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| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | 1.Arboreto Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). | davila7/ | 32k | 12 repos | ~1.7k | Automated safety check: Pass | MIT | today |
| 2 | Detects CPU, GPU, memory and disk resources before heavy scientific tasks and writes a JSON file with advice on parallelism, out-of-core work and GPU use. | davila7/ | 32k | 10 repos | ~2.4k | Automated safety check: Pass | MIT | today |
| 3 | Chunked N-D arrays for cloud storage. An agent skill from davila7/claude-code-templates. | davila7/ | 32k | 11 repos | ~5k | Automated safety check: Pass | MIT | today |
| 4 | 4.Dask Parallel/distributed computing. An agent skill from davila7/claude-code-templates. | davila7/ | 32k | 11 repos | ~3.5k | Automated safety check: Pass | MIT | today |
| 5 | 5.Arboreto Infers candidate gene regulatory networks from bulk or single-cell expression data using AertsLab Arboreto GRNBoost2 and GENIE3. | K-Dense-AI/ | 48k | 1 repo | ~2.7k | Automated safety check: Pass | BSD-3-Clause | 3 days ago |
| 6 | 6.Dask Scales pandas, NumPy, and custom Python research workflows beyond memory or across clusters with Dask. | K-Dense-AI/ | 48k | 1 repo | ~4.4k | Automated safety check: Notes | BSD-3-Clause | 3 days ago |
| 7 | Stores and queries chunked N-D scientific arrays with Zarr-Python 3, including codecs, sharding, S3/GCS storage, and NumPy/Dask/Xarray integration. | K-Dense-AI/ | 48k | 1 repo | ~2.2k | Automated safety check: Notes | MIT | 3 days ago |
| 8 | A skill your agent uses when working with Dask Array: chunked NumPy-like arrays, dask.array.fromarray, chunk planning, slicing, mapblocks, blockwise, reductions, overlap, rechunking, generalized… | VectorSpaceLab/ | 328 | — | ~839 | Automated safety check: Pass | BSD-3-Clause | 1 mo ago |
| 9 | Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <- CSR (Python) implicit… | GPTomics/ | 1.2k | 1 repo | ~5.6k | Automated safety check: Pass | MIT | 1 mo ago |
| 10 | GRN inference from expression via GRNBoost2 (gradient boosting) or GENIE3 (Random Forest). | jaechang-hits/ | 370 | 2 repos | ~5.3k | Automated safety check: Pass | BSD-3-Clause | 9 days ago |
| 11 | Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads. | NVIDIA/ | 3.5k | — | ~2.3k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 12 | Use this Dask sub-skill for configuration files and environment variables, the dask command line interface, local diagnostics/profiling/progress, callbacks/cache, scheduler/deployment documentation… | VectorSpaceLab/ | 328 | — | ~694 | Automated safety check: Pass | BSD-3-Clause | 1 mo ago |
| 13 | Use this Dask sub-skill for Dask DataFrame creation, CSV/Parquet/JSON/SQL IO, partitions and divisions, groupby/aggregation, joins/merge, shuffle, repartitioning, categorical/string/pyarrow… | VectorSpaceLab/ | 328 | — | ~1k | Automated safety check: Pass | BSD-3-Clause | 1 mo ago |
| 14 | Fast in-memory DataFrame with lazy evaluation, parallel execution, Arrow backend. | jaechang-hits/ | 370 | — | ~6.4k | Automated safety check: Pass | MIT | 9 days ago |
| 15 | Out-of-core DataFrame for billion-row data via lazy evaluation and memory-mapped files. | jaechang-hits/ | 370 | — | ~6.2k | Automated safety check: Pass | MIT | 9 days ago |
| 16 | Parallel/distributed computing for larger-than-RAM data. An agent skill from jaechang-hits/SciAgent-Skills. | jaechang-hits/ | 370 | — | ~4.1k | Automated safety check: Pass | BSD-3-Clause | 9 days ago |
