list_cached_datasets

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

With no annotations, the description carries the behavioral burden and does well by disclosing the local cache path and the downstream constraint that only cached datasets can be queried or audited. It does not explicitly state read-only behavior, ordering, or edge cases such as an empty cache, but for a simple listing operation the key behavioral context is present.

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 two front-loaded sentences with no redundant wording. The core behavior is stated first, followed by the useful dependency and alternative tool.

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 zero-parameter listing tool with an output schema, the description supplies everything needed to select and invoke it correctly: what is listed, where the cache lives, the constraint on downstream use, and the alternative for uncached datasets. Return values need not be explained because an output schema exists.

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, so the baseline is 4 and there is no parameter meaning for the description to add. The schema is empty and fully covered.

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 uses a specific verb and resource: list dataset ids whose rows are cached locally in data/raw/. It also explicitly contrasts with fetch_dataset for datasets that are not cached, so the agent can distinguish it from sibling tools without opening schemas.

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?

It clearly states when this tool is relevant by noting that only cached datasets can be queried in SQL or audited for coverage. It also names the alternative action, fetch_dataset, for datasets that are not yet cached.

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