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1 pack
@samyakjhaveri
Helpers
Utility skills (decision-matrix, navigate, model-route, prompt-improver, grill-research, align-prompt). Useful for specialized one-off tasks like structured decisions, adversarial research grilling, or aligning a draft prompt to an Opus model. NOT for: daily development workflow — these are situational tools, not always-on skills.
4 skills · pack

Results for “opus”

5 skills
k-dense-ai
polars
Process data with high-performance DataFrames using Polars' expression-based API, lazy evaluation, and parallel execution for ETL, analytics, and pandas migration.
30.2k · bundle
k-dense-ai
umap-learn
Perform nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised or semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows using the umap-learn library.
30.2k · bundle
jorcan
polars
Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for fast in-memory analysis and pandas migration.
0 · bundle
k-dense-ai
omero-integration
Access microscopy images and metadata via the OMERO Python API: retrieve datasets, analyze pixels, manage ROIs and annotations, and batch-process for high-content screening workflows.
30.2k · bundle
lingxling
polars
High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.
253 · bundle