Dataset query

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. 'Query' implies a read, but nothing confirms read-only semantics, whether the dataset object must be pre-fetched, or what the call returns; for a zero-annotation tool this is a substantial gap.

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?

A single short sentence with the resource and scope front-loaded and no filler. It is terse to the point of under-specification, but nothing in it is wasted.

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 no annotations, no output schema, and no explanation of the returned shape, the description is too thin for a 3-parameter query tool. An agent still cannot tell what a listing versus a named lookup yields, or how the dataset_obj must be obtained before calling.

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 100%, with kind (enum), name ('omit to list'), and dataset_obj ('from get_results/dataset') all documented, so baseline 3 applies. The description adds no syntax or semantic detail beyond the schema.

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 (Query) and resource (parameters or attributes on a dataset object), so the agent knows exactly what is being read. The parenthetical '(not fd_instance)' scopes the target object type, though fd_instance is never defined and is not a sibling tool, so the differentiation is only partly useful.

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 gives no guidance on when to reach for this versus get_info, get_results, or object_action. The only usage hint ('omit to list') lives in the schema, not the description, and there is no statement of prerequisites or exclusions beyond the cryptic fd_instance note.

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