query-metrics

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

The description indicates this is a read operation that accepts arbitrary Datadog query syntax, but it does not disclose return format, pagination, error handling, or performance implications. Since no annotations are provided, the description carries the full burden, but it only partially meets 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 two sentences: the first states the core purpose, the second adds important detail about query syntax support. No extraneous information—every 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 a query tool with moderate complexity (time range and query syntax), the description does not explain the return value structure, limits, or output format. Since there is no output schema, this is a gap. However, the input parameters are well-documented.

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?

The input schema has 100% description coverage, so the baseline is 3. The description adds value by explaining that the 'query' parameter supports any Datadog syntax and provides an example, which goes beyond the schema's description.

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 it queries time-series metric data from Datadog and supports any Datadog metric query syntax, using a specific verb and resource. This distinguishes it from sibling tools like 'get-metrics' or 'list-active-metrics' which are for listing metric names or metadata.

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?

No guidance is provided on when to use this tool versus alternatives like 'get-metrics' or 'list-active-metrics'. There are no explicit when-to-use or when-not-to-use instructions, leaving it to the agent to infer context from the name and description.

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