gauge_report

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

No annotations are present, so the description must convey behavior. It discloses that the tool returns average metrics and improvement recommendations, but it does not clarify whether it modifies any state or its safety profile. This is minimal but not misleading.

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 two sentences, front-loaded with the primary action, and every sentence adds value (purpose and output). No filler or redundancy.

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?

For a one-parameter tool with no output schema, the description provides a high-level explanation of the output ('平均メトリクスと改善推奨事項'). It is sufficient for a basic understanding, though it could elaborate on the exact nature of the metrics or error handling.

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 covers 100% of the parameter (trace_ids) with a description indicating the list of trace IDs. The tool description does not add extra semantic detail about the parameter beyond what the schema states, so it scores at the baseline for high schema coverage.

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 a specific verb ('生成する' - generates) and resource ('統合レポート' - integrated report) from multiple trace sessions, distinguishing it from siblings like gauge_compare or gauge_evaluate by focusing on aggregation and recommendations.

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 generating a combined report from trace sessions but does not explicitly state when to use it over alternatives or when not to use it. No exclusion criteria or sibling comparisons are provided.

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