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imbenrabi

Financial Modeling Prep MCP Server

getExecutiveCompensation

Read-onlyIdempotent

Retrieve comprehensive executive compensation data including salaries, stock awards, total compensation, and filing details for any publicly traded company by entering its stock symbol.

Instructions

Retrieve comprehensive compensation data for company executives with the FMP Executive Compensation API. This API provides detailed information on salaries, stock awards, total compensation, and other relevant financial data, including filing details and links to official documents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock symbol
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds context about the type of data returned (salaries, stock awards, total compensation, filing details, links), which is useful but does not disclose any additional behavioral traits like pagination or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, concise and front-loaded with the purpose. It efficiently conveys the tool's function and data included, though it could be slightly more structured (e.g., bullet points for data types).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter, read-only, no output schema) and the rich annotations, the description adequately covers the purpose and data returned. However, it lacks usage guidelines and does not describe the output format, which would be helpful given the absence of an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema description coverage at 100% and only one parameter ('symbol' described as 'Stock symbol'), the description does not add extra meaning beyond the schema. The baseline of 3 applies since the schema carries the full burden.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Retrieve comprehensive compensation data for company executives', specifying the verb ('retrieve') and resource ('executive compensation data'). The description distinguishes from siblings like 'getCompanyExecutives' and 'getExecutiveCompensationBenchmark' by detailing the data types (salaries, stock awards, total compensation, filing details), though it does not explicitly compare with them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 such as 'getCompanyExecutives' or 'getExecutiveCompensationBenchmark'. It does not mention contexts that are appropriate or inappropriate, nor does it indicate prerequisites or behavioral constraints.

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

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