is for 'annual earnings surprises,' which aligns with the schema. With high schema coverage, the baseline score is 3, as the description doesn't compensate with extra details like format constraints or examples.

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: 'retrieve bulk data on annual earnings surprises' and 'provides actual versus estimated earnings per share (EPS) for multiple companies at once.' It specifies the verb ('retrieve'), resource ('bulk data on annual earnings surprises'), and scope ('multiple companies at once'), distinguishing it from single-company earnings tools. However, it doesn't explicitly differentiate from sibling tools like getEarningsCalendar or getEarningsReports, which might also involve earnings 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 no guidance on when to use this tool versus alternatives. It mentions 'enabling quick analysis' and 'offering valuable insights for investors and analysts,' but these are generic benefits that don't help an agent choose this tool over siblings like getEarningsCalendar (which lists upcoming earnings) or getEarningsReports (which might provide detailed reports). No explicit when-to-use, when-not-to-use, or alternative tools are specified.

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