search-metric-volumes

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

No annotations provided, description carries full burden. It states the tool searches with volume and ingestion data but gives no details on pagination, rate limits, side effects, or interpretation of volume. Minimal behavioral context.

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 concise sentences: first states function, second lists use cases. No fluff, front-loaded with key information.

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?

Adequate for a search tool with 5 parameters but no output schema or annotations. Lacks details on parameter interactions (e.g., AND/OR logic, defaults, pagination). Could be more complete.

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 100%, so baseline is 3. Description does not add additional meaning beyond the schema; it only mentions 'metric name pattern' which maps to filterMetric. No extra parameter insights.

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 verb (search) and resource (metrics by name pattern with volume and ingestion data), and provides example use cases. It distinguishes from siblings like 'query-metrics' by mentioning volume data, but lacks explicit differentiation.

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'. However, it does not specify when not to use or mention alternatives.

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