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

Discloses the non-obvious double opt-in flow: it does NOT email the expert, instead sends a confirmation link to the user (valid 48h), only reaching the expert after the click, and Payotte keeps no copy. This goes well beyond the annotations and covers the key behavioral surprise of the tool.

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?

Front-loaded with the ONLY-when trigger, then the opt-in mechanics, then a compact numbered pre-call checklist. Despite its length, nearly every sentence carries distinct operational information and none is redundant with the schema.

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?

For a 9-parameter mutation tool with no output schema, the description covers trigger, mechanism, prerequisites, safety constraints, and what the user should expect afterward. It is nearly complete; only field-level edge cases (e.g., validation failures) are left to the schema's own constraints.

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 a baseline of 3 applies, but the description adds real semantics: it explains the ordering of collected inputs, the consentement=true gating rule, and the warning never to invent contact details. It stops short of clarifying field-level formats, which the schema already handles.

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?

States a precise verb+resource (contact a verified Payotte-listed professional) and immediately distinguishes its trigger from siblings by requiring an explicit user request and pointing to trouver_expert as a prerequisite lookup. An agent can tell exactly what this tool does and when it applies without opening any schema.

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?

Gives explicit when-to-use (only on explicit user request to contact/request a quote), names the alternative (trouver_expert to select the expert first), and lays out a numbered precondition sequence ending in consentement=true. No usage inference is left to the agent.

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