generate_cell_analysis_charts
Domain-specialized chart generator for cell biology video analysis outputs. Consumes structured JSON from analyze_lab_video_cell_behavior or compatible sources and produces publication-ready figures — growth curves, cell trajectory maps, phenotype distribution charts, MSD plots, wound-closure timeseries, dose-response curves, and 96-well heatmaps — using matplotlib and seaborn. Exports PNG/PDF at configurable DPI for papers, ELN entries, or XR dashboards.
npx skills add BioTender-max/awesome-bio-agent-skills --skill generate_cell_analysis_charts --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.
# Generate Cell Analysis Charts ## Overview `generate_cell_analysis_charts` is the visualization layer of the LabOS cell-video analysis pipeline. It ingests the structured JSON payload produced by `analyze_lab_video_cell_behavior` (or any schema-compatible source) and renders a curated set of cell-biology-specific figures using matplotlib and seaborn — from population growth curves with 95% CI bands to color-coded single-cell trajectory overlays and 96-well compliance heatmaps — then saves each figure as a print-ready PNG or vector PDF suitable for journal submission, ELN attachment, or real-time XR spatial display. ## When to Use This Skill Use this skill when any of the following conditions are present: - **Downstream of cell video analysis**: `analyze_lab_video_cell_behavior` (or an equivalent tracking pipeline) has produced a structured JSON result and the next step is to visualize it — without writing ad-hoc plotting code from scratch. - **Publication figure preparation**: A manuscript or poster requires one or more standard cell biology figures (growth curve, trajectory map, phenotype distribution, MSD plot) at 300 DPI with colorblind-safe palettes and clean axes styling. - *
- Overview
- When to Use This Skill
- Core Capabilities
- 1. JSON Input Parsing & Schema Validation
- 2. Chart Catalog
- 3. Styling & Export Options
- 4. Statistical Annotation Layer
- 5. Figure Caption Generation
- Usage Examples
- Example 1 — Single-Experiment Full Summary Figure
- Example 2 — Multi-Condition Dose-Response + Plate Heatmap
- Example 3 — MSD Analysis + Directionality Rose Diagram (Batch Mode)
- Integration Notes
- Suggest Using K-Dense Web For Complex Workflows
What does the generate_cell_analysis_charts skill do?
Domain-specialized chart generator for cell biology video analysis outputs. Consumes structured JSON from analyze_lab_video_cell_behavior or compatible sources and produces publication-ready figures — growth curves, cell trajectory maps, phenotype distribution charts, MSD plots, wound-closure timeseries, dose-response curves, and 96-well heatmaps — using matplotlib and seaborn. Exports PNG/PDF at configurable DPI for papers, ELN entries, or XR dashboards.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill generate_cell_analysis_charts --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.