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 reads and returns data, but doesn't cover critical aspects like error handling (e.g., what happens if the file doesn't exist), performance implications (e.g., memory usage for large files), or output format details. This leaves significant gaps for a data-reading tool.

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, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action and outcome, making it easy to understand at a glance. Every word earns its place.

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 incomplete for a data-reading tool with 3 parameters. It doesn't explain what 'return the data' means in practice (e.g., format, structure, or limitations), nor does it address behavioral aspects like error handling. This is inadequate for guiding an agent effectively.

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 input schema fully documents all parameters (file_path, limit, columns). The description adds no additional meaning beyond what's in the schema—it doesn't explain parameter interactions or provide examples. Baseline 3 is appropriate as 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 action ('Read') and resource ('a Parquet file'), and specifies the outcome ('return the data'). It's specific about what the tool does, though it doesn't explicitly differentiate from sibling tools like 'read_dbn_file' or 'export_to_parquet' beyond the file format.

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 no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over 'read_dbn_file' for similar data reading tasks, or any prerequisites like file accessibility. Usage is implied by the name and purpose, but no explicit context or exclusions are given.

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