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

The description fully discloses the tool's behavior: it sends a 6-digit code to the customer's email, requires a subsequent call to confirm_quote, and discards the request if not confirmed. No annotations are provided, so the description carries the burden and does so comprehensively.

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 somewhat lengthy due to bilingual content, but it is well-structured, front-loads key points (two-step, real data), and uses clear warnings. Every sentence serves a purpose, though it could be slightly more concise.

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?

Given the complexity of the two-step verification process and the strict data-validation requirements, the description is remarkably complete. It covers the entire workflow, prerequisites, and consequences, leaving no critical gaps.

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?

While the input schema already has descriptive parameter comments (100% coverage), the description adds process-level context: it explains why each required parameter is real data and their roles (email for code, phone for callback). This adds value beyond the schema.

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 purpose: submitting a real quote request via a two-step email verification process. It distinguishes itself from sibling tools by mentioning the follow-up tool confirm_quote and contrasting with other tools like get_price_estimate and list_inventory.

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: only when the user explicitly requests an actual quote and provides real personal details. It warns against using placeholder data and tells the agent to call confirm_quote after obtaining the verification code.

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