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imbenrabi

Financial Modeling Prep MCP Server

getRSI

Calculate the Relative Strength Index (RSI) to analyze stock momentum and identify overbought or oversold conditions using historical price data.

Instructions

Calculate the Relative Strength Index (RSI) for a stock using the FMP RSI API. This tool helps users analyze momentum and overbought/oversold conditions based on historical price data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock symbol
periodLengthYesPeriod length for the indicator
timeframeYesTimeframe (1min, 5min, 15min, 30min, 1hour, 4hour, 1day)
fromNoStart date (YYYY-MM-DD)
toNoEnd date (YYYY-MM-DD)
Behavior2/5

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 states the tool calculates RSI using an API but lacks details on rate limits, authentication needs, error handling, or what the output looks like (since there's no output schema). For a tool with no annotation coverage, this is a significant gap in transparency.

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 concise with two sentences that efficiently state the tool's purpose and its analytical use. It is front-loaded with the core functionality, though it could be slightly more structured by explicitly listing key parameters or output format.

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

Completeness2/5

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

Given the complexity of a financial indicator tool with no annotations and no output schema, the description is incomplete. It fails to explain the return values, error conditions, or behavioral traits like rate limits, which are crucial for an AI agent to use the tool effectively in a financial context.

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 description coverage is 100%, so the schema already documents all five parameters (symbol, periodLength, timeframe, from, to) with clear descriptions. The description adds no additional parameter semantics beyond what the schema provides, such as default values or usage examples, which aligns with the baseline score of 3 when schema coverage is high.

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 the tool calculates the Relative Strength Index (RSI) for a stock using the FMP RSI API, which is a specific verb (calculate) and resource (RSI for a stock). It distinguishes from siblings by focusing on momentum and overbought/oversold conditions analysis, though it doesn't explicitly differentiate from other technical indicators like getADX or getSMA in the sibling list.

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 mentions that the tool 'helps users analyze momentum and overbought/oversold conditions based on historical price data,' which implies usage for technical analysis. However, it provides no explicit guidance on when to use this tool versus alternatives (e.g., other technical indicators like getADX or getSMA), nor does it specify prerequisites or exclusions.

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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