FMP MCP Server

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

Annotations already provide readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true, covering safety and idempotency. The description adds valuable context beyond this by specifying the data scope (upcoming estimates and recent annual history) and return structure, which helps the agent understand what to expect without contradicting annotations.

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 in the first sentence, followed by specific data details and parameter explanation. Every sentence earns its place by adding clarity without redundancy, making it efficient and well-structured for quick understanding.

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 behavior), and the presence of an output schema (which handles return values), the description is complete enough. It explains the purpose, data scope, and parameter semantics, leaving no critical gaps for agent 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?

With 0% schema description coverage, the description fully compensates by explaining the 'symbol' parameter's meaning ('Stock ticker symbol') and providing an example ('e.g. "AAPL"'). This adds essential semantics beyond the bare schema, though it doesn't detail format constraints (e.g., case sensitivity).

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 with specific verbs ('Get analyst earnings estimates and income statement history') and resource ('for a stock'), distinguishing it from siblings like 'analyst_consensus' (which lacks historical context) and 'financial_statements' (which is broader). It precisely identifies what data is retrieved: upcoming quarterly estimates (EPS/revenue) and recent annual income 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 implies usage context by specifying it provides 'upcoming quarterly estimates' and 'recent annual income data for trend context,' suggesting it's for earnings analysis. However, it doesn't explicitly state when to use this tool versus alternatives like 'earnings_postmortem' (likely for past earnings) or 'financial_statements' (comprehensive data), leaving some ambiguity in sibling differentiation.

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