data_analyze_dataset

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

Annotations already carry destructiveHint=true, openWorldHint=true, and idempotentHint=false, and the description does not contradict them. It adds useful context about the dispatcher routing and JWT/tenant/company scoping, but it does not disclose side effects, failure modes, or operational risks beyond what annotations already imply.

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 description is short, front-loaded with the operation, and uses a clear Args section. Every sentence adds relevant information, with no filler or repetition of schema details.

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?

Although an output schema exists and return values need no explanation, the description does not say what `analyze_dataset` actually does, when it should be used, or how it relates to the many sibling data-domain actions. For a destructive-capable, open-world tool, this is a notable completeness gap.

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 burden of explaining parameters. It does so for both: `message` is a free-text objective and `inputs` is an optional JSON string of structured inputs. This adds meaning beyond the bare schema, though the exact structure of `inputs` is left vague.

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 clearly states the operation: run the `analyze_dataset` domain-agent action, and adds context that it routes through the platform's dispatcher under the caller's JWT, tenant, and company scope. It does not differentiate from sibling data tools like `data_profile_dataset` or `data_discover_data`, so it falls short of top marks.

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 guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The description only states routing and scope, leaving the agent to infer when `analyze_dataset` is preferable to similar data-domain tools.

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