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

Annotations already declare the tool as readOnly, idempotent, and non-destructive. The description adds beyond annotations by stating the advice is 'conseils concrets issus des données et guides Izifete.' It does not contradict annotations and provides some context about the output source and nature, though it could mention limitations (e.g., no legal guarantee). Overall, it adds value beyond the structured metadata.

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 description is three sentences, front-loaded with the core purpose and usage condition. Every sentence serves a purpose: defining the audience, listing example topics, stating the output source, and providing exclusions with alternative tools. No redundancy or fluff.

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?

The tool is simple (one parameter, no output schema), and the description fully covers it: when to use, what it does, what it returns, and when not to use. It includes targets audience, example queries, and exclusions. No missing critical context for correct invocation.

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 schema already covers the single parameter 'question' with a clear description and min/max lengths. The tool description adds value by providing specific example questions and reiterating the expected domain. This extra context helps the agent formulate valid queries, going beyond the schema's generic 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?

The description clearly identifies the tool's purpose: providing business advice to French event industry professionals (DJ, caterer, photographer, etc.). It specifies the exact audience (PROFESSIONNEL de l'événementiel) and the type of queries (finding clients, pricing, legal obligations). This clearly distinguishes it from sibling tools like conseils_evenement, which serves individuals.

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 description explicitly states when to use the tool ('Utilise cet outil quand l'utilisateur est un PROFESSIONNEL...') and lists concrete example questions. It also explicitly says when NOT to use it, naming the alternative tool (conseils_evenement) and other excluded cases (creating a profile or request). This is exemplary guidance.

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