Get usage summary

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

Annotations already provide readOnlyHint=true, so the description builds on that by detailing pagination, a cap on events, and the return fields (total count, product area breakdown, spend). It also notes that spend is conditional on API reporting. This adds meaningful behavioral context beyond the annotation.

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?

Three sentences covering purpose, filters, pagination, and return values. No fluff, front-loaded with key information. Every sentence adds value.

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 tool has 10 optional parameters and no output schema, the description explains the main return values and pagination behavior. It misses details on some filters (e.g., 'failed', 'product_area') but overall provides a sufficient understanding of what the tool does and returns.

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 description groups parameters into categories (time range, simulation, scenario, job) but does not explain individual parameters like 'failed' or 'product_area' beyond what the schema already provides. With schema description coverage at 60%, the description only partially compensates.

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 tool summarizes VerifyAX usage events with optional filters, using a specific verb and resource. It distinguishes itself from siblings like list_scenarios or get_run_details by focusing on aggregation (count, breakdown, spend) rather than listing raw events or runs.

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 description implies when to use the tool: for a summary over a time range or for specific simulations, scenarios, or jobs. It does not explicitly state when not to use or name alternatives, but the context is clear. No exclusion criteria are provided.

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