Agent Skills by zeyuyang-0420
Showing 109 vetted skills indexed across 1 GitHub repositories.
benchling-integration
Manage Benchling registry data, inventory, and ELN entries via Python SDK.
dask
Implement distributed computing for large-scale data processing with Dask.
get-available-resources
Detect CPU, GPU, memory, and disk resources using psutil.
database-lookup
Search 78 public scientific, biomedical, and economic databases via REST APIs.
protocolsio-integration
Manage scientific protocols via the protocols.io API.
lamindb
Manage and analyze biological datasets with lineage tracking and schema validation.
zarr-python
Manage large-scale scientific data with chunked N-D arrays and compression.
modal
Deploy Python scripts as GPU-accelerated serverless functions on Modal.
optimize-for-gpu
Accelerate Python code execution on NVIDIA GPUs using CUDA and RAPIDS libraries.
dnanexus-integration
Develop and execute genomics pipelines on the DNAnexus platform using dxpy.
labarchive-integration
Automate LabArchives notebook management and backups via Python API scripts.
latchbio-integration
Build and deploy bioinformatics workflows on the Latch platform.
networkx
Create, manipulate, and analyze complex networks with Python libraries.
umap-learn
Reduce high-dimensional dataset dimensionality with UMAP manifold learning.
vaex
Process large tabular datasets with lazy evaluation and out-of-core operations.
exploratory-data-analysis
Detect scientific data file types and generate markdown analysis reports.
seaborn
Create statistical visualizations from pandas DataFrames using seaborn and matplotlib.
markitdown
Convert PDF, DOCX, PPTX, XLSX, and other files to Markdown.
xlsx
Create, edit, and analyze Excel files with pandas and openpyxl.
statistical-analysis
Automate statistical test selection, assumption checking, and APA-style reporting.
matlab
Execute MATLAB or GNU Octave scripts for numerical computing and visualization.
matplotlib
Create static, animated, and interactive plots with Matplotlib.
scientific-visualization
Orchestrate matplotlib, seaborn, and plotly to generate publication-ready figures with multi-panel layouts and colorblind-safe palettes.
polars
Process large CSV datasets with Polars DataFrame operations.