Databento MCP

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 states the tool estimates costs, implying it's a read-only, non-destructive operation, but lacks details on rate limits, authentication needs, or what the estimation output includes (e.g., currency, granularity). This leaves gaps for a tool with no annotation coverage.

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

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

The description is a single, front-loaded sentence that efficiently conveys the tool's purpose without unnecessary words. Every part of the sentence earns its place by specifying the action ('estimate'), target ('cost'), and context ('before executing it').

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

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

Given no annotations and no output schema, the description is minimally complete for a read-only estimation tool. It clarifies the tool's role but lacks details on behavioral aspects (e.g., response format, error handling) and output expectations, which are important for a cost estimation function in a data query context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents all 5 parameters. The description does not add any parameter-specific information beyond what the schema provides (e.g., it doesn't explain relationships between parameters like 'dataset' and 'schema'). Baseline 3 is appropriate when the schema handles parameter documentation.

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

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

The description clearly states the tool's purpose with a specific verb ('estimate') and resource ('cost of a historical data query'), distinguishing it from siblings like 'get_historical_data' (which executes queries) and 'list_unit_prices' (which lists pricing). It precisely indicates this is a pre-execution estimation tool.

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

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

The description provides clear context for usage ('before executing it'), implying this tool should be used to check costs prior to running actual queries. However, it does not explicitly state when not to use it or name specific alternatives (e.g., 'get_historical_data' for execution), which prevents a perfect score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.