sim2real-calibrationlisted

# sim2real-calibration This skill compares simulation metrics with measured prototype metrics and proposes conservative parameter updates. The MVP is file-based and does not connect to hardware. It helps reduce the sim-real gap after a physical prototype exists. ## When To Use Use this skill for: - Comparing simulated and measured speed, slip, torque, roll/pitch, and latency. - Producing parameter update suggestions for simulation/MuJoCo. - Blocking digital-twin trust when sim-real error is too high. - Creating calibration reports after physical testing. ## Workflow 1. Read `<project>/calibration_dataset.yaml`. 2. Compare `simulation` and `real` metrics against tolerances. 3. Estimate conservative parameter updates. 4. Write calibration report artifacts into `<project>/reports/`. ## Commands ```bash python skills/sim2real-calibration/scripts/compare_logs.py skills/sim2real-calibration/examples/quadruped_mvp python skills/sim2real-calibration/scripts/propose_parameter_update.py skills/sim2real-calibration/examples/quadruped_mvp ``` ## Rules - Never claim calibrated parameters are validated without a follow-up simulation and physical re-test. - Treat missing real logs or excessive error in required metrics as blockers. - Keep updates conservative and bounded. - Do not import sibling subskill code. Read files only. ## References - `references/input-contract.md` for `calibration_dataset.yaml` fields. - `references/metrics.md` for comparison metrics. - `references/upda