Best fit
- Use when users ask for a Wall-Street-style analytics terminal, trading cockpit, or high-tech financial dashboard template with realistic data layout.
nexu-io/open-design
Professional trading analysis dashboard template (single-file HTML) with light/dark theme switch, dense market panels, chart interactions, demo/live playback, and command palette behavior. Use when users ask for a Wall-Street-style analytics terminal, trading cockpit, or high-tech financial dashboard template with realistic data layout.
npx skills add https://github.com/nexu-io/open-design --skill "design-templates/trading-analysis-dashboard-template"Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Limited to facts supported by the pinned source
Produce a premium, data-dense, Wall-Street style trading dashboard as a self-contained HTML artifact.
npx skills add https://github.com/nexu-io/open-design --skill "design-templates/trading-analysis-dashboard-template"The pinned source contains about 144 English words and 3 usable sections. That evidence supports a source profile, not a complete guide.
144 source words · 3 usable sections
Best fit
Analysis outputs
What the source actually contains
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
1. Read active DESIGN.md, then map typography/color/layout into CSS variables. 2. Copy assets/template.html to index.html. 3. Personalize headings, instrument names, and numeric labels to the user brief. 4. Preserve interaction fidelity: - Light/Dark mode switch - Live/Demo mode…
Review the “Resource map” section in the pinned source before continuing.
One sentence before artifact, then:
Choose a different workflow
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
A separate implementation from K-Dense-AI/scientific-agent-skills; compare its source, maintenance signals, and permission requirements.
Open source detailAnalyze Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.
A separate implementation from K-Dense-AI/scientific-agent-skills; compare its source, maintenance signals, and permission requirements.
Open source detailStandard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, visualization, and converting R-friendly single-cell formats such as Seurat or SingleCellExperiment RDS files into h5ad for Scanpy. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.
A separate implementation from K-Dense-AI/scientific-agent-skills; compare its source, maintenance signals, and permission requirements.
Open source detailFAQ
The source record exposes this install command: npx skills add https://github.com/nexu-io/open-design --skill "design-templates/trading-analysis-dashboard-template". Inspect the command and pinned source before running it.
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Compare before choosing
These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
Analyze Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.
Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, visualization, and converting R-friendly single-cell formats such as Seurat or SingleCellExperiment RDS files into h5ad for Scanpy. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.
Generate enriched ICP-based lead lists with Exa Agent, including structured scoring and CSV output. Use when generating leads, building prospect lists, finding companies to sell to, outbound research, or ICP-based company discovery. Triggers on leads, lead gen, prospect list, find companies, ICP, outbound list. Distinct from lead-magnet (content asset that captures emails).
Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.
Produce a premium, data-dense, Wall-Street style trading dashboard as a self-contained HTML artifact.
trading-analysis-dashboard-template/
├── SKILL.md
├── assets/
│ └── template.html
├── references/
│ └── checklist.md
└── example.html
DESIGN.md, then map typography/color/layout into CSS variables.assets/template.html to index.html./)— or neutral labels) where real numbers are unknown.references/checklist.md before emitting.One sentence before artifact, then:
<artifact identifier="trading-analysis-dashboard" type="text/html" title="Trading Analysis Dashboard">
<!doctype html>
<html>...</html>
</artifact>