Context Window
AI / MCPDefinition
The context window is the maximum amount of text (measured in tokens) that a language model can process in a single request. It includes both the input prompt and the generated output.
How It Relates to CrawlForge
Context window size determines how much scraped content an AI agent can work with at once. Claude's 200K token context window can hold roughly 150,000 words, while smaller models may be limited to 4K-32K tokens. Exceeding the context window means data gets truncated or lost.
CrawlForge helps manage context window constraints through tools like summarize_content, which condenses long pages, and extract_text, which strips out boilerplate. For large-scale research, deep_research synthesizes multiple sources into a concise summary rather than dumping all raw content into context.
Related CrawlForge Tools
Related Terms
Token
A token is the basic unit of text that language models process. Text is split into tokens (roughly 4 characters or 0.75 words each) before being processed by the model. Token counts determine costs and context limits.
Large Language Model (LLM)
A large language model is a neural network trained on vast amounts of text data that can understand and generate human language. LLMs power AI assistants, code generators, and autonomous agents.
Prompt Engineering
Prompt engineering is the practice of designing and refining instructions given to language models to achieve desired outputs. It involves crafting system prompts, few-shot examples, and structured queries.
Retrieval-Augmented Generation (RAG)
RAG is an AI architecture that combines information retrieval with text generation. It first retrieves relevant documents from external sources, then uses them as context for the language model to generate accurate, grounded responses.
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