list_datasets

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

No annotations are provided, so the description carries the burden. 'List' implies a read-only operation with no side effects, which is sufficient. The description also notes that schemas are included, providing basic behavioral context. However, no details about performance, ordering, or caching are given.

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 sentence that is perfectly concise and front-loaded. Every word adds value, and there is no unnecessary elaboration.

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 zero parameters, the presence of an output schema, and recognizable sibling tools, the description is largely complete. It explains what the tool does and what it returns ('with their schema'). A minor improvement could mention ordering or pagination, but it is not necessary for a simple list operation.

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 tool has zero parameters and schema coverage is 100% (trivially). The description adds no parameter information because none exist, which is appropriate. According to guidelines, 0 parameters yields a baseline of 4.

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 'List all registered datasets with their schema' uses a specific verb ('List') and resource ('registered datasets'), clearly distinguishing it from sibling tools like load_csv, summary, and filter_rows which operate on specific 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 clearly states the tool's function as a listing operation, implying it should be used as a starting point before selecting or manipulating datasets. While no explicit exclusions or alternatives are given, the context from sibling tools makes the usage straightforward.

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