Packs
2 packscurated
Task Execution Workflow
Load a plan, execute tasks with verification, and track progress via issues.
10 skills · pack
@dotnet
Dotnet Test
Skills for running, generating, analyzing, and improving .NET tests: test execution, filtering, platform detection, coverage, testability, and MSTest workflows.
20 skills · pack
Results for “workflow-execution”
9 skills
oyi77 data
Provides a SQLite-backed persistence layer for skill execution metrics, feedback, improvement candidates, and version history, with query and maintenance workflows.
10
oyi77 prefect-flows
Orchestrates Python data pipelines with Prefect flows, tasks, retries, caching, parallel execution, and deployments to work pools.
10
nimoqup046-collab polars
Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for faster pandas-style workflows.
2
More results
thanakijwanavit data-workflow
Use this skill for any data or analytics task — querying databases, analyzing metrics, exploring data warehouses, processing datasets, or creating visualizations.
0
antood69 data-workflow
Use this skill for any data or analytics task — querying databases, analyzing metrics, exploring data warehouses, processing datasets, or creating visualizations.
0
k-dense-ai nextflow
Build, run, and debug Nextflow data pipelines and nf-core workflows end to end, covering processes, channels, operators, configuration, testing, and deployment to HPC or cloud.
30.2k · bundle
k-dense-ai dnanexus-integration
Build and deploy apps/applets on the DNAnexus cloud genomics platform, manage data objects, run workflows, and use the dxpy Python SDK for genomics pipeline development and execution.
30.2k · bundle
schattenspiegel xarray-python
Write, review, debug, or test Python Xarray workflows for labeled N-dimensional DataArray and Dataset operations, including coordinates, alignment, indexing, groupby, resample, rolling, weighted reduction, Dask-backed execution, and NetCDF/Zarr I/O.
0 · bundle
alterlab-ieu alterlab-dask
Scales pandas/NumPy workflows beyond memory with Dask distributed computing — parallel DataFrames, arrays, delayed task graphs, and cluster execution. Use when existing pandas/NumPy code must run on larger-than-RAM data or across clusters, for parallel file processing, distributed ML, or integration with existing pandas code. For out-of-core analytics on a single machine prefer vaex; for in-memory speed prefer polars. Part of the AlterLab Academic Skills suite.
60 · bundle