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

Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=false, so the safety profile is fully covered. The description contributes real domain meaning by defining 'failure' as a refused presentation and enumerating reason categories, but discloses nothing about result shape, grouping effects, or mode behavior.

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?

A single front-loaded sentence that defines the metric and immediately grounds it with examples. No filler, no restatement of the tool name, nothing wasted.

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?

For a 5-parameter, zero-required read tool with no output schema, the description covers the subject well but leaves the returned structure undefined and gives no routing advice among the four sibling analytics tools. Adequate, but an agent still has to guess at output shape and when this beats get_breakdown.

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?

Schema description coverage is 100% with 5 optional parameters, each carrying date, mode, group_by and project_id semantics in the schema itself. The description adds no parameter-level information (e.g. how group_by reshapes rows), so the schema does all the work and the baseline 3 applies.

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 names the specific dataset ('refused presentations') and the aggregation ('by reason category'), and the parenthetical examples (wallet declined, issuer not trusted, expired credential) make the subject concrete. It contrasts implicitly with the sibling get_breakdown by scoping to refusals, though it never states that distinction outright.

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?

There is no explicit when-to-use guidance, no prerequisites, and no alternative named. The agent must infer from the name alone that this is the failure-specific counterpart to get_breakdown, with nothing in the text to confirm that choice.

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