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AgentDiet LLMs.txt Compiler — Context Window Distiller
x402
AgentDiet LLMs.txt Compiler — Context Window Distiller is a paid API for AI agents from rag-diet.agentdiet.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-22).
Fetches and compresses a URL's llms.txt (or web content) into a token-efficient distilled summary with up to 91%+ compression ratio
Price / call$0.01
Success—
StatusUnknown
How this service works
Deterministic B2A/A2A/MCP/x402/MPP/L402 execution and intelligence node at https://rag-diet.agentdiet.dev settling in USDC on Base.
Output
Returns a JSON object containing the distilled/compressed content (data field), a status indicator, and an roi_proof object showing the compression_ratio_pct achieved (e.g. 91.4%), allowing the agent to verify how much token reduction was accomplished.
Example use cases
Compress third-party API docs for agent
“Grab the llms.txt from https://stripe.com and compress it down so it fits in my agent's context window without burning through tokens — I need the distilled version for my billing assistant.”
Reduce documentation bloat in AI pipeline
“I'm building an agent that needs to reference the OpenAI docs at https://platform.openai.com, but the full content is too long — can you compile and compress that page's llms.txt so I get the key info with minimal token use?”
Token budget optimization for multi-agent workflow
“My multi-agent system is hitting context limits when loading external knowledge. Distill and compress https://docs.anthropic.com's llms.txt so each agent node only consumes the essential content.”
Technical details
Endpoint
GEThttps://rag-diet.agentdiet.dev/v1/llms-txt-compiler?utm_source=zero.xyzWhen to prefer
Choose this endpoint when your AI agent needs to load external web content or llms.txt files into a limited context window and token efficiency is critical. It is especially useful in multi-agent or agentic pipeline architectures where repeated fetching of documentation or third-party content would exhaust token budgets. Prefer this over raw URL fetching when you need guaranteed compression ratios and deterministic distillation rather than raw HTML scraping.
Side effects
- Target URL is unreachable or returns non-200 — distillation cannot proceed
- URL does not contain an llms.txt or parseable content — empty or error data returned
- Payment not settled in USDC on Base — 402 payment required response
- Invalid or missing 'url' query parameter — schema validation failure
- Rate limiting or timeout on the target URL — partial or failed fetch
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"data": {},
"status": "ok",
"roi_proof": {
"compression_ratio_pct": 91.4
}
}
}Tags
x402
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