analyze_lab_video_cell_behavior
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 metrics from the footage.
- Cell motility assays: Wound-healing (scratch assay), Boyden chamber, or transwell migration experiments require automated measurement of migration front velocity, closure rate, or directionality index.
- Growth and proliferation quantification: Confluence over time, doubling time, or colony-forming unit (CFU) counts must be computed from phase-contrast or brightfield videos without manual inspection.
- Apoptosis / cytotoxicity screening: A drug treatment experiment requires automatic detection of apoptotic morphology (membrane blebbing, cell shrinkage, nuclear condensation) at the population level for IC50 or Z-factor calculation.
- Live-cell imaging pipelines: The lab runs high-content screening (HCS) or high-content imaging (HCI) and needs to programmatically extract phenotypic readouts from multi-well plate videos for batch processing.
- Report or figure generation: Downstream tools (
matplotlib,plotly,scientific-visualization,pptx-generation) need structured numeric inputs (trajectories, growth curves, event rates) from video that cannot be manually annotated at scale. - Multi-experiment comparison: Several video datasets from different drug doses, cell lines, or time points must be processed with a uniform pipeline to enable statistically comparable outputs.
More from wu-yc/labclaw
tooluniverse-chemical-safety
Comprehensive chemical safety and toxicology assessment integrating ADMET-AI predictions, CTD toxicogenomics, FDA label safety data, DrugBank safety profiles, and STITCH chemical-protein interactions. Performs predictive toxicology (AMES, DILI, LD50, carcinogenicity), organ/system toxicity profiling, chemical-gene-disease relationship mapping, regulatory safety extraction, and environmental hazard assessment. Use when asked about chemical toxicity, drug safety profiling, ADMET properties, environmental health risks, chemical hazard assessment, or toxicogenomic analysis.
20rowan
Cloud-based quantum chemistry platform with Python API. Preferred for computational chemistry workflows including pKa prediction, geometry optimization, conformer searching, molecular property calculations, protein-ligand docking (AutoDock Vina), and AI protein cofolding (Chai-1, Boltz-1/2). Use when tasks involve quantum chemistry calculations, molecular property prediction, DFT or semiempirical methods, neural network potentials (AIMNet2), protein-ligand binding predictions, or automated computational chemistry pipelines. Provides cloud compute resources with no local setup required.
19tooluniverse-protein-therapeutic-design
Design novel protein therapeutics (binders, enzymes, scaffolds) using AI-guided de novo design. Uses RFdiffusion for backbone generation, ProteinMPNN for sequence design, ESMFold/AlphaFold2 for validation. Use when asked to design protein binders, therapeutic proteins, or engineer protein function.
19tooluniverse-drug-repurposing
Identify drug repurposing candidates using ToolUniverse for target-based, compound-based, and disease-driven strategies. Searches existing drugs for new therapeutic indications by analyzing targets, bioactivity, safety profiles, and literature evidence. Use when exploring drug repurposing opportunities, finding new indications for approved drugs, or when users mention drug repositioning, off-label uses, or therapeutic alternatives.
19tooluniverse-drug-research
Generates comprehensive drug research reports with compound disambiguation, evidence grading, and mandatory completeness sections. Covers identity, chemistry, pharmacology, targets, clinical trials, safety, pharmacogenomics, and ADMET properties. Use when users ask about drugs, medications, therapeutics, or need drug profiling, safety assessment, or clinical development research.
19tooluniverse-pharmacovigilance
Analyze drug safety signals from FDA adverse event reports, label warnings, and pharmacogenomic data. Calculates disproportionality measures (PRR, ROR), identifies serious adverse events, assesses pharmacogenomic risk variants. Use when asked about drug safety, adverse events, post-market surveillance, or risk-benefit assessment.
19