gaussian_splatting_scene_description
Generates natural language scene descriptions from 3D Gaussian Splatting reconstructions built from lab photos or short video clips. Outputs structured text with instrument placement, sample positions, spatial layout keywords, and relational predicates — optimized for VLM or spatial intelligence model consumption in protocol guidance, error detection, or AR overlay generation.
npx skills add BioTender-max/awesome-bio-agent-skills --skill gaussian_splatting_scene_description --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Gaussian Splatting Scene Description ## Overview `gaussian_splatting_scene_description` bridges 3D lab reconstruction and natural language understanding. Given a small set of lab photos or short video clips, it builds a 3D Gaussian Splatting (3DGS) scene representation and then generates a structured natural language description of the spatial layout — instrument positions, sample locations, bench topology, and relational predicates (e.g., "pipette is left of tube rack", "centrifuge is behind the operator"). The output is designed for downstream consumption by VLMs, spatial reasoning models, or LabOS skills (`protocol_video_matching`, `detect_common_wetlab_errors`, `realtime_protocol_guidance_prompts`) that need a persistent, queryable representation of the lab environment for context-aware guidance, error detection, or AR overlay anchoring. ## When to Use This Skill Use this skill when any of the following conditions are present: - **Spatial context for protocol guidance**: A protocol step references "the tube on your left" or "the centrifuge behind you"; the agent needs a 3D-aware scene description to resolve spatial references and generate accurate `realtime_protocol_guidance_
- Overview
- When to Use This Skill
- Core Capabilities
- 1. 3D Gaussian Splatting Reconstruction
- 2. Scene Understanding & Object Detection
- 3. Natural Language Description Generation
- 4. Output Formats
- 5. Lab-Specific Enhancements
- 6. Integration with LabOS Pipeline
- Usage Examples
- Example 1 — Bench Layout from 15 Photos
- Example 2 — VLM Prompt Prefix for Protocol Step
- Example 3 — Short Video Clip → 3DGS + Description
- Integration Notes
What does the gaussian_splatting_scene_description skill do?
Generates natural language scene descriptions from 3D Gaussian Splatting reconstructions built from lab photos or short video clips. Outputs structured text with instrument placement, sample positions, spatial layout keywords, and relational predicates — optimized for VLM or spatial intelligence model consumption in protocol guidance, error detection, or AR overlay generation.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill gaussian_splatting_scene_description --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.