remove_dataset_logs

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

There are no annotations, so the description carries the full burden. It explicitly states that logs are removed and 'wipe' for all, but does not disclose whether the operation is permanent, requires permissions, or has side effects on related data. This lack of caution or detail reduces transparency.

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 concise, consisting of two sentences, and efficiently packs the purpose, usage examples, and special cases without any fluff. It is well-structured and easy to parse.

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 absence of an output schema and annotations, the description provides sufficient context about the operation, including how to target specific logs or all logs. It could mention irreversibility or error conditions, but for a delete tool, the coverage is adequate.

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?

The schema already describes all parameters with 100% coverage. The description adds value by providing a concrete example for the filters structure and clarifying the role of is_deleting_all_logs. This enhances understanding beyond the schema.

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's purpose: removing logs from a dataset by filter. It also distinguishes itself from read-only siblings like list_dataset_logs or retrieve_dataset_log by emphasizing deletion and provides specific usage examples for single or all logs.

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 gives concrete usage instructions (filter syntax, is_deleting_all_logs flag) but does not explicitly mention when not to use it or compare to alternative deletion methods. However, the examples are sufficient to understand when to call it.

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