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

Annotations only cover read-only/idempotent/open-world, but the description adds materially new context: no-LLM extraction, the Open Graph/meta fallback with matched=false, and the metering model (100/day free bucket then 1 credit via x402). It also documents the return payload shape, which no output schema supplies.

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?

Front-loaded with purpose, then when/when-not, then returns and pricing in clearly segmented clauses. The returns object listing is dense but each field is informative; nothing is wasted, though the brace dump is borderline verbose.

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 no output schema, the description proactively supplies the exact response shape, the fallback condition, and cost model for a metered open-world call. An agent has everything needed to invoke correctly and interpret results.

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 baseline is 3, but the description adds meaning by listing which fields each schema type yields and noting 'auto' detection from JSON-LD types. It slightly exceeds what the enum table conveys without duplicating it.

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 ('extract a page's structured data into a named schema') and enumerates the supported schema types, so an agent knows exactly what this returns. It also names the sibling tools it is not (web_metadata, web_extract, web_fetch), making differentiation immediate.

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?

Has explicit 'When to use' with concrete field examples (title/author/date, price/availability, FAQ Q&A) and an explicit 'Do not use' clause naming the alternatives for verbatim JSON-LD and raw text. Routing is fully determined without opening any schema.

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