AI agents call job_result to retrieve information from LLM CLI Gateway without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool retrieves or queries the result of a previously submitted validation job. The verb 'collect' combined with 'VALIDATION job' suggests fetching status or output from an async job that has already run. This is a read operation with no side effects—it does not create, modify, delete, or execute anything.
From the tool's definition Tool name 'job_result' and description 'Collect a VALIDATION job' indicate data retrieval of an existing job result without modification or execution.
Documented attack patterns abuse exactly the kind of access job_result gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and LLM CLI Gateway, and nothing reaches the server without passing your rules. This is the rule we recommend for job_result:
{
"version": "1",
"default": "deny",
"tools": {
"job_result": {}
}
}job_result is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Collect a VALIDATION job. It is categorised as a Read tool in the LLM CLI Gateway MCP Server, which means it retrieves data without modifying state.
Register the LLM CLI Gateway MCP server in PolicyLayer and add a rule for job_result: 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 LLM CLI Gateway. Nothing to install.
job_result 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 job_result 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.
Set action: deny in the PolicyLayer policy for job_result. 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.
job_result is provided by the LLM CLI Gateway MCP server (llm-cli-gateway). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from LLM CLI Gateway, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
46 LLM CLI Gateway tools catalogued and risk-classified — across an index of 43,000+ MCP servers.