Create DataLens REST catalog

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

Annotations only declare non-read-only/non-idempotent/open-world; the description adds materially new context beyond them — cost/billing side effect requiring user consent, asynchronous operation semantics, and the caveat that the endpoint is experimental, written from docs, and never invoked/measured. That last point is unusually valuable for an agent deciding whether to trust the call.

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?

Front-loaded with the purpose, then the billing warning and polling workflow, then the experimental caveat — a sensible order with little waste. The phrasing "make ... the operation that makes it" is slightly awkward but not harmful.

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 output schema, the description usefully explains that the return is an operation and how to poll it, and it flags the billing side effect for this 5-param nested-object tool. Coverage is good though it does not detail the operation object's contents, which is left to lakehouseoperations_get.

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%, so every parameter (including the nested bucket_settings fields) is already documented in the schema. The description adds no parameter-level detail, so the baseline of 3 applies.

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 states a specific verb+resource ("Make a REST catalog") and adds a distinguishing behavioral note that it returns an async operation handle rather than the finished catalog. It does not explicitly contrast with nearby siblings like datalens_restcatalogs_list or datalens_trinoclusters_catalog_create, so sibling differentiation is only implicit.

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?

Strong, actionable guidance: it warns that a cloud bucket is created and may be billed, instructs to ask the user before calling, and directs the agent to poll lakehouseoperations_get until "done". It does not name when to prefer this over other catalog-creation tools, so it is clear context without explicit alternatives.

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