query_metrics

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 discloses that the tool returns time-series data and supports specific operators, which is useful. However, it does not explicitly state whether the operation is read-only or describe potential side effects, rate limits, or error behavior. The word 'query' implies read-only, but the absence of explicit safety context leaves some ambiguity.

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 concise, with a front-loaded purpose statement followed by two supporting sentences. Every sentence earns its place, providing syntax compatibility and operator examples without any fluff. It is easy to scan and directly actionable.

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 the tool's complexity, the description covers the essential aspects: what it does, syntax compatibility, and supported operations. The input schema is detailed (100% coverage), and an output schema exists, so return formats are not needed in the description. It could mention time-range defaults or rollup behavior, but those are already in the schema, so the description is sufficiently 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 coverage is 100%, so baseline is 3. The description adds value by explaining the query syntax and listing supported operators (avg, sum, min, max, etc.) and grouping, which goes beyond the schema's individual parameter descriptions. This helps agents construct valid queries using the 'query' parameter.

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 the action ('Execute a metrics query') and the resource ('metrics query'), and distinguishes it from sibling tools like search_logs by specifying time-series metrics data. The verb 'execute' is specific and the scope is unambiguous.

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 implies use for metrics queries by stating it uses the same syntax as the Sumo Logic UI and lists supported operators. However, it does not explicitly mention when not to use it or name alternatives like search_logs or validate_query. The context is clear but lacks explicit exclusions.

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