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 reveals the conditional billing logic (if billing address differs, set billing_* fields; if not, use delivery address) and enumerates payment options with their corresponding provider values. It also discloses the order of actions (ask questions, then create cart). It does not mention side effects or error behavior, but the core behaviors are well covered.

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 moderately sized but well-structured. Each sentence adds value: purpose, fields set, billing logic, and prerequisite questions. The use of numbered questions improves readability. While slightly lengthy, it avoids redundancy and includes only relevant operational details.

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 complex tool with 17 parameters, no output schema, and no annotations, the description provides comprehensive contextual guidance: it explains the core action, conditional billing behavior, and the necessary customer questions. The only gap is the lack of information about the return value or next steps after cart creation, but this is a minor omission given the absence of an output schema.

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?

Although the input schema already describes all 17 parameters with 100% coverage, the description adds meaningful context beyond the schema. It explains the conditional relationship between billing and shipping addresses, and it maps payment provider enum values to user-facing options (Kreditkarte/Apple Pay/Google Pay to stripe, etc.). This semantic enrichment helps the agent correctly populate parameters.

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: 'Legt einen Warenkorb bei Blumen Komander an und fügt einen Blumenstrauß hinzu' (creates a cart and adds a bouquet). The verb 'Legt an' is specific and resource-oriented, and it lists the fields set. It is distinct from sibling tools like check_availability, get_checkout_link, and search_flowers, which serve different functions.

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 usage context by instructing the AI to ask two prerequisite questions before creating the cart (billing address match, payment method preference). It does not explicitly mention when not to use this tool or alternatives, but the sibling tool list makes it clear this is the only cart-creation tool. The prerequisite questions serve as clear when-to-use guidance.

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