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

The description discloses that the operation is audited and that evidence is replaced or added, which are important behavioral traits. However, it does not mention permissions, failure modes, or consequences for inactive memories, leaving some transparency gaps given the absence of 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 two short sentences, front-loaded with the primary action and accompanied by a concise audit note. There is no fluff or redundancy, making it highly efficient.

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?

With no annotations or output schema, the description is not complete enough. It lacks context about when to use the tool, the purpose of the reason parameter, and what constitutes an 'active' memory, leaving an AI agent with insufficient guidance 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 input schema only describes one parameter (evidence), and the description adds no meaningful detail about the required 'id' or optional 'reason'. The phrase 'preuve courte' only reinforces the existing schema description, so parameter semantics are minimally enhanced.

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: marks an active memory as verified and replaces or adds its evidence. This distinguishes it from other memory tools like memory_add or memory_score, and avoids tautology.

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 no explicit guidance on when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. It only implies usage for verifying memories, which is not enough direction for an AI agent.

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