# AgentDiet RAG Context Sanitizer

> AgentDiet RAG Context Sanitizer is a paid API for AI agents from rag-diet.agentdiet.dev, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-22).

Compresses and sanitizes RAG context text to reduce token usage by up to 91% before feeding it into an AI agent's context window

## Facts

- Endpoint: GET https://rag-diet.agentdiet.dev/v1/workflows/rag-context-sanitizer?utm_source=zero.xyz
- Price: $0.005/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-22
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/agentdiet-rag-context-sanitizer-63169d98
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_8ChZf4Fc5F9nxSfgNw4er

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability agentdiet-rag-context-sanitizer-63169d98
```

Example prompt: Can you run this retrieved document text through AgentDiet's RAG context sanitizer to strip out the bloat and compress it before I send it to the LLM — I want to see the compression ratio too?

## When to prefer this

Choose this endpoint when you need deterministic, measurable token reduction for RAG-retrieved context before passing it to an LLM — especially when you need a provable compression ratio (roi_proof) and are operating in an A2A or MCP agent pipeline that supports x402 micropayments in USDC on Base. Prefer this over generic summarization APIs when you need consistent, repeatable compression rather than abstractive rewriting.

## Known failure modes

- Missing or empty 'text' query parameter returns an error or empty data
- Input text too large may exceed processing limits
- Payment not settled in USDC on Base causes 402 rejection
- Invalid HTTP method (not GET or POST) returns method-not-allowed
- Network timeouts on very large context payloads

## 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 sanitized/compressed text and an 'roi_proof' object showing the compression_ratio_pct (e.g. 91.4%), along with a status field confirming success.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method"
   ],
   "properties": {
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "GET",
      "POST"
     ],
     "type": "string"
    },
    "queryParams": {
     "type": "object",
     "properties": {
      "text": {
       "type": "string"
      }
     }
    }
   },
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object"
    }
   }
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "data": {},
  "status": "ok",
  "roi_proof": {
   "compression_ratio_pct": 91.4
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/agentdiet-rag-context-sanitizer-63169d98/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from rag-diet.agentdiet.dev](https://www.zero.xyz/host/rag-diet.agentdiet.dev/llms.txt)