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 cancels jobs but doesn't mention important behavioral aspects: whether cancellation is reversible, what permissions are required, if there are rate limits, how long cancellation takes, or what happens to associated resources (e.g., files). The description adds basic return information but lacks critical operational context for a mutation 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 well-structured with clear sections (purpose, parameters, returns, example) and uses bold formatting effectively. The core purpose is stated upfront in the first sentence. While the parameter and return sections are somewhat redundant given the schema coverage, they're organized efficiently. The example adds practical value without unnecessary verbosity.

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?

For a mutation tool with no annotations and no output schema, the description is incomplete. It mentions return values but doesn't specify their format or structure. It doesn't cover error conditions, side effects, or dependencies. Given the tool's potential impact (canceling jobs) and lack of structured metadata, the description should provide more comprehensive operational context to be complete.

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 fully documents the single parameter 'job_id'. The description repeats the parameter documentation verbatim ('The batch job ID to cancel'), adding no additional meaning beyond what the schema provides. With complete schema coverage, the baseline score of 3 is appropriate as the description doesn't enhance parameter understanding.

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 ('Cancel') and target resource ('a pending or processing batch job'), making the purpose immediately understandable. It distinguishes from siblings like 'submit_batch_job' and 'list_batch_jobs' by focusing on cancellation rather than creation or listing. However, it doesn't explicitly differentiate from potential alternatives like 'stop_batch_job' or 'abort_batch_job' if they existed.

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. While it mentions 'pending or processing batch job', it doesn't specify prerequisites (e.g., job must be in a cancellable state), exclusions (e.g., cannot cancel completed jobs), or compare it to related tools like 'get_batch_job_files' for checking job status first. Usage context is implied but not explicitly stated.

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