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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds behavioral context by explaining that the tool returns unified concept IDs from multiple taxonomies (NAF, Google, LinkedIn), which is useful for understanding the output. It doesn't mention pagination or default limit behavior, but the schema covers the limit parameter. No contradiction with annotations.

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 compact and front-loaded: it states the core function in the first sentence, then the use case, then examples. Every sentence earns its place, and there is no redundant information.

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 (2 params, 1 required, no nested objects) and has an output schema, so the description doesn't need to explain return values. The description covers the purpose, use case, and examples. It could mention the default limit behavior or the exact structure of the returned IDs, but given the simplicity and schema coverage, it is nearly complete.

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%, so the schema already documents both parameters (`q` and `limit`). The description adds a bit of context by showing example values for `q` and explaining the purpose of the returned IDs, but it doesn't add significant meaning beyond the schema. Baseline 3 is appropriate.

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 states the tool's function: autocomplete for ACTIVITÉ/MÉTIER that returns unified concept IDs (NAF + Google categories + LinkedIn industries). It specifies the exact use case (filling the `activity` filter for both people and companies) and gives concrete examples. This distinguishes it from sibling tools like basile_suggest and basile_search_*.

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 says when to use it: 'À utiliser pour remplir le filtre `activity` (people ET companies).' It also provides examples of queries. However, it does not explicitly state when NOT to use it or mention alternatives (e.g., basile_suggest) for other suggestion needs, so it falls short of a 5.

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