Databento MCP

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

With no annotations provided, the description carries full burden. It discloses what the tool returns (5 specific components) which is valuable behavioral context. However, it doesn't mention performance characteristics, rate limits, authentication needs, or potential side effects. The description adds meaningful value but doesn't fully compensate for the lack of annotations.

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 perfectly structured: a clear purpose statement, bulleted combination list, concrete examples, and bulleted return values. Every sentence earns its place with zero waste. It's front-loaded with the core purpose and appropriately sized for the tool's complexity.

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 the tool's moderate complexity (4 parameters, no output schema, no annotations), the description does well by explaining what the tool returns in detail. However, it could better address when to use this versus individual component tools. The lack of output schema is partially compensated by the return value description.

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 already documents all parameters thoroughly. The description provides examples showing parameter usage but doesn't add semantic meaning beyond what's in the schema. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 performs a 'comprehensive analysis of a symbol' and specifies exactly what it combines: metadata, cost estimate, sample data, trading session info, and data quality check. It distinguishes itself from siblings like get_cost or get_symbol_metadata by bundling multiple functions into one call.

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 implies when to use this tool (for a quick, all-in-one analysis) but doesn't explicitly state when NOT to use it or name specific alternatives. It suggests this is for comprehensive analysis rather than individual components, but lacks explicit comparison to siblings like get_cost or get_historical_data.

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