taobao_fetch_product

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

Annotations already declare readOnlyHint and idempotentHint. The description adds value by disclosing the auto-login behavior and the detailed deep_price mechanism (clicking variants, slower, capped at 24 SKUs). This provides the agent with important behavioral context beyond the annotations.

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 an example. It front-loads the core purpose and then provides critical nuance about deep_price. Every sentence serves a purpose with minimal waste.

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 output schema exists, return values need not be explained. The description covers login behavior, parameter semantics, and a key behavioral option (deep_price). It could mention error handling or rate limits, but for a read-only fetch tool, this is adequate.

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?

With 0% schema description coverage, the description fully compensates by explaining the product_url_or_id parameter through an example and clearly defining deep_price's purpose, effect, and performance trade-offs. This adds meaning beyond the raw 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 'Fetch one product' and enumerates the specific data fields: title, shop, every SKU variant with price/stock, specs, images. This verb+resource combination is specific and distinct from sibling tools like search or reviews.

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 explains that login is auto-ensured, eliminating the need for a separate login call. It also provides explicit guidance on the deep_price parameter: when set true, it clicks each variant for live subsidy prices, is slower, and is skipped if more than 24 SKUs. This helps the agent decide when to use that option. However, it does not compare directly to sibling tools for when to use this tool vs. alternatives.

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