reset_metrics

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

The description implies a destructive action (reset) but offers no details on side effects, irreversibility, or what gets reset. With no annotations, this is a significant gap in understanding the tool's impact.

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 extremely concise (two words) but may be under-specified. It is front-loaded, but brevity comes at the cost of useful context.

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 presence of an output schema (not provided) and no annotations, the description is insufficient to fully understand the tool's behavior. It does not explain what resetting entails or what happens after.

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 zero parameters, and the schema coverage is 100% by definition. The description does not need to add parameter details. Baseline for 0 params is 4, and the description meets this.

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 ('Reset') and the resource ('all metrics'), making the purpose immediately understandable. However, it does not elaborate on what 'metrics' specifically refers to, which slightly reduces precision.

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?

No guidance is provided on when to use this tool versus alternatives like 'metrics' (which likely reads metrics). The description lacks context about prerequisites, scenarios, or comparisons.

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