nexo_cognitive_metrics

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

With no annotations provided, the description does not disclose behavioral traits such as read-only nature, side effects, authentication needs, or error handling. It only states it returns metrics, which is minimal for safe invocation.

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 efficiently states the purpose and specifies key metrics. The reference to 'spec section 9' is cryptic but not overly wasteful. It is concise and front-loaded with the main 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 no output schema and one simple parameter, the description could provide more detail on the return format, units, or how to interpret the metrics. The vague 'spec section 9' reference does not compensate for this lack of completeness.

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 single parameter 'days' is already fully described in the input schema (coverage 100%). The description adds no extra meaning or context about the parameter, so it meets the baseline without improvement.

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 specifies the tool provides 'Performance metrics' and lists three concrete metrics: retrieval relevance %, repeat error rate, multilingual recommendation. This differentiates it from sibling cognitive tools, though 'performance metrics' is still somewhat broad.

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 on when to use this tool vs alternatives like nexo_cognitive_stats or nexo_cognitive_inspect. The description does not specify conditions, prerequisites, or exclusions, leaving the agent without context for selection.

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