list_datasets

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

No annotations are supplied, and the description covers the basics implied by "Lists": read-only enumeration with page/offset pagination. It does not disclose permission requirements, rate limits, or whether the listing is complete across all DAGs/workspaces, so the burden isn't fully carried, though nothing is contradicted.

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 core fact and the v1/v2 caveat are front-loaded, which is good. But the "[Tool Role]" prefix and the Args block largely restate the schema defaults that are already machine-readable, adding length without much new information.

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?

With an output schema present, return values need no explanation, and all three optional parameters are accounted for with pagination semantics. For a simple read-only list endpoint the definition is close to sufficient, missing only filter-pattern semantics and permission context.

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?

Schema description coverage is 0%, so the description must carry the parameters, and it does: limit and offset get explicit meaning plus defaults, and uri_pattern is identified as an optional dataset URI filter. The remaining gap is that uri_pattern's matching syntax (glob, regex, exact) is not specified.

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?

States a specific verb and resource ("Lists all datasets in the Airflow system") and adds a version qualifier that disambiguates the v1 datasets concept from v2 Assets. It does not explicitly distinguish itself from siblings like get_dataset or list_dataset_events, but the listing scope is unambiguous.

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 v1-only / v2-uses-Assets note gives environment-level guidance about when this tool applies. However, there is no explicit routing advice such as "use get_dataset for a single dataset" or "use list_dataset_events for events," leaving alternative selection to inference.

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