Datasets List Data Models

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

Annotations already declare this a safe read (readOnlyHint=true, destructiveHint=false), but the description adds real behavioral information the annotations cannot: it auto-paginates to the last page, so nextPage is always null and hasMore always false. That disclosure is valuable because an agent might otherwise write pagination loops. It stops short of warning about cost/latency for very large orgs, which would raise it further.

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 action and the most useful knob (summary_only) are front-loaded in the first sentence. The following sentences explain pagination semantics compactly, and no sentence is filler, though the parenthetical about hasMore/nextPage is denser than it needs to be.

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?

An output schema exists, so the return-shape explanation is mostly bonus, but the explanation of pagination behavior does add meaning beyond the schema. With annotations covering the safety profile, the only meaningful gap is the failure to distinguish this tool from datasets_list_all_data_models, a notable omission in a very crowded sibling set.

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 carries the full burden, and it does address both parameters: 'limit' is identified as the page size and 'summary_only' is explained as producing a concise, token-efficient response. It does not describe what the concise form omits or how limit interacts with the auto-pagination, so the compensation is partial rather than complete.

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 with scope ('List all data models in the organization'), which is unambiguous on its own. However, the sibling list contains both datasets_list_data_models and datasets_list_all_data_models, and the description never explains how they differ, leaving an agent to guess which list tool to pick.

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?

Gives one actionable usage hint ('Pass summary_only=True for concise token-efficient response'), which implies when to use the compact mode. It offers no guidance on when to choose this tool over datasets_list_all_data_models or the narrower datasets_list_data_model_* siblings, so selection across siblings is left to inference.

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