Agent skill · NVIDIA
amc-run-sample-calibration
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.
What it needs
About 7k tokens when loaded.
What this skill does
Skill: Calibrate Sample Dataset When to Use This Skill Activate this skill when the user wants to sanity-check a running AMC stack with the bundled sample dataset. Typical prompts: "test the sample dataset" / "run sample calibration" "verify AMC install" "launch and test" (chain with amc-setup-calibration-stack if the MS isn't already running) Do NOT use this skill when: The user references their own video paths (e.g. /data/videos/, cam.mp4 not from the bundled zip) — route to amc-run-video-calibration. The user provides live RTSP streams or rtsp://... URLs — route to amc-run-rtsp-calibration. This skill is exclusively for assets/sdg082sampledata010926.zip. Prerequisite: AMC microservice running on a port in 8000-8009. If no backend is detected, delegate to amc-setup-calibration-stack first. If execution cannot proceed in the current environment (no backend, missing sample data, etc.), surface the blocker AND describe the expected workflow + API sequence concisely so the user understands what will run once prerequisites are met. Do not fabricate calibration outputs, evaluation metrics, or trajectories. Overview Run a full calibration on the bundled sample dataset (sdg082sampledata010926.zip, 4 synthetic warehouse cameras with ground truth) against a running AutoMagicCalib microservice. Useful for verifying that a freshly-launched stack works end-to-end before throwing real data at it. The sample includes GT, so the run produces evaluation metrics (L2 distance, reprojection error) — no calibration parameter tuning needed. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills NVIDIA/amc-run-sample-calibration