List Datasets

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing: no indication of whether this is a read-only enumeration, whether results are paginated, whether authentication or a project context is required. The presence of an output schema covers return shape, but the behavioral profile is essentially undocumented.

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?

It is a single short fragment with no wasted words, but it is under-specified rather than genuinely concise — the brevity comes at the cost of missing guidance and parameter meaning. Front-loading is fine given the length.

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 list tool with one undocumented boolean parameter, no annotations, and no usage guidance, the description leaves the agent short of what it needs to invoke the tool correctly. The output schema excuses it from explaining return values, but the only_on_disk semantics and its interaction with the listing are still missing.

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% and the single parameter only_on_disk (boolean, default true) is left completely unexplained in both schema and description. The description never mentions filtering or disk state, so an agent has to guess what the flag does and that it defaults to true.

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 identifies the resource precisely (curated public EEG datasets / MOABB packs) and its scope (available to pipelines), which helps distinguish it from siblings like inspect_dataset. However, it is a noun phrase rather than a verb+resource statement, so it never explicitly says the tool lists or returns them — the agent must infer the action from the name.

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?

There is no statement of when to use this tool, when not to, or how it relates to inspect_dataset, which is the obvious adjacent sibling. No prerequisites or context for choosing it are given.

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