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

Annotations only cover readOnlyHint and openWorldHint. The description adds genuinely useful behavioral detail beyond them: description and the full image gallery are best-effort, every other field is guaranteed, and an unknown pv yields a not-found error. This reliability and error contract is exactly what annotations don't provide.

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?

Three tight sentences, front-loaded with what the tool returns, then where pv comes from, then the reliability caveats. No filler; every clause conveys actionable information.

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 single-param read tool with an output schema and readOnly/openWorld annotations, the description covers purpose, parameter provenance, field-guarantee caveats, and error behavior. Nothing an agent needs to call it correctly is missing.

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 coverage is 100%, so the baseline is 3, but the description goes further by documenting where pv originates (search, category, or the tool's own products[].pv and other_colors[] fields), which the schema only gestures at generically. That added lineage meaning lifts it above baseline.

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?

States a specific verb+resource ('Normalized product-detail data for one Prada product/color variant') and enumerates the returned fields, which uniquely distinguishes it from prada_search, prada_category, and prada_suggest. An agent can tell immediately this is the singleton detail fetch, not a list/search tool.

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?

It explains the pv lineage - returned by prada_search's, prada_category's, and its own products[].pv/other_colors[] fields - which effectively tells the agent this is the follow-up call after a search or category browse. It doesn't state explicit exclusions, but the sourcing chain gives clear usage context.

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