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AgentDiet RAG Context Window Distiller
x402
AgentDiet RAG Context Window Distiller is a paid API for AI agents from rag-diet.agentdiet.dev, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-22).
Compresses and distills AI context windows by up to 91% using RAG-based de-bloating, reducing token usage while preserving semantic content
Price / call$0.001
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 with a `data` field containing the distilled/compressed content, a `status` field ('ok' on success), and a `roi_proof` object showing the compression_ratio_pct (e.g. 91.4%). This allows the caller to verify how much the context was reduced.
Example use cases
Token cost reduction for RAG pipelines
“Take this URL https://en.wikipedia.org/wiki/Transformer_(machine_learning_model) and compress it using AgentDiet's RAG distiller so I can feed only the essential content into my agent without blowing my token budget.”
Web content de-bloating before LLM call
“I'm about to send a long webpage to my AI — can you use AgentDiet to strip out the bloat from https://www.example.com/news/article-2024 and give me just the distilled semantic content with the compression ratio?”
A2A context window slimming in multi-agent workflow
“Before passing this context from one agent to another, run https://docs.myapp.com/api-reference through AgentDiet's distiller to cut down the token count — I need the compression proof so I can log the ROI.”
Technical details
Endpoint
GEThttps://rag-diet.agentdiet.dev/v1?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to reduce token consumption before feeding web content or documents into an LLM or multi-agent pipeline, especially when working with large HTML pages, documentation, or any URL-based context that needs to be slimmed down. It is particularly suited for A2A/MCP agent workflows where context window size is a bottleneck and cost-per-token matters. Prefer it over generic summarization APIs when you need a deterministic compression ratio proof and micro-payment-native ($0.001 USDC) pricing via x402/L402.
Side effects
- Invalid or unreachable URL returns an error status
- Missing required `input` object causes schema validation failure
- Unsupported HTTP method (not GET or POST) triggers an enum validation error
- Payment not settled in USDC on Base results in 402 response blocking execution
- Malformed query params cause processing failure with no compression output
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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