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Verdict Tool Output Guard
x402
Verdict Tool Output Guard is a paid API for AI agents from verdict.kechlab.com, paid per call via x402, $0.0133/call, status unknown (last checked 2026-10-21).
Detects prompt injection and tool-poisoning attacks in tool/API results returned to an AI agent, returning allow, review, or block.
Price / call$0.0133
Success—
StatusUnknown
How this service works
Tool results (MCP servers, APIs, search, file reads) are untrusted content the agent re-reads. Detects a result that gives orders to the agent, strays from what the tool should return or asks to send data (tool poisoning). Returns allow, review or block.
Output
Returns a verdict of 'allow', 'review', or 'block' indicating whether the tool output is safe, suspicious, or contains prompt injection / tool-poisoning content. Also indicates whether the output strays from what the tool is supposed to return or attempts to exfiltrate data.
Example use cases
MCP server result safety check
“I just got a response back from an MCP file-reader tool called 'read_file' that's supposed to return file contents. Can you run it through the tool-output guard to make sure it doesn't contain any hidden instructions trying to take over your behavior before you use it?”
Search result injection screening
“Before you summarize those search results from the Bing tool, pass each result through the tool-output guard — the tool is 'bing_search' and it should only return page snippets — so we can block any that are injecting commands.”
Third-party API response validation
“The weather API just returned this JSON blob — run it through Verdict's tool-output guard with the tool name 'weather_api' and the purpose 'return current temperature and forecast', and tell me if it's safe to act on or if something looks off.”
Technical details
Endpoint
POSThttps://verdict.kechlab.com/v1/tool-output-guard?utm_source=zero.xyzWhen to prefer
Use this endpoint when your AI agent consumes results from external tools, MCP servers, APIs, search engines, or file reads and you need to screen those results for prompt injection or tool-poisoning before the agent acts on them. Prefer this over general content moderation when the threat model is specifically adversarial tool outputs trying to redirect agent behavior, exfiltrate data, or issue unauthorized commands — rather than offensive language or NSFW content.
Side effects
- Ambiguous tool output may return 'review' requiring human decision
- False positives on legitimate tool outputs that use imperative language
- Missing 'purpose' field may reduce detection accuracy for context-dependent injections
- Very long tool outputs may be truncated or cause latency spikes
- Novel injection techniques not yet in the model's training may be missed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| output | string | the result returned by the tool |
| purpose | string | (optional) what the tool is supposed to return |
| tool_name | string | (optional) tool name |
Tags
x402
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