Works with the AI Agents you already use
rawfy
Convert any URL, PDF, or JavaScript-heavy site into clean, structured Markdown and JSON for AI agents.
Free
rawfy
Example session with this skill installed
Use the rawfy CLI to extract the main content from https://example.com/blog-post in markdown format and show me the link map.
- Read your context and instructions
- Compiled the rawfy
I have extracted the content from the specified URL using the Rawfy CLI. The output has been cleaned and formatted as Markdown, including the metadata and link mapping for downstream processing.
Extracted Content: https://example.com/blog-post
| Field | Value |
|---|---|
| Title | The Future of Agentic Workflows |
| Format | markdown |
| Word Count | 842 words |
| Status | 200 OK |
Markdown Body
# The Future of Agentic Workflows
Published on October 24, 2023
As AI agents move from simple chat interfaces to autonomous systems, the need for clean data extraction becomes critical. Most websites are designed for humans, not machines.
## The Challenge of Noise
Navigation bars, advertisements, and footer links create noise that confuses LLMs. By stripping these elements, we reduce token consumption by up to 60%.
## Structural Integrity
Maintaining headers and lists in Markdown allows the agent to understand the document hierarchy without needing to parse complex CSS or nested divs.
Extracted Links
Next steps
- Pass the Markdown Body to a summarization agent to generate a TL;DR.
- Use the Extracted Links list to initiate a recursive crawl of the documentation section.
- Save the output to a
.mdfile for your local RAG knowledge base.
Connects securely to your tools. The creator never sees your data.
About this skill
Web scraping for LLMs often results in noisy HTML, broken layouts, or empty responses from JavaScript-heavy sites. This skill provides a clean extraction layer that converts any URL into structured, machine-readable Markdown or JSON.
What it does
- Content extraction converts messy web pages into clean Markdown, JSON, or plain text.
- Multi-format support handles standard HTML, JavaScript-rendered SPAs, and PDF files natively.
- Structured output returns a consistent object containing the page title, body content, metadata, and a link map.
- Interface flexibility provides access via CLI, MCP server, REST API, Node.js SDK, or Python wrapper.
- Agentic pipeline integration enables research loops by fetching content and passing structured data to downstream summarizers or analyzers.
How it works
- Selection Choose the interface that matches your environment, such as the CLI for terminal work or MCP for agentic tool calls.
- Extraction Run the fetch command with the target URL and optional flags for format or JavaScript waiting.
- Processing The tool parses the DOM, extracts core content, and strips out noise like ads or navigation.
- Integration Use the resulting structured JSON or Markdown directly in your LLM context or database.
Frameworks & tools
Built for Node.js environments and Python wrappers. It integrates with MCP-compatible agents (like Claude Desktop) and provides a REST API for microservice architectures.
Why this beats prompting it yourself
Writing custom scrapers for every site is brittle and time-consuming. This skill handles the edge cases of modern web tech, like SPAs and PDFs, delivering pre-cleaned data that saves token costs and prevents model hallucinations caused by HTML noise.
Use cases
- Research agents fetching web documentation to generate technical summaries.
- Link crawlers extracting link arrays to map out website architectures.
- Data extraction turning product pages into structured JSON for price tracking.
- Knowledge retrieval converting PDFs and articles into Markdown for RAG systems.
Known limitations
Does not support local file paths or direct API endpoints that already return JSON. JS-heavy sites may require specific wait flags to ensure full content rendering.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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