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Nice-Wolf-Studio

DataBento MCP Server

metadata_get_cost

Calculate the USD cost of a historical data query before downloading. Specify dataset, symbols, and date range to estimate fees.

Instructions

Calculate the cost in USD for a historical data query before downloading

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasetYesDataset code (e.g., GLBX.MDP3)
symbolsNoComma-separated list of symbols or single symbol
schemaNoSchema name (default: trades)
startYesInclusive start date/time (YYYY-MM-DD or ISO 8601)
endNoOptional exclusive end date/time (YYYY-MM-DD or ISO 8601)
modeNoQuery mode (default: historical-streaming)
stype_inNoInput symbology type (e.g., raw_symbol, continuous)
stype_outNoOutput symbology type (e.g., instrument_id, raw_symbol)
Behavior4/5

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

With no annotations, the description must fully disclose behavior. It states the tool calculates cost before downloading, implying it is a safe, read-only operation. However, it does not explicitly state idempotency or lack of side effects, but the name 'metadata_get_cost' and description suggest no state changes. This is adequate for a simple cost estimation tool.

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, concise sentence that directly conveys the tool's purpose. There is no fluff or redundant information. Every word is necessary.

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 lack of an output schema and the moderate complexity of 8 parameters, the description is minimal. It does not explain the return format, units, or any error conditions. While the parameter schema covers inputs, the agent would benefit from knowing that the result is a numeric cost value. The description is adequate but not fully complete.

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 input schema has 100% description coverage, meaning it already documents all 8 parameters with their meanings. The description does not add any additional semantic information beyond what the schema provides. Therefore, a score of 3 is appropriate as the description adds no value beyond the schema.

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's purpose: 'calculate the cost in USD for a historical data query before downloading'. The verb 'calculate' and resource 'cost' are specific, and it distinguishes itself from sibling tools like 'get_historical_bars' which retrieve data, and 'batch_submit_job' which submits downloads.

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 does not provide explicit guidance on when to use this tool versus alternatives. While the purpose is clear, it lacks information about prerequisites, exclusions, or scenarios where other tools would be more appropriate. The agent must infer usage context.

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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