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imbenrabi

Financial Modeling Prep MCP Server

getFundSectorWeighting

Read-onlyIdempotent

Retrieve the percentage allocation of a fund's assets across industry sectors. Use this data to analyze ETF exposure to specific sectors like technology or healthcare.

Instructions

The FMP ETF Sector Weighting API provides a breakdown of the percentage of an ETF's assets that are invested in each sector. For example, an investor may want to invest in an ETF that has a high exposure to the technology sector if they believe that the technology sector is poised for growth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesFund symbol
Behavior3/5

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

Annotations already indicate read-only, idempotent, and open-world traits. The description adds that it returns sector percentages, which is core behavior. However, it does not disclose any additional behavioral traits (e.g., data format, limits) beyond what annotations and schema imply.

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, with the second sentence being an illustrative example that adds little actionable guidance for an AI agent. It is slightly verbose but still efficient.

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?

With no output schema, the description should clarify the return format. It vaguely mentions 'breakdown of percentages per sector', which is adequate but could be more precise (e.g., list of objects with sector and weight). For a simple tool, it is marginally sufficient.

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?

Schema coverage is 100% with a single parameter 'symbol' described as 'Fund symbol'. The description does not add any extra meaning or context for this parameter, so baseline score applies.

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

Purpose5/5

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

The description clearly states the tool provides a breakdown of ETF sector weightings, using a specific verb ('provides') and resource ('percentage of an ETF's assets invested in each sector'). This differentiates it from siblings like getFundCountryAllocation or getFundAssetExposure.

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

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives an example scenario but does not explicitly state when to use this tool over alternatives or when not to use it. Siblings like getFundCountryAllocation and getFundAssetExposure are not mentioned, so guidance is only implied.

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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