Queue Docs
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Integrations
CLI
Running Agents
Launch and monitor agents from the terminal.
Starting a run
Queue gives you two ways to kick off an agent: pass the goal inline as an argument, or let the CLI prompt you interactively.
Output streams to your terminal in real time. Each step prints a short reasoning summary alongside any tool calls the agent made. Hit Ctrl+C at any point to cancel — Queue stops cleanly and preserves the partial trace so you can inspect what happened.
Flags
All flags below can be combined in a single run.
--model
Override the model for this run. Changes take effect immediately without touching your agent config.
--max-steps
Set an upper bound on how many reasoning steps the agent can take. Useful when you need tighter control over cost or want to cap exploration on an open-ended task.
--timeout
Hard wall-clock limit in seconds. If the agent hasn’t finished by then, Queue cancels it gracefully and saves the trace up to that point.
--context
Feed the agent additional context — a file path, a URL, or a glob. You can pass the flag multiple times. The content is prepended to the agent’s system context before the run starts.
--dry-run
Trace the agent’s reasoning without executing any tools or writing anything to disk. Queue prints what each step would have done — handy for auditing a new agent before letting it run for real.
--env
Target a specific environment. Agents can carry distinct credentials, tool configs, and integrations per environment, so you can test in staging before promoting to production.
Interactive mode
The agent pauses at any step marked as a checkpoint in your config and waits for you to confirm before continuing. Use this when you want human sign-off on irreversible actions — file writes, API calls, deployments — without giving up the speed benefits of automation everywhere else.
Quiet mode
Suppress per-step output and only print the final result. Ideal for scripting or piping Queue into other tools where intermediate noise would break downstream parsing.
Reading the output
A completed run prints the final answer, total step count, token usage, and a link to the full trace in the Queue dashboard. Add --json to receive everything as a structured object instead.
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