shield_analyze
ActiveTool of IA-QA — 130+ QA & Dev Tools for AI Agents
declared in 1.0.0
Run a comprehensive AI guardrail analysis on an LLM response. Orchestrates 6 deterministic safety checks plus an optional LLM-powered deep analysis in parallel: hallucination detection (grounding score), prompt injection scan, toxicity scan, output validation (PII/safety), guardrail rules, response quality scoring, and AI verdict (via Qwen, Gemma, Llama, etc.). Returns a unified PASS/FIX/BLOCK verdict with a 0-100 safety score, per-check results, and actionable fix recommendations. Use this as a single-call safety gate before surfacing any LLM output to users.
Parameters schema
{
"type": "object",
"required": [
"response"
],
"properties": {
"model": {
"type": "string",
"description": "LLM model for AI-powered deep analysis (default: \"qwen/qwen3-32b\"). Set to \"none\" to skip LLM check. Supports any model from list_llm_models."
},
"rules": {
"type": "array",
"items": {
"type": "object",
"properties": {
"type": {
"type": "string"
},
"label": {
"type": "string"
},
"value": {
"type": "string"
}
}
},
"description": "Optional guardrail rules array (same format as guardrail_test tool)"
},
"prompt": {
"type": "string",
"description": "Optional original prompt (used for quality scoring and injection detection)"
},
"source": {
"type": "string",
"description": "Optional reference/source text for hallucination grounding check"
},
"response": {
"type": "string",
"description": "The LLM-generated response to analyze"
}
}
}No endpoints wrapped at confidence ≥ 0.70.
Parent server
IA-QA — 130+ QA & Dev Tools for AI Agents
https://github.com/jcjamet/ia-qa
1/7 registries