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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so safety is covered. The description adds value beyond them by disclosing the return payload's shape (per-language and per-difficulty counts, repeat-clicker course assignment, QR-code totals), which matters because there is no output schema. It does not mention caching or size, but for a small lookup that is minor.

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 preamble, with the payload contents front-loaded and the sibling linkage placed last where it acts as a next-step pointer. The middle enumeration is dense but every item maps to a real returned field rather than padding.

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 one-parameter, no-output-schema, read-only lookup, the description covers both what comes back and how the result feeds another tool. Nothing an agent needs in order to call this correctly and use the response is missing, aside from the minor language-scope nuance.

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% and the single `language` parameter is fully documented with an enum and default, so the baseline of 3 applies. The description says counts are broken out 'per language' but never clarifies whether the `language` parameter controls labels only or filters the returned counts, which is the one ambiguity the schema does not resolve.

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 resource (phishing simulation template categories) and immediately enumerates its contents: key, label, counts per language and difficulty, repeat-clicker course, and total/QR-code counts. That specificity is enough to distinguish it from siblings like list_simulation_templates or get_overview without opening a schema.

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 second sentence explicitly ties this tool to a sibling: 'The category keys are the values accepted by the category filter of list_simulation_templates.' That gives the agent a concrete discovery-then-filter workflow. It stops short of a full when/when-not statement (e.g. does not say whether to call this before or instead of list_courses for course data), so it is clear context rather than exhaustive routing.

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