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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered and the bar is lower. The description adds genuinely new context: the findings are agent-generated, org-scoped, and span a specific set of detection categories. It stops short of any ordering, acknowledgment-state, or return-shape detail.

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, zero waste, and the core scope statement is front-loaded ahead of the routing hint. Every clause earns its place by naming a distinct detection category.

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 simple, fully-annotated, zero-required-param read tool with complete schema coverage and no output schema, the description covers purpose, scope and trigger adequately. Minor gap: nothing about ordering or default result count, though the schema supplies the default.

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% — limit (default 25, max 200) and the severity enum are fully documented in the schema with sensible defaults. The description adds nothing about filtering or paging semantics, so 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?

States a specific verb (List) plus the resource (findings) and its origin (raised by Aeroz compliance agents watching this organisation). It then enumerates the concrete finding categories — recall hits, DPP gaps, regulatory changes, dwell anomalies, clone detections — which an agent can distinguish from siblings like check_recall or dpp_readiness that each cover only one slice.

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 closing sentence gives a clear situational trigger ('what needs my attention'), which frames when to reach for this aggregate list rather than a point-check tool. However, it names no alternatives and gives no exclusions, so the routing decision against check_recall/dpp_readiness is left to inference.

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