search-metric-volumes

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

No annotations are provided, so the description carries the full burden. It implies a read-only search but does not explicitly confirm non-destructive behavior, authentication needs, or rate limits. The lack of behavioral details is a gap, but 'search' suggests safety.

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?

Two sentences with no wasted words. The first sentence states the core action, and the second provides usage examples. Excellent structure and front-loading.

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?

Describes purpose and usage examples clearly. With 5 optional parameters and no output schema, a bit more detail on what 'volume and ingestion data' includes would be beneficial. However, the context from siblings and schema is sufficient.

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 100% with descriptions for all 5 parameters. The description adds little beyond mentioning 'volume and ingestion data', which hints at the windowSeconds parameter. Baseline 3 is appropriate as the schema already documents parameters thoroughly.

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?

Description clearly states the tool searches metrics by name pattern and returns volume and ingestion data. It gives specific usage examples, effectively distinguishing it from siblings like query-metrics or list_metric_tag_configs.

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 lists use cases: 'find metrics matching pattern', 'metric ingestion volume', 'what metrics are configured'. Lacks explicit when-not-to-use or alternatives, but the examples provide clear guidance.

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