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

Annotations already establish that this is a safe, read-only, idempotent, closed-world listing. The description adds useful domain context, namely that the list is specific to France and that each profession maps to a slug usable by sibling tools. It does not describe return format or pagination, but with these annotations the remaining gap 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?

The purpose and France scope are front-loaded, followed by a few examples and a clear downstream usage note. Every clause is useful and there is no filler.

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-only list tool with no output schema, the description provides enough to call it correctly: what is listed, the jurisdiction, representative examples, and how the returned profession slugs are used.

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 parameter semantics are inherently trivial and the schema has nothing to explain. The description correctly adds no parameter detail, matching the empty schema.

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?

Uses a specific verb ("Lists") and resource ("professions") with clear geographic scope ("France"), and examples of professions make the content concrete. It also implicitly distinguishes the tool from siblings by explaining that its output slugs are consumed by get_profession_signature_rules or generate_email_signature.

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?

Clearly tells the agent what to do after calling it: use a slug with get_profession_signature_rules or generate_email_signature. It does not explicitly say when not to use it or contrast it with alternatives, but the downstream usage context is strong.

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