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

Annotations already declare the operation read-only, idempotent, and non-destructive. The description adds valuable behavioral context by explaining that the tool reports freshness state, including counters and policy, and frames it as a pre-check before asserting currency. No contradiction with annotations exists.

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 two sentences with no filler. The main purpose is front-loaded, and the usage note is compact and relevant. Every word earns its place.

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 optional parameter and no required inputs. The description states what the tool returns, and an output schema exists to provide structured return details. Nothing necessary for calling the tool correctly is missing.

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 input schema fully documents the single optional limit parameter with default, minimum, and maximum, so schema coverage is 100%. The description does not mention limit, but the schema carries the full semantic burden and the description does not need to compensate.

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 uses a specific verb ('Renvoie') and resource ('fraîcheur du corpus l0g'), then enumerates what the tool returns: latest contents, counters, available endpoints, and freshness policy. This clearly separates it from siblings like get_changes or get_changefeed, which focus on content changes rather than corpus freshness metadata.

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 gives explicit guidance: call this tool before presenting a snapshot as current. This is a clear, actionable usage context. It does not enumerate when not to use the tool or name alternatives, but the stated use case is sufficient for most decision-making.

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