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 mentions retrieving and analyzing data but doesn't specify critical behaviors such as the data format (e.g., JSON, CSV), time range defaults, rate limits, authentication requirements, or whether it's a read-only operation. The phrase 'using the Historical S&P 500 API' hints at an external source but lacks operational details, making it insufficient for a tool with potential complexity in data handling.

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 long and avoids unnecessary fluff, but it could be more front-loaded. The first sentence states the core action ('Retrieve historical data'), and the second adds analysis context. However, it includes vague phrases like 'understand trends and performance over time' that don't add specific value. While concise, it lacks the precision needed for optimal agent guidance, making it adequate but not exemplary.

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 historical data retrieval and analysis, the description is incomplete. No annotations or output schema are provided, and the description fails to cover essential aspects like data format, time ranges, error handling, or example use cases. It mentions 'additions and removals of companies,' which adds some context, but overall, it leaves too many operational details unspecified for a tool that likely returns structured historical data.

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 0 parameters with 100% description coverage, so no parameters need documentation. The description doesn't add parameter details, which is appropriate since there are none to describe. It mentions analyzing 'past changes' and 'trends over time,' which could imply temporal aspects, but without parameters, this doesn't compensate for missing schema info. The baseline for 0 parameters is 4, as the description doesn't need to cover parameters but could have hinted at implicit filters.

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 historical data for the S&P 500 index' and 'Analyze past changes in the index, including additions and removals of companies.' It specifies the verb ('retrieve,' 'analyze') and resource ('S&P 500 index'), distinguishing it from siblings like 'getHistoricalDowJonesChanges' or 'getHistoricalNasdaqChanges' by focusing on the S&P 500. However, it doesn't explicitly differentiate from other S&P 500 tools (e.g., 'getSP500Constituents'), which slightly reduces clarity.

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 'additions and removals of companies,' which might imply usage for tracking index composition changes, but it doesn't specify when to choose this over tools like 'getHistoricalDowJonesChanges' for other indices or 'getSP500Constituents' for current constituents. There are no explicit when-to-use or when-not-to-use instructions, leaving the agent with minimal contextual direction.

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