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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuine behavioral value by disclosing the progressive depth of returns (overview → per-result → full reasons and remediation) and that level only filters within a named example. It says nothing about caching, availability, or failure behavior, so it sits at solid adequacy rather than richness.

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?

Four short sentences, front-loaded, each tied to a distinct calling mode with zero filler. The telegraphic phrasing 'result by result (level filters by light)' is slightly awkward to parse but costs nothing in length.

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 four optional parameters and no output schema, the description carries the burden of explaining return shapes, and it does so for all three modes including what the deepest result contains. The lang parameter's effect is only documented in the schema, which is a minor gap for an otherwise complete definition.

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 coverage is 100%, so the baseline is 3, but the description adds real meaning: it reveals that id is meaningless without name (a dependency the schema does not state) and that level scopes to the figures of a named example rather than globally. Only lang is left to the schema entirely.

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 identifies the resource precisely — published example audits such as the AI Project Radar — and its three operating modes make clear it is a retrieval tool. It lacks an explicit verb (get/list), but the mode lines leave no doubt about what it returns.

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?

It gives explicit, argument-conditioned usage: no arguments for the overview and list, a name for one example, a name plus id for a single result. The closing line 'They are not the person's data' implicitly separates it from the sibling audit tools, though it never names show_audit or start_audit directly.

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