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Open and control Three.js views/examples in Annolid Bot sessions.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Label video behavior segments from frame-grid images with a defined behavior list, model-ready JSON, resumable outputs, and no_behavior handling for sparse labels.
Use Annolid GUI tools for robust automation across web, PDF, video, and chat controls.
Infer the assay or paradigm from video context, task text, tracked entities, and experimental cues such as social interaction, open field, courtship, resident-intruder, and novel object recognition.
Choose assay-specific features and measurable objectives for behavior analysis, including distances, zones, speed, contact, orientation, and object interaction.
Segment behavior timelines from tracks, pose, contact, speed, and proximity signals into typed intervals with stable labels and rationales.
Keep behavior analysis aligned with assay objectives, controls, reproducibility, and measurable outputs instead of ad hoc summaries.
| name | threejs |
| description | Open and control Three.js views/examples in Annolid Bot sessions. |
Use this skill when users ask to open Three.js content, switch to 3D canvas, or load built-in 3D examples.
gui_open_threejs(path_or_url)gui_open_threejs_example(example_id)two_mice_html (default)brain_viewer_htmlhelix_points_csvwave_surface_objsphere_points_plyopen threejs example two miceopen threejs example brainopen threejs html /path/to/viewer.htmlopen threejs https://example.org/viewer.htmlopen threejs /path/to/model.plytwo_mice_html..html/.htm/.xhtml, open in Three.js URL viewer mode.