Low Risk

guardrail_test

Test an LLM response against a set of guardrail rules: must-include, must-not-include, max length, required format, language, forbidden patterns, and custom regex. Returns pass/fail per rule.

Part of the IA-QA — 130+ QA & Dev Tools for AI Agents server.

guardrail_test is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call guardrail_test to retrieve information from IA-QA — 130+ QA & Dev Tools for AI Agents without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though guardrail_test only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "guardrail_test": {}
  }
}

See the full IA-QA — 130+ QA & Dev Tools for AI Agents policy for all 146 tools.

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These attack patterns abuse exactly the kind of access guardrail_test gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so guardrail_test only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the guardrail_test tool do? +

Test an LLM response against a set of guardrail rules: must-include, must-not-include, max length, required format, language, forbidden patterns, and custom regex. Returns pass/fail per rule.. It is categorised as a Read tool in the IA-QA — 130+ QA & Dev Tools for AI Agents MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on guardrail_test? +

Register the IA-QA — 130+ QA & Dev Tools for AI Agents MCP server in PolicyLayer and add a rule for guardrail_test: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches IA-QA — 130+ QA & Dev Tools for AI Agents. Nothing to install.

What risk level is guardrail_test? +

guardrail_test is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit guardrail_test? +

Yes. Add a rate_limit block to the guardrail_test rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block guardrail_test completely? +

Set action: deny in the PolicyLayer policy for guardrail_test. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides guardrail_test? +

guardrail_test is provided by the IA-QA — 130+ QA & Dev Tools for AI Agents MCP server (https://www.ia-qa.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every IA-QA — 130+ QA & Dev Tools for AI Agents tool call.

Deterministic rules across all 146 IA-QA — 130+ QA & Dev Tools for AI Agents tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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