Recalibrer l'importance

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly reveals key guardrails: pinned facts and importance ≥0.9 untouchable, variation capped at ±0.15 per call/pass via passId, and bounds 0.4–0.85. It also explains dryRun behavior ('logue sans appliquer'), which is critical for safe usage.

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, with the primary action stated first. The list of safeguards is dense but each phrase carries meaningful information. The final warning is direct and effective. No redundant or filler content.

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 description covers the tool's purpose, constraints, dryRun behavior, and usage boundaries well. However, since there is no output schema, it does not mention what is returned on success or failure, which would be helpful for agents to interpret results. Still, the description is quite complete for a recalibration tool with such detailed guardrails.

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 already provides descriptions for all 5 parameters (100% coverage), so the baseline is 3. The description adds value by explaining the cumulative cap via passId and clarifying the +/-0.15 constraint, which is not fully detailed in the schema. It also gives a concrete example for 'reason' ('paire: X bat Y'), enriching the meaning of that parameter.

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 specific action: 'Ajuste l'importance d'une mémoire' (adjusts the importance of a memory). It also explicitly distinguishes this from writing a fact with 'Ne pas utiliser pour écrire un fait — uniquement pour recalibrer', setting it apart from sibling tools like memory_add.

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 provides explicit guidance on when to use the tool: for recalibration only, and explicitly warns 'Ne pas utiliser pour écrire un fait'. This exclusion is clear and directly addresses alternatives, even though it does not name sibling tools explicitly. The mention of 'calibrage par le sub-agent de scoring, comparaisons par paires' gives context for the intended use case.

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