Fetch AI-parsed page data

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It mentions the ScrapeUnblocker mechanism and that output is AI-parsed structured JSON, providing some transparency about the process. However, it does not disclose potential non-determinism of AI parsing, possible errors, or side effects of scraping (e.g., rate limits, target site load).

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, front-loaded with the core function, and every sentence adds value. It avoids unnecessary elaboration and is highly scannable.

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 no annotations, the description is somewhat incomplete: it doesn't describe the expected JSON structure or mention that AI-parsed output may vary in shape. It covers the main purpose and use cases, but for a tool with unstructured AI output, a note about variability or potential failure would improve completeness.

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 100%, so all parameters are already documented in the schema. The description adds context about typical extraction targets (product details, article content), which implicitly informs rules_hint, but does not add significant new meaning beyond the schema.

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: fetching a web page through ScrapeUnblocker and returning AI-parsed structured JSON instead of raw HTML. It specifies use cases (product details, article content), distinguishing it from the sibling fetch_html which presumably returns raw HTML.

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 clear usage context: 'Best for extracting fields from product, listing or article pages without writing your own HTML parsing.' It implicitly contrasts with raw HTML retrieval, suggesting when not to use it, but does not explicitly name the alternate tool or exclusions beyond that.

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