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rerun_agent_run

Rerun a failed, waiting, or stuck Rolli Agent run. Resets the run to pending and re-enqueues it. Running runs are force-cancelled first. Returns 422 if the run is already completed.

Part of the Rolli server.

rerun_agent_run can trigger actions in Rolli, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke rerun_agent_run to trigger processes or run actions in Rolli. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

rerun_agent_run can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "rerun_agent_run": {
      "limits": [
        {
          "counter": "rerun_agent_run_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Rolli policy for all 30 tools.

Get this rule live on your own Rolli server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access rerun_agent_run 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 rerun_agent_run only ever does what you allow.

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Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the rerun_agent_run tool do? +

Rerun a failed, waiting, or stuck Rolli Agent run. Resets the run to pending and re-enqueues it. Running runs are force-cancelled first. Returns 422 if the run is already completed.. It is categorised as a Execute tool in the Rolli MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on rerun_agent_run? +

Register the Rolli MCP server in PolicyLayer and add a rule for rerun_agent_run: 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 Rolli. Nothing to install.

What risk level is rerun_agent_run? +

rerun_agent_run is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit rerun_agent_run? +

Yes. Add a rate_limit block to the rerun_agent_run 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 rerun_agent_run completely? +

Set action: deny in the PolicyLayer policy for rerun_agent_run. 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 rerun_agent_run? +

rerun_agent_run is provided by the Rolli MCP server (@rolli/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Rolli tool call.

Deterministic rules across all 30 Rolli tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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