list-datasets

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

No annotations are provided, so the description must convey behavioral traits. It describes the return type and includes an example, but does not disclose pagination behavior (despite the 'limit' parameter), rate limits, authentication needs, or any side effects. The example is helpful but incomplete.

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: a brief one-line summary, then a clear definition of datasets, an example usage, and an expected return with formatted JSON. Every sentence adds value, and the key information is front-loaded.

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 simple list tool with one optional parameter and no output schema, the description provides a clear example of the return object. However, it lacks explanation of the 'limit' parameter, error conditions, or how to handle empty results, leaving some gaps despite the low complexity.

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 0% description coverage; the 'limit' parameter has no description in the schema and is not mentioned in the tool description. The description adds no meaning beyond the schema's type, default, and constraints. For a parameter with schema coverage 0%, the description should compensate but fails to do so.

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 gets 'a list of all datasets', provides a definition of datasets, and includes example usage and expected return with a sample JSON object. It effectively differentiates from sibling tools like 'get-dataset' by indicating it returns multiple 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 explains the purpose of datasets and provides an example query ('Show me all available datasets'). However, it does not explicitly state when not to use this tool or mention alternatives among the many siblings, which would enhance guidance.

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