FMP MCP Server

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true, covering safety and idempotency. The description adds useful context by specifying the return data structure (analyst count, price targets, ratings breakdown, and FMP's own rating), which enhances understanding beyond annotations. No contradictions with annotations are present.

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 front-loaded with the core purpose, followed by a bullet-point-style list of return values and a clear parameter explanation. Every sentence adds value without redundancy, making it efficient and well-structured.

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, rich annotations (covering safety and idempotency), and the presence of an output schema (which handles return value documentation), the description is complete. It effectively explains the purpose, parameter, and return data without needing to duplicate structured information.

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% description coverage, but the description compensates by explaining the 'symbol' parameter as 'Stock ticker symbol (e.g. "AAPL")', providing clear semantics and an example. Since there is only one parameter, this is sufficient to achieve a high score, though it doesn't detail format constraints beyond the example.

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 specific action ('Get Wall Street analyst consensus') and resource ('price targets, ratings, and buy/sell distribution'), distinguishing it from siblings like 'fair_value_estimate' or 'stock_brief' by focusing exclusively on analyst data rather than intrinsic valuation or general summaries.

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 implies usage for analyst consensus data but does not explicitly state when to use this tool versus alternatives like 'fair_value_estimate' (which might provide different valuation metrics) or 'peer_comparison' (which could include analyst data in a broader context). No exclusions or prerequisites are mentioned.

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