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# Context Compiler (Generate Command)
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The generate command uses LLM analysis to produce optimized files that improve your site's LLM readiness. It crawls a URL, sends the content to an LLM, and writes structured output files.
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## Overview
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The Context Compiler pipeline:
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1. **Crawl** -- fetches and renders the target URL
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2. **Extract** -- pulls content, structure, and metadata
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3. **Analyze** -- sends extracted data to an LLM with specialized prompts
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4. **Generate** -- writes output files to `./context-output/` (or custom directory)
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## Output Files
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### llms.txt
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A machine-readable file that tells LLMs how to interact with your site. Placed at `/llms.txt` on your domain, it provides:
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- Site description and purpose
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- Content structure guidance
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- Preferred citation format
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- Key pages and their topics
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```bash
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context-cli generate example.com
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```
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### schema.jsonld
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Optimized Schema.org JSON-LD structured data based on your page content. The compiler analyzes your content and generates appropriate schema types (Article, Product, FAQ, HowTo, etc.) with complete properties.
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```bash
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context-cli generate example.com
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```
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### AGENTS.md
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An [AGENTS.md](https://docs.google.com/document/d/1ON2MRbDC2RVJpKMIoluHFz-bGDAELz3RjMLErxEDqn4) file that tells AI agents how to interact with your site, including available endpoints, authentication requirements, rate limits, and data formats.
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```bash
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context-cli generate example.com --agents-md
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```
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## Batch Mode
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Generate assets for multiple URLs from a file:
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```bash
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context-cli generate-batch urls.txt
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context-cli generate-batch urls.txt --concurrency 5 --profile ecommerce
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context-cli generate-batch urls.txt --json
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```
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Each URL's output goes to a subdirectory under the output directory.
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## Industry Profiles
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Tailor the generated output with `--profile`:
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```bash
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context-cli generate example.com --profile saas
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```
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Available profiles:
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| Profile | Optimized for |
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|---|---|
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| `generic` | General-purpose sites (default) |
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| `cpg` | Consumer packaged goods |
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| `saas` | Software-as-a-Service products |
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| `ecommerce` | E-commerce and product pages |
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| `blog` | Blog and content sites |
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Profiles adjust the LLM prompts to emphasize relevant schema types, content structures, and agent interaction patterns for each industry.
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## BYOK (Bring Your Own Key)
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The generate command auto-detects your LLM provider from environment variables:
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| Priority | Env Variable | Default Model |
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|---|---|---|
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| 1 | `OPENAI_API_KEY` | gpt-4o-mini |
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| 2 | `ANTHROPIC_API_KEY` | claude-3-haiku-20240307 |
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| 3 | Ollama running locally | ollama/llama3.2 |
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Override with `--model`:
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```bash
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context-cli generate example.com --model gpt-4o
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```
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No API key is needed if you have Ollama running locally -- the compiler will use it as a fallback.
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## Web Server Config Generation
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Generate web server configuration snippets for routing `Accept: text/markdown` requests:
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```bash
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context-cli generate-config nginx
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context-cli generate-config apache
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context-cli generate-config caddy
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```
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See [serve-modes.md](serve-modes.md) for details on content negotiation and deployment.
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## x402 Payment Config
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Generate x402 payment signaling configuration for monetizing AI agent access:
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```bash
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context-cli generate-x402
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```
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This generates configuration for HTTP 402 responses and x402 headers that signal payment-gated access to AI agents.

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