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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, so the safety profile is covered. The description adds genuinely non-structured context: no AI inference is involved, values are authoritative rather than inferred, and billing is success-only at US$0.002 per call, which matters for an agent deciding whether to call it repeatedly. Failure modes and engine fallback behavior are still unstated.

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 opening sentence delivers the core differentiator first, followed by a dense but scannable payload list. The pricing sentence at the end earns its place for cost-aware agents, though the payload enumeration is long enough to slightly dilute front-loading.

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 must convey return values, and it does so thoroughly via the payload enumeration. Pricing and success-only charging cover the commercial caveat. The remaining gap is operational: nothing explains the engine choice or what happens on failure/blocked pages.

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 description coverage is 0%, so the description carries the full burden, yet it says nothing about any of the three parameters. The `engine` enum (auto/fetch/kitesurf/chromium) is entirely unexplained — an agent cannot know when to force `chromium` versus `fetch`, and `user_agent` is never mentioned at all.

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 names a specific operation and then enumerates the exact resources returned: JSON-LD/schema.org objects, prices and offers, meta/Open Graph tags, canonical URL, language versions, licence, feeds, and HTML data tables. That enumeration ('exact values instead of guesses from text') implicitly separates it from the plain-text sibling `read`, so an agent can tell what this tool returns without opening a 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?

'Exact values instead of guesses from text' plus 'No AI model involved' clearly signals the context: use this when you need machine-readable facts rather than prose extraction. It does not name an alternative sibling (e.g. `read`, `preflight`, `actions`) or an explicit when-not, 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.