list_datasets

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

With no annotations, the description must indicate behavioral traits. It states 'list all currently loaded datasets' and 'without reloading', implying a read-only, non-destructive operation with minimal impact. It does not mention authentication or side effects, but none are expected for a list operation.

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 extremely concise: two sentences that state the action and the usage context. No filler or repetition. Every sentence adds value.

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 tool has no parameters and an output schema exists (though not shown), the description is sufficient. It specifies the return values (names, row counts, column names). It could mention if there are limits or pagination, but for a simple list, this 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 tool has zero parameters, and schema description coverage is 100%. The description adds no parameter info since none exist, which is appropriate. Baseline for 0 parameters is 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 clearly states the tool lists currently loaded datasets and specifies the returned information (names, row counts, column names). It distinguishes from sibling tools like load_dataset, which loads data, and explain_segment, which analyzes segments.

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 includes a usage hint: 'Use this to remind yourself what data is available without reloading.' This implies the tool is for quick lookup, avoiding reloading. However, it does not explicitly state when not to use it or compare to alternatives like load_dataset.

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