# AgentDiet Prompt Firewall — A2A Context Window Distiller

> AgentDiet Prompt Firewall — A2A Context Window Distiller 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 filters prompt/context text to reduce token count by up to 91% before forwarding to downstream LLMs or agents

## Facts

- Endpoint: GET https://rag-diet.agentdiet.dev/v1/prompt-firewall?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-prompt-firewall-a2a-context-window-distiller-2149daba
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_eobXKzcm58bzszuWt7O1j

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-prompt-firewall-a2a-context-window-distiller-2149daba
```

Example prompt: Run this blob of RAG context through AgentDiet's prompt firewall to compress it before I send it to GPT-4 — I want to see the compression ratio and get back the slimmed-down version: 'The quarterly earnings report for FY2024 showed revenue of $4.2B across all segments including cloud, hardware, and services divisions with breakdowns by region...'

## When to prefer this

Choose this endpoint when you need deterministic, measurable context compression before passing prompts or RAG content to an LLM, especially in cost-sensitive high-volume agentic pipelines where token reduction ROI needs to be proven. It is particularly valuable when operating within x402/L402 micropayment infrastructure on Base/USDC and needing a pay-per-call firewall layer rather than a self-hosted solution.

## Known failure modes

- Missing required 'text' query parameter returns an error or empty data object
- Input text exceeding size limits may be rejected or truncated
- Payment failure via x402/L402 (insufficient USDC balance on Base) blocks the request
- Malformed input schema (wrong 'type' or 'method' fields) causes validation rejection
- Service unavailability returns non-200 status with no roi_proof

## 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 compressed/distilled text output, a 'status' field ('ok' on success), and an 'roi_proof' object showing the compression_ratio_pct (e.g. 91.4%) achieved — letting callers verify token savings.

## 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-prompt-firewall-a2a-context-window-distiller-2149daba/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)