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AgentDiet Tool Poisoning Shield
x402
AgentDiet Tool Poisoning Shield 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).
Scans text for tool-poisoning attacks — malicious prompt injections or adversarial content embedded in tool outputs — and returns a safety verdict with compression metadata.
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 a 'status' field ('ok' or error), a 'data' object containing the safety analysis results, and an 'roi_proof' object that includes a compression_ratio_pct value (e.g. 91.4%) indicating how much the content was processed or reduced. A status of 'ok' with data payload confirms whether the scanned text is clean or flagged as poisoned.
Example use cases
Web scraping pipeline safety check
“I'm building an agent that scrapes websites and feeds the content into GPT-4. Before each scraped page goes into the context window, scan it for tool poisoning or hidden prompt injections so my agent doesn't get hijacked.”
MCP tool output validation
“My agent just got a response from an MCP tool — can you run that response text through the tool-poisoning shield to make sure it doesn't contain adversarial instructions trying to override my agent's behavior?”
RAG retrieval security gate
“I'm using a RAG pipeline that pulls from external documents. Check this retrieved chunk for any embedded prompt injection or tool-poisoning content before I inject it into my LLM's context.”
Technical details
Endpoint
GEThttps://rag-diet.agentdiet.dev/v1/tool-poisoning-shield?utm_source=zero.xyzWhen to prefer
Choose this endpoint when your agent pipeline ingests text from untrusted external sources — web scrapes, RAG retrievals, external API tool responses, or MCP outputs — and you need a lightweight, pay-per-call security gate that checks for embedded prompt injections or tool-poisoning attacks before that content reaches your LLM's context window. It is especially suited for A2A and agentic workflows using x402/L402 micropayment rails on Base.
Side effects
- Missing or empty 'text' query parameter returns an error or empty analysis
- Non-string input types may be rejected by schema validation
- Network timeout if the text payload is excessively large
- Payment failure (x402) if USDC balance on Base is insufficient — returns 402 Payment Required
- Ambiguous or edge-case adversarial patterns may not be flagged with high confidence
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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