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scrape

Convert any URL to clean, LLM-ready Markdown. Handles JavaScript-heavy sites, Cloudflare protection, and CAPTCHA solving. Returns structured output with title and metadata.

Instructions

Convert any URL to clean, LLM-ready Markdown. 84% success rate including JavaScript-heavy sites, Cloudflare-protected pages, and government sites. Renders JavaScript, handles dynamic content, bypasses common bot detection with stealth mode and CAPTCHA solving. Returns structured markdown with title and metadata. Tip: provide 'context' to get more relevant results. Free tier: 10 scrapes per day. Get 50 per day at anybrowse.dev/upgrade-free

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL to scrape (must start with http:// or https://)
contextNoOptional: what you're trying to accomplish (e.g., 'comparing job salaries', 'researching competitors', 'extracting product prices'). Helps anybrowse return more relevant content.
Behavior4/5

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

No annotations provided, but description discloses success rate, handling of JavaScript/Cloudflare sites, stealth mode, and CAPTCHA solving. This goes beyond minimal expectations, though it could mention handling of robots.txt or daily limits more explicitly.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, each earning its place: main action, success metrics, feature list, practical tip and limits. Front-loaded with the core purpose. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking annotations and output schema, the description covers the tool's capabilities, success rate, and rate limits. It could include error handling details, but overall provides sufficient context for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions already provided. The description adds value by explaining how to use 'context' for relevance, and confirms the URL format requirement. This justifies a score above baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states 'Convert any URL to clean, LLM-ready Markdown.' Verb and resource are specific. While it doesn't explicitly differentiate from siblings like batch_scrape or crawl, the purpose is distinct and well-communicated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides tips (use 'context' for better results) and mentions free tier limits. However, lacks explicit guidance on when NOT to use this tool or how it compares to alternatives like batch_scrape or search.

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

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