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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so safety is covered. The description still adds real value by disclosing that only *public* entries are returned and by naming the three returned fields — important since no output schema exists. It leaves out ordering and whether the category list is nested, which is a minor gap.

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 with the verb first and no filler. Every clause (public scope, resource, returned fields) carries information an agent needs.

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 no-parameter read tool with full annotation coverage, the description supplies what the annotations cannot: the scope filter (public) and the return shape. Only a gloss for the untranslated '节日' and a hint about result size/ordering would make it fully self-contained.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; baseline is 4 by rule. The input schema is an empty object with additionalProperties=false, consistent with the description.

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?

A specific verb ('List') applied to a specific resource ('the public 节日 taxonomy group'), plus an enumeration of what comes back (name, slug, categories). It doesn't distinguish itself from the many sibling list_* taxonomy tools (list_themes, list_groups, list_types), so an agent must infer that each targets a different taxonomy vocabulary.

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?

Usage is only implied: an agent can infer this is the lookup for the festivals vocabulary, presumably to resolve slugs/IDs before filtering works. There is no explicit statement of when to prefer it over list_themes or list_groups, nor any note about prerequisites or follow-up calls.

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