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alpacahq

alpaca-mcp-server

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by alpacahq

get_option_trades

Retrieve historical trade data for option contracts to analyze market activity, track price movements, and inform trading decisions using Alpaca's API.

Instructions

Retrieves historical trade data for one or more option contracts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolsYesA comma-separated list of contract symbols with a limit of 100.
startNoThe inclusive start of the interval. Format: RFC-3339 or YYYY-MM-DD. Default: the beginning of the current day, but at least 15 minutes ago if the user doesn't have real-time access for the feed.
endNoThe inclusive end of the interval. Format: RFC-3339 or YYYY-MM-DD. Default: the current time if the user has a real-time access for the feed, otherwise 15 minutes before the current time.
limitNoThe maximum number of data points to return in the response page. The API may return less, even if there are more available data points in the requested interval. Always check the `next_page_token` for more pages. The limit applies to the total number of data points, not per symbol!
page_tokenNoThe pagination token from which to continue. The value to pass here is returned in specific requests when more data is available, usually because of a response result limit.
sortNoSort data in ascending or descending order.asc

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions retrieving 'historical trade data,' implying a read-only operation, but fails to specify critical details like rate limits, authentication requirements, data latency (e.g., how recent the data is), or pagination behavior (though the schema hints at pagination). This leaves significant gaps for safe and effective tool invocation.

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

Conciseness5/5

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy for an agent to parse quickly while still conveying the core functionality.

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 complexity (6 parameters, historical data retrieval) and the presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks context on behavioral traits (e.g., rate limits, data freshness) and usage guidelines, which are important for a data-fetching tool with multiple siblings. The schema and output schema cover technical details, but the description doesn't fully compensate for the missing annotations.

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?

The schema description coverage is 100%, with detailed parameter documentation in the input schema (e.g., defaults for 'start', 'end', and 'limit', and pagination notes). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 for adequate but not enhanced parameter context.

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 verb ('Retrieves') and resource ('historical trade data for one or more option contracts'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_option_bars' or 'get_option_latest_trade', which also retrieve option data but with different scopes or formats.

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 like 'get_option_bars' (for aggregated data) or 'get_option_latest_trade' (for real-time data). It lacks context about prerequisites, such as required permissions or data availability, leaving the agent to infer usage from the tool name alone.

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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