kaggle_kernel_logs

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

There are no annotations, so the description carries the full behavioral burden. It does disclose one non-obvious trait: logs are often only available after the kernel is complete. However, it does not mention whether the call is read-only, what happens when logs are not ready, or whether it errors or returns partial data.

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 with no filler. It efficiently communicates the core action and a key timing caveat.

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?

This is a simple one-parameter tool with an output schema, so the return format need not be described. Still, the description is thin: it leaves usage timing vague with 'often,' lacks parameter format details, and does not help an agent decide between this and closely related sibling tools.

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 0%, and the description does not explain the kernel_slug parameter or its expected format. The parameter title 'Kernel Slug' and the tool name provide some self-evident meaning, but there is no guidance on forms like 'owner/kernel-slug' versus just a slug, and the description adds no parameter-level value.

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 states a clear verb and resource: 'Fetch kernel output logs.' The caveat 'often only after complete' adds context and helps distinguish from status-checking tools like kaggle_kernel_status. However, it does not explicitly differentiate itself from sibling tools or specify whether 'logs' means stdout/stderr, full output, or something else.

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?

No explicit when-to-use or when-not-to-use guidance is provided. The phrase 'often only after complete' implies logs should be fetched after kernel completion, but it does not explain how this relates to kaggle_kernel_status or kaggle_kernel_output_to_drive, nor when an agent should prefer an alternative.

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