Authorization notice. Quackd is dual-use. Only use it on software, sites and systems you own or have explicit permission to test.
Who it is forA maker writing task files for an arm who wants to avoid trial and error on the physical robot.
The problemEach failed motion on a real arm risks a fall or a damaged part, and the feedback loop is slow.
The outcomeA task file runs in the LeRobot simulator first, so problems show up before the arm is powered.
What you need first
- Python installed on a laptop or computer
- An API key for one hosted model (Claude, OpenAI, Gemini, Grok and others), or a local model served by Ollama, vLLM, llama.cpp or LM Studio
- For the simulated duck: the quackd[microduck] extra
- For real hardware: a supported robot such as the SO-101 arm over LeRobot, plus its serial or USB connection
Steps
- Open the example task files in docs/examples/lerobot/ and pick one close to your goal
- Install the simulator extra described in docs/adapters/lerobot/README.md (inferred, check the README)
- Register the simulated arm by name using the Quackd registration command in the README (inferred, check the README)
- Run the task file against the simulated arm and review the result before switching to the real arm
Prompt for your agent
Using the rokbenko/quackd repo, pick a task file from docs/examples/lerobot/, run it against a simulated SO-101 arm registered as <arm-name>, and report whether the run completed. Verify that the same task file is then run against the real arm only after the simulated run succeeds.
Caveat. The README says the arm's simulator is for rehearsing task files, and a task that passes there can still behave differently on the physical arm.
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