get_loyalty_coupons_dashboard

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

No annotations are provided, so the description carries full burden. It discloses the authentication requirement and read-only 'Retrieves' nature, but does not describe error behavior, potential empty results, or side effects. For a simple read operation, this is acceptable but not comprehensive.

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 concise (two sentences) and front-loaded with the action, immediately stating what it does and what it returns. It wastes no words and is well-structured for an agent to parse quickly.

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?

This tool has no input schema and no output schema. The description compensates by specifying all returned metrics (count of coupons, total amount, coupons in cart) and the authentication prerequisite. For a read-only summary tool, this is sufficiently complete.

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 tool has 0 parameters, and the description adds no parameter semantics (there is nothing to add). However, it explicitly lists the return values, which is useful. The baseline for 0 params is 4, and the description does not overspecify, so a 4 is appropriate.

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 it retrieves a loyalty coupons dashboard summary for the authenticated user on Carrefour France, specifying the three data points returned. It distinguishes itself from sibling tools like get_loyalty_coupon_collection (which likely returns a detailed list) by focusing on a concise overview.

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 clear context: 'Useful for displaying a quick overview of the user's loyalty coupon status.' It does not explicitly mention when not to use it or alternative tools, but the context of a quick overview is sufficient guidance. However, it lacks explicit exclusions or mention of more detailed tools.

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