get_system_metrics

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

No annotations provided, so description must cover behavior. It correctly implies read-only ('Exibe'), but does not disclose potential performance impacts, authorization needs, or data freshness. The list of metrics adds some transparency.

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?

Two sentences, no extraneous words. Front-loaded with main verb ('Exibe') and resource ('métricas de evolução'). Every word serves a purpose.

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 no output schema, the description adequately conveys what the tool returns. Lacks details on authentication, caching, or data scope but is sufficient for a simple read operation.

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?

No parameters exist; schema coverage is 100%. Description compensates by fully explaining the output (metrics shown). Exceeds baseline of 3 by providing meaningful return value details.

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?

Description clearly states the tool displays system evolution metrics, listing specific items (total interactions, quality score, trend, individual performance). Distinguishes from sibling tools like 'analyze' or 'generate_documentation' which have different purposes.

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 explicit guidance on when to use this tool vs alternatives. However, the purpose is clear enough that an agent would infer usage for retrieving system metrics, but lacks exclusions or context-specific advice.

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