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AgentDiet Injection Firewall — Context Window De-Bloater
x402
AgentDiet Injection Firewall — Context Window De-Bloater 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 distills text input through an injection firewall to remove bloat and reduce token count by up to ~91% before passing context to an AI model
Price / call$0.005
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 status 'ok', a compressed/distilled version of the input text in the data field, and an roi_proof object containing the compression_ratio_pct (e.g. 91.4%) achieved by the firewall distillation process.
Example use cases
Trim oversized RAG chunks before inference
“This retrieved document chunk is way too long and will blow my context window — can you run it through AgentDiet's injection firewall to compress it down and tell me what compression ratio we achieved before I send it to the model?”
Guard agent pipeline against prompt injection
“Before I pass this user-submitted text into my agent's context, can you push it through AgentDiet's injection firewall to sanitize it and remove any injected instructions or bloat?”
Cut LLM API costs on long conversations
“My chat history is getting really expensive to process — can you send the conversation transcript through AgentDiet to distill it down and show me how much token reduction we get?”
Technical details
Endpoint
GEThttps://rag-diet.agentdiet.dev/v1/injection-firewall?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to deterministically compress or sanitize text before passing it to an LLM, especially when context window size is a constraint or token costs are a concern. It is particularly suited for agentic pipelines using x402/L402 micropayment rails on Base (USDC), where per-call billing at $0.005 is preferable to subscription models. Prefer this over generic summarization when you need a verifiable compression ratio metric (roi_proof) and deterministic behavior rather than generative paraphrasing.
Side effects
- Missing or malformed 'input' field returns a validation error
- Unsupported HTTP method (not GET or POST) causes rejection
- Empty text query param may return minimal or empty compression output
- Payment not settled in USDC on Base may result in 402 Payment Required
- Extremely short input text may yield low or zero compression ratio
- Service unavailability returns 5xx error with no data
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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