get_revenue_insights

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

With no annotations, this description carries the full disclosure burden. It implies a read-only query but doesn't explicitly state side effects, data scope, or output behavior, offering only a minimal observation about profitability.

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?

One sentence, each word adds value. 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?

The tool is simple and the description adequately conveys its purpose. While it could mention performance limits or return format, these are likely implied by the simplicity. It's complete enough for an agent to infer usage.

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?

Zero parameters mean the schema already fully describes them (empty). The description adds value by implying the tool returns a comparison, but no parameter docs are needed since there are none.

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 specifies the action ('most profitable vs. least profitable classes') and the resource ('classes by revenue'). It distinguishes from sibling tools like get_cluster_metrics or get_classification_metrics by focusing on profitability analysis.

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. The description doesn't mention prerequisites, frequency, or any context for selection, leaving the agent to infer.

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