metrics_metric_summary

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

No annotations are provided, so the description carries full responsibility. It indicates a read-only operation returning a summary dict but does not disclose any side effects, authentication needs, or performance considerations. It is adequate but lacks extra 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?

The description is a single sentence that conveys all necessary information efficiently. It is front-loaded with the purpose and includes output structure. No extraneous words.

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 zero parameters and an output schema that likely defines the return structure, the description adds value by specifying the dict keys and values. It is complete for a tool of this simplicity.

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 zero parameters, so the description does not need to explain parameter meaning. It correctly states no input is required, and the output format is described. With 0 parameters, baseline is 4, and the description meets expectations.

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 (Get a summary), the resource (all metrics), and the output format (single dict with keys as metric names and values as state dicts). It distinguishes from sibling tools like metrics_metric_get or metrics_metric_list by emphasizing it returns a summary of all metrics.

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 usage for obtaining an overview of all metrics but does not provide explicit guidance on when to use this tool versus alternatives (e.g., metrics_metric_list or metrics_metric_get). No exclusions or contextual comparisons are mentioned.

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