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

With no annotations, the description carries the full burden. It discloses important behaviors: condition=refurbished/used only filters source-declared enabled offers, never infers condition from price/text, default availability=available, and AutoID stock is prioritized over distribution-only stock. This goes beyond the schema and gives the agent critical operational knowledge. It doesn't mention pagination or rate limits, but the schema covers limit/offset defaults.

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 core purpose. Every sentence adds value: the first states what it lists, the second explains the condition contract, the third clarifies filter semantics, the fourth states defaults, and the fifth explains stock prioritization. It's slightly dense but not bloated. Could be improved by separating the stock prioritization into a 'Notes' section, but it's still well-structured.

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 list tool with 5 params, no output schema, and no annotations, the description covers the key behavioral nuances: condition filtering, availability defaults, and stock prioritization. It doesn't describe the return shape (e.g., whether it returns offers per SKU or just SKU strings), but the tool name and purpose imply SKU listing. The absence of output schema raises the bar, and the description mostly meets it, though a note on response structure would make it 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?

Schema description coverage is only 20% (only 'model' has a description). The description compensates by explaining the semantics of condition and availability filters, including the 'never infers condition' rule and the stock prioritization behavior. It doesn't explicitly explain 'autoid' vs 'supplier' availability values, but the description's context about AutoID stock prioritization helps. This is strong compensation for a low-coverage 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 states a specific verb ('Lists'), a specific resource ('exact SKUs belonging to an AutoID grouped product'), and distinguishes it from siblings like list_products and get_product_offer. It also clarifies the relationship to the canonical API's condition contract, which makes the tool's purpose unambiguous.

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 on when to use this tool (for AutoID grouped products, exact SKUs) and explains filtering behavior for condition and availability. It doesn't explicitly name alternative tools or say 'use X instead', but the sibling list and the specificity of 'AutoID grouped product' imply the right context. A small gap: no explicit exclusion of non-AutoID products or direction to list_products for those.

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