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

Annotations already declare readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds return-structure detail (brief user summary vs. full assistant detail), debug telemetry behavior, and the constraint that dataflow_id is not a dataset_id. These go beyond the annotations and help the agent understand output handling and debugging.

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 front-loaded with the one-sentence purpose and call example, then return info, usage guidance, and a structured args block. It is slightly verbose for the args section, but the format is clear and each sentence earns its place.

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 an inspection tool with no output schema, the description fully explains the return value (summary plus full detail), all parameters, usage context relative to sibling tools, and the debug telemetry behavior. Nothing an agent needs to call it correctly is 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%, so the description must fully document all four parameters. It does: agency_id and dataflow_id get examples and clarify the dataflow_id vs. dataset_id distinction; sample explains its role; debug explains when it is populated. This completely compensates for the absent schema descriptions.

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 ('inspect') and resource ('dataflow's dimensional structure and constraint codes'), clearly distinguishing it from siblings like inspect_dataset (which targets datasets) and discover (which finds dataflows). The call example further cements the intended target.

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?

Explicitly places the tool in a workflow: 'drill into a dataflow found via discover before building a query with ask.' This clarifies when to use it relative to discover and ask, and differentiates from inspect_dataset by noting the dataflow_id is not a dataset_id. It does not list explicit when-not-to-use scenarios for all siblings, but the context is strong.

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