list_datasets

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

Annotations already signal a read-only operation, and the description adds useful scope: only datasets under the active storage_path are listed, and only indexed datasets appear. This gives agents accurate expectations without contradicting readOnlyHint.

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?

Three short sentences, each with a distinct role: what is returned, when to call it, and a scope limitation. No filler or repetition; the most critical action ('call it first') 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?

The description covers the returned fields, the recommended usage order, and the storage_path constraint. For a zero-parameter read-only listing tool, this fully equips an agent to invoke it effectively.

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?

There are zero parameters and schema description coverage is 100%, so no parameter documentation is needed. The description does not add parameter-specific detail, but none is required; baseline 4 is appropriate.

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 states a specific verb and resource: list every indexed dataset, and includes concrete output fields (row count, column count, source file). It also frames itself as the entry point for 'every other tool,' which distinguishes it from siblings like list_repos or describe_column.

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?

Explicitly instructs 'Call it first' to find the dataset name needed by other tools and to confirm a file was indexed. It lacks explicit exclusions or comparisons to sibling tools, but the intended call order and use case are clear.

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