Test an AI prompt in isolation without creating a workflow or execution. Pass a prompt template with {{variable}} syntax and variable values to run the AI and see the response. Useful for tuning prompts and response structures before adding an AI step to a workflow. Example: test_ai_action("Analy...
Accepts raw HTML/template content (template)
Part of the Agentled MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents call test_ai_action to retrieve information from Agentled 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 test_ai_action 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.
tools:
test_ai_action:
rules:
- action: allowSee the full Agentled policy for all 56 tools.
Agents calling read-class tools like test_ai_action have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.
Test an AI prompt in isolation without creating a workflow or execution. Pass a prompt template with {{variable}} syntax and variable values to run the AI and see the response. Useful for tuning prompts and response structures before adding an AI step to a workflow. Example: test_ai_action("Analyze this company: {{company}}", { company: "Stripe" }, { score: "number 0-100", summary: "string" }). It is categorised as a Read tool in the Agentled MCP Server, which means it retrieves data without modifying state.
Add a rule in your Intercept YAML policy under the tools section for test_ai_action. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Agentled MCP server.
test_ai_action is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the test_ai_action rule in your Intercept 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.
Set action: deny in the Intercept policy for test_ai_action. 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.
test_ai_action is provided by the Agentled MCP server (@agentled/mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept