list-datasets

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

No annotations are provided, so the description must compensate. It describes the return format with an example array, indicating a read-only operation. The description is straightforward and does not hide any behavioral traits, but it could have mentioned that it is non-destructive.

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 a clear first line, explanatory text, example usage, and expected return format. It is front-loaded and each section adds value, though the dataset explanation could be slightly more concise.

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 lack of an output schema, the description provides a detailed example of the return structure. It explains what datasets are and how the tool is used. However, it omits explanation of the 'limit' parameter, which is a minor gap for a simple list tool.

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 input schema has one parameter 'limit' with 0% description coverage. The description does not mention this parameter, so it fails to add meaning beyond the schema. Although 'limit' is somewhat self-explanatory, the description should clarify its purpose (e.g., 'limits the number of datasets returned').

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 'Get a list of all datasets' and explains what datasets are, making the tool's purpose unambiguous. It distinguishes itself from sibling tools like get-dataset and list-experiments-for-dataset by focusing on listing all datasets.

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 a clear example usage ('Show me all available datasets') and context for when to use the tool. While it does not explicitly state when not to use it or mention alternatives, the purpose is well-defined and easily understood from the sibling tool set.

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