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

Beyond the annotations (readOnlyHint, openWorldHint), the description discloses significant behavioral traits: LLM fallback, cost structure (including free cached results), cache bypass implications, and detailed metadata about provenance, freshness, and abstention. This far exceeds annotations and adds important trust-related context.

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 dense but well-structured: it front-loads the core purpose, then covers cost, metadata, and trust signals in separate clauses. It is longer than average, but every sentence contributes meaningful information, so it earns a 4 rather than a 3.

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 7 parameters and no output schema, the description does a good job explaining the nature of the response (product fields plus _shopgraph metadata). However, it does not enumerate the complete set of returned fields or provide explicit output structure examples, leaving some ambiguity for an agent.

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. The description adds value by explaining cost implications (e.g., free cache, 3x for force_refresh, 2x for minimum_confidence triggers) and the role of verification metadata, which helps agents reason about parameter trade-offs beyond schema descriptions.

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 extracts comprehensive product data from a URL, listing specific fields (name, price, brand, images, availability). It distinguishes itself from siblings like enrich_basic by emphasizing comprehensiveness and the use of schema.org plus LLM fallback.

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 provides strong contextual guidance: it mentions cost per call, caching behavior, and the methodology (schema.org with LLM fallback). However, it does not explicitly name alternatives or state when not to use this tool versus enrich_basic or enrich_html, so it falls short of a 5.

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