🧠 A New Approach to LLM Context
Traditional llm.txt files often fail with complex libraries like Crawl4AI. They dump massive amounts of API documentation, causing information overload and lost focus. They provide the "what" but miss the crucial "how" and "why" that makes AI assistants truly helpful.
💡 The Solution: Multi-Dimensional, Modular Contexts
Inspired by modular libraries like Lodash, I've redesigned how we provide context to AI assistants. Instead of one monolithic file, Crawl4AI's documentation is organized by components and perspectives.
The "What"
Precise API facts, parameters, signatures, and configuration objects. Your unambiguous reference.
The "How" & "Why"
Design principles, best practices, trade-offs, and workflows. Teaches AI to think like an expert.
The "Show Me"
Runnable code snippets demonstrating patterns in action. Pure practical implementation.
Why this matters: You can now give your AI assistant exactly what it needs - whether that's quick API lookups, help designing solutions, or seeing practical implementations. No more information overload, just focused, relevant context.
Select Components & Context Types
| Component | Memory Full Content |
Reasoning Diagrams |
Examples Code |
|---|
Available Context Files
| Component | Memory | Reasoning | Examples | Full |
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