analyze_lab_video_cell_behavior
Automated cell behavior analysis from microscopy or XR lab recordings. Classifies cell motion phenotypes (migration, proliferation, apoptosis, division, quiescence), computes population-level quantitative metrics (growth rate, migration velocity, directionality index), and emits structured JSON for downstream reporting, plotting, or ELN integration.
npx skills add BioTender-max/awesome-bio-agent-skills --skill analyze_lab_video_cell_behavior --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.
# Analyze Lab Video — Cell Behavior ## Overview `analyze_lab_video_cell_behavior` converts raw time-lapse microscopy video or first-person XR lab recordings into quantitative cell biology data. The skill ingests brightfield, phase-contrast, or fluorescence video, runs single-cell tracking and phenotype classification through a VLM / computer-vision pipeline, and returns a structured JSON payload containing per-cell trajectories, population growth curves, migration statistics, and apoptosis/division event counts — turning unstructured lab footage into publication-ready metrics in a single step, fully aligned with the LabOS "from video to paper" vision. ## When to Use This Skill Use this skill when any of the following conditions are present: - **Time-lapse microscopy analysis**: A researcher has recorded brightfield, phase-contrast, DIC, or fluorescence (GFP, mCherry) time-lapse videos of cell cultures and needs automated quantification without manual cell counting or commercial software (Fiji, Imaris, Cellpose GUI). - **XR lab recording playback**: A first-person or overhead XR camera captured an ongoing cell culture experiment and the agent must retroactively extract cell behavior
- Overview
- When to Use This Skill
- Core Capabilities
- 1. Video Ingestion & Preprocessing
- 2. Cell Segmentation & Single-Cell Tracking
- 3. Cell Behavior Phenotype Classification
- 4. Quantitative Metric Computation
- 5. Structured JSON Output
- 6. Visualization & Report Integration
- Usage Examples
- Example 1 — Wound-Healing Scratch Assay Quantification
- Example 2 — Drug Cytotoxicity Screen from 96-Well Plate Video
- Example 3 — Real-Time XR Cell Culture Monitoring
- Integration Notes
What does the analyze_lab_video_cell_behavior skill do?
Automated cell behavior analysis from microscopy or XR lab recordings. Classifies cell motion phenotypes (migration, proliferation, apoptosis, division, quiescence), computes population-level quantitative metrics (growth rate, migration velocity, directionality index), and emits structured JSON for downstream reporting, plotting, or ELN integration.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill analyze_lab_video_cell_behavior --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.