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retry_run

Retry a failed simulation run. Resets an errored run back to 'created' status and triggers a new package build. The same run ID is reused. Only valid when status is 'error'. Returns 409 for any other state.

Part of the Hydrata - ANUGA Flood Simulation server.

retry_run can trigger actions in Hydrata - ANUGA Flood Simulation, 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 retry_run to trigger processes or run actions in Hydrata - ANUGA Flood Simulation. 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.

retry_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": {
    "retry_run": {
      "limits": [
        {
          "counter": "retry_run_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Hydrata - ANUGA Flood Simulation policy for all 9 tools.

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

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so retry_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 retry_run tool do? +

Retry a failed simulation run. Resets an errored run back to 'created' status and triggers a new package build. The same run ID is reused. Only valid when status is 'error'. Returns 409 for any other state.. It is categorised as a Execute tool in the Hydrata - ANUGA Flood Simulation MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on retry_run? +

Register the Hydrata - ANUGA Flood Simulation MCP server in PolicyLayer and add a rule for retry_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 Hydrata - ANUGA Flood Simulation. Nothing to install.

What risk level is retry_run? +

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

Can I rate-limit retry_run? +

Yes. Add a rate_limit block to the retry_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 retry_run completely? +

Set action: deny in the PolicyLayer policy for retry_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 retry_run? +

retry_run is provided by the Hydrata - ANUGA Flood Simulation MCP server (https://hydrata.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 Hydrata - ANUGA Flood Simulation tool call.

Deterministic rules across all 9 Hydrata - ANUGA Flood Simulation tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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