find_usage_operation_divergence

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

Annotations already declare readOnlyHint=true, and the description does not contradict this. It adds useful behavioral context by explaining that it computes usage percentiles from raw token totals, compares them to yield percentiles, and returns all 50 operators with divergence classes. This goes beyond the annotation without overpromising side effects.

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 carry full value: the first states the core purpose, and the second explains the method and output. No filler or redundant restatement of the tool name, and key details like 'all 50 operators' and divergence class examples are included efficiently.

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?

With no parameters and an output schema present, the description covers what an agent needs to know: which operators are returned, how divergence is computed, and what categories are produced. There are no configuration choices, side effects, or ambiguous inputs that would require additional context.

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, so the description cannot add parameter-level meaning. The schema already covers 100% of a nonexistent parameter set, making the baseline 4 appropriate. The description focuses on what the computation does, which is sufficient given there is nothing to configure.

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 states a specific verb and resource: 'Find operators with usage-operation divergence.' It also explains the computation involved, distinguishing this from generic get_* siblings by focusing on divergence classification rather than simple retrieval. The mention of specific divergence classes further clarifies the intended output.

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 imperative 'Find operators with usage-operation divergence' clearly indicates when this tool is appropriate: when an agent needs to identify operators whose usage percentile diverges from yield percentile. It does not explicitly name alternative tools or exclusion conditions, but the context is unambiguous enough for an agent to select it correctly from the sibling list.

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