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

The description frames the tool purely as a read ('Read a product or app listing', 'It does not create a survey'), while the annotations declare readOnlyHint=false and destructiveHint=true. Nothing in the text explains what could be destructive, whether the lookup consumes credits, or why it is non-idempotent, so the agent is left with a direct conflict between prose and structured hints. The annotation_contradiction flag applies.

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?

Purpose and the anti-pattern (web page fetch) are front-loaded, followed by source rules and then the downstream mockup-template mapping. The trailing sentences about list_mockup_templates/save_survey are dense but each carries actionable routing information rather than filler, and no sentence merely restates the schema.

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?

With an output schema present the description needn't document return shape, and it still explains the field-provenance model ('each field carries the provider that filled it; a field the store did not return is absent'). For an open-world, multi-source lookup the only missing pieces are failure behavior (unsupported store, not-found listings) and the cost/side-effect question raised by the annotations.

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 already 100%, so the baseline is 3, but the description adds real semantics beyond the schema: source must be omitted only when the link's host names the store while a bare id requires it, and a region embedded in the link overrides the explicit region parameter. Only the region default (US) is left purely to the schema, so the added value is genuine if not exhaustive.

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 opening sentence names a specific verb and resource ('Read a product or app listing from its store by id or link') and enumerates the returned fields: title, images, price/currency, rating, ratings count, description, store-specific fields. It also carves out a clear boundary against the obvious alternative ('instead of fetching the web page, which misses details the store renders with JavaScript') and lists the supported sources. An agent can distinguish it from siblings like extract_images or list_mockup_templates without opening any schema.

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?

Explicit when-to-use ('when the user names a listing and you need what it shows'), an explicit when-not (don't scrape the web page), and an explicit parameter dependency rule (omit source only when the reference is a link whose host identifies the store; a bare id needs source). It even routes downstream: an Amazon result fills one row on the amazon-search mockup template, with the exact field mapping and pointer to save_survey for the steps, plus a negative scope statement ('It does not create a survey').

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