inspect_dataset

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does add transparency by naming the prerequisite (dataset must be registered) and all the return contents, but it does not explicitly state that inspection is read-only, requires no special permissions, or has no side effects. The verb 'inspect' implies safety but does not fully guarantee it.

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 only two sentences with no filler. It is front-loaded with the primary action and then states the output. Every phrase adds value and none is tautological.

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?

Given a simple single-parameter tool with no output schema, this description is nearly complete: it explains what to pass, when to use the tool, and what will be returned. The only noticeable gap is not specifying the structure or format of the returned fields, but the output schema is absent, so the agent can still make a correct call with the identifier information.

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 coverage is 0% for dataset_id, so the description must compensate. It explains that the dataset must already be registered, which gives dataset_id the essential context that an ID of an already-registered dataset is expected. It could have elaborated on where to find this ID, but the core need is met.

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 ('inspect'), a specific resource ('a registered dataset'), and a clearly scoped purpose ('before MMM configuration'). It also enumerates the output (candidate targets, channels, controls, frequency, and data issues), which distinguishes it from siblings like register_dataset or validate_dataset.

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 phrase 'before MMM configuration' establishes a precise temporal and functional context, telling the agent exactly when this is the right tool. However, it does not explicitly point to alternatives or provide any 'when not to use' guidance, which would cap the score at 5.

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