get_metric_active_configurations

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 indicates a read operation ('List') but doesn't disclose behavioral traits like authentication requirements, rate limits, pagination, error conditions, or what 'actively queried' means operationally. The description is functional but lacks critical behavioral context for a tool with zero annotation coverage.

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, well-structured sentence that efficiently conveys the tool's purpose without redundancy. It front-loads the key action ('List tags and aggregations') and specifies the scope clearly. Every word earns its place, making it highly concise.

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 has 0 parameters and 100% schema coverage, the description adequately explains what it does. However, with no annotations and no output schema, it lacks details on behavioral traits (e.g., safety, performance) and return format. For a read-only tool with simple inputs, it's minimally complete but could benefit from more context about outputs or usage constraints.

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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description appropriately doesn't add parameter details, as none are needed. It implicitly references 'a given metric name' as context, but since no parameters exist, this doesn't affect the score negatively.

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 specific action ('List tags and aggregations') and the target resource ('that are actively queried on dashboards, notebooks, monitors, the Metrics Explorer, and using the API for a given metric name'). It distinguishes itself from siblings by focusing on active configurations rather than raw metric data or creation/deletion operations.

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 guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid metric name), exclusions, or compare it to similar tools like 'get_metric_tags' or 'get_metric_all_tags' in the sibling list. Usage context is implied but not explicit.

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