fetch_parsedFetch a web page through the ScrapeUnblocker API (https://developers.scrapeunblocker.com) and return AI-parsed structured JSON instead of raw HTML (product details, article content, listings).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The absolute URL to fetch and parse. | |
| proxy_country | No | Optional ISO country code, e.g. 'US'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. The description adds context about using the ScrapeUnblocker API and returning parsed JSON, but doesn't disclose additional behavioral traits such as rate limits or what happens on failure.
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 a single, efficient sentence that front-loads the core purpose. It is concise without being overly terse, though breaking into multiple sentences could improve readability.
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 tool with 2 parameters, no output schema, and openWorldHint, the description adequately explains the input (URL) and output (structured JSON). It could mention that output format depends on page type, but overall it is sufficient.
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% and both parameters have descriptions. The description does not add any parameter-specific semantic information beyond what is already in the schema, so baseline 3 is appropriate.
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 specific verb 'Fetch', the resource 'web page', and the output 'AI-parsed structured JSON', which distinguishes it from siblings like fetch_html (raw HTML) and google_search (search results).
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 phrase 'instead of raw HTML' implies when to use this tool versus fetch_html, but no explicit exclusions or alternative guidance for google_search are provided. Usage context is clear, but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clear, distinct purpose: fetch_html returns raw HTML, fetch_parsed returns structured JSON, and google_search performs a search. No overlap.
All tool names follow a consistent verb_noun pattern using lowercase with underscores (fetch_html, fetch_parsed, google_search).
Three tools is a reasonable count for a focused scraping API, covering core functionality without being sparse or excessive.
The set covers fetching raw HTML, parsed data, and Google search, but lacks features like custom headers, session management, or other search engines, leaving notable gaps for advanced use cases.