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drmartell

thetadata-mcp

by drmartell

option_at_time_quote

Retrieve the last NBBO quote for an option contract at a specified time of day. Use it to access historical option quotes at a precise timestamp.

Instructions

[VALUE] Last option NBBO quote at a specific time of day.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rightNoThe right (call or put) of the contract.both
strikeNoThe strike price of the contract in dollars (ie `100.00` for `$100.00`), or `*` for all strikes.*
symbolYesThe stock or index symbol, or underlying symbol for options.
max_dteNoIf specified, only contracts with a full calendar day 'Days to Expiration' (DTE) less than or equal to this number will be returned.
end_dateNoThe end date (inclusive).
expirationYesThe expiration of the contract in `YYYY-MM-DD` or `YYYYMMDD` format, or `*` for all expirations.
start_dateNoThe start date (inclusive).
time_of_dayYesThe time of the day to fetch data for; assumed to be America/New_York.
strike_rangeNoUsed to specify a filter to limit the number of contracts returned relative to the underlying's spot price. Will return the specified number of strikes above and below the spot price, as well as the at-the-money strike.
Behavior2/5

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

With no annotations, the description must carry the burden of behavioral disclosure, but it only says 'last option NBBO quote at a specific time of day.' It does not clarify that this is historical, how 'last' is determined, timezone handling, or what the response contains. The schema mentions timezone, but the description adds little value.

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 a single concise sentence that communicates the core purpose efficiently. However, the '[VALUE]' prefix is extraneous and slightly detracts from the structure.

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?

This tool has nine parameters and no output schema, yet the description is a single sentence that does not explain parameter interactions, filtering behavior, or return format. It is insufficient for an agent to fully understand the tool's behavior beyond the schema descriptions.

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 every parameter already has a description. The tool description does not add any additional parameter semantics, which aligns with the baseline score of 3 for high schema coverage.

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 identifies the tool as returning the last option NBBO quote at a specific time of day, which distinguishes it from snapshot or historical range tools. However, it lacks an explicit action verb like 'get' or 'fetch', and the leading '[VALUE]' placeholder adds noise.

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?

No guidance is provided on when to use this tool versus alternatives such as option_snapshot_quote or option_history_quote. The description simply states what it does, leaving the appropriate use case implicit.

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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