query_measurements

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the basic safety profile is covered. The description adds some behavioral context by mentioning cursors and reviewed filters, but it does not disclose details like return format, pagination behavior, or any constraints that go beyond the annotations. No contradiction exists.

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 a single sentence with the verb front-loaded, and it avoids unnecessary words. It is appropriately concise for a read-only query tool, though it could trade some brevity for parameter detail without becoming bloated.

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 six optional parameters, no parameter descriptions, and an output schema that is not visible to the agent, the description is insufficient. It does not explain what 'normalized measurements' are, how cursor-based pagination works, or what the returned data looks like. An agent would have to guess the meaning of run_id, artifact_id, and other fields.

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?

With 0% schema description coverage, the description carries the full burden of explaining parameters, but it only generically refers to 'filters and cursors' without naming or describing any of the six parameters (limit, cursor, run_id, artifact_id, name_prefix, include_warmups). It does not help an agent understand which filter to use for what purpose, so parameter meaning remains opaque.

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 clear action ('Query') and resource ('normalized measurements'), which distinguishes it from the many extract_* tools that pull raw data. However, it does not name sibling query tools or specify what makes these measurements 'normalized' or 'reviewed,' so it is clear but not fully differentiated.

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 description provides no explicit guidance on when to use this tool versus alternatives like list_runs or get_artifact, nor does it mention prerequisites or context. The only hint is 'through reviewed filters and cursors,' which implies pagination and filtering but does not explain why this is the right choice.

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