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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds a useful behavioral fact not in structured data: pricing (page cost plus 5 credits). It omits other traits such as timeouts, retries, or how the AI extraction behaves on failed pages.

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 the core action and the two key parameters, with no filler. The pricing clause is short and earns its place.

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 15-parameter scraping tool with no output schema and zero schema documentation, the description is too thin. It covers the AI-extraction core but leaves most browser/proxy/render controls unexplained, which an agent would need to invoke it correctly in non-default cases.

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 0% across 15 parameters, so the description must carry the load. It only explains 2 of them (ai_query, ai_schema) with brief examples, leaving url, wait, cookies, timeout, wait_for, proxies, rendering flags, and screenshot undocumented in both schema and description.

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 (fetch) and resource (web page) plus the distinctive behavior (AI extracts requested fields as JSON), which separates it from a plain fetch. However, it never names or contrasts against the closest sibling, scrapeWebsite, so the agent must infer the boundary.

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 two usage modes (ai_query vs ai_schema) with examples, which is genuine guidance about how to invoke it. It does not say when to prefer this over scrapeWebsite or runBrowserScenario, nor mention prerequisites or exclusions.

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