validate_dataset_advanced

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

The description discloses that execution occurs inside a Docker container connected to a remote CIFS share, which is useful behavioral context. No annotations were provided, so the description partially fills the gap. However, it does not mention potential side effects, required permissions, or whether the tool is read-only.

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 two sentences long, front-loads the core purpose, and each sentence adds meaningful information. No superfluous content.

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 complexity (Docker execution, remote share, multiple task types), the description omits prerequisites (Docker, CIFS mount), potential errors, and timeouts. However, since an output schema exists, return values are not required. The description is adequate for basic understanding but not fully 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?

With 0% schema description coverage, the description adds value by explaining that 'task' supports detect/segment (yaml) and classify (directory), and 'dataset_path' is the path on the CIFS share. However, it does not detail allowed values for 'task' beyond these categories or the format of 'dataset_path'.

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 it validates a YOLO dataset structure, specifies the method (Docker container, CIFS share), and lists supported task types. However, it does not distinguish from the sibling tool 'check_dataset_path', which may perform a similar validation.

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 guidance is provided on when to use this tool versus alternatives like 'check_dataset_path'. The description does not include context for use cases or prerequisites.

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