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

Annotations only include a title, providing no read-only or destructive hints, so the description must bear the full burden. It discloses the pay-per-call cost model, which is a useful behavioral trait, but it omits critical behaviors like whether JavaScript is executed, how errors are handled, rate limits, or handling of dynamic content. For a scraping tool, these gaps are significant, making the description only minimally transparent.

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 two sentences long and front-loaded with the intended purpose. The first sentence states the core action and output formats; the second provides the pay-per-call context. Every word earns its place, with no fluff or redundancy.

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 and only a minimal annotation, the description carries the burden of explaining what the agent gets back. It only says 'return content' without detailing the JSON structure, error behavior, or limitations. While the parameter schema is rich, the description lacks essential context for a tool with 5 parameters, making it incomplete for reliable invocation.

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?

The input schema has 100% coverage with descriptions for all parameters, so the baseline is 3. The description adds no extra meaning beyond the schema: it only repeats the output formats already listed in the format parameter and provides no context for wait_ms, viewport, or wait_for. Thus, the parameter semantics add no value beyond the structured definition.

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 the tool's function: scraping any webpage and returning content in markdown, html, text, or json. It uses a specific verb (scrape) and resource (webpage), making the purpose unambiguous. However, it does not explicitly distinguish itself from sibling tools like extract_structured_data or extract_metadata, so it stops short of a 5.

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 no explicit guidance on when to use this tool versus alternatives. It mentions 'pay-per-call web scraping for AI agents' which hints at cost-sensitive usage, but it doesn't state any context or exclusions relative to sibling tools such as screenshot_webpage or extract_structured_data. This leaves the agent without clear selection criteria.

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