Plugins
4 plugins@dotnet
Dotnet AI
AI and ML skills for .NET: technology selection, LLM integration, agentic workflows, RAG pipelines, MCP, and classic ML with ML.NET.
5 skills · plugin
@pwdev-solucoes
Pwdev Uiux
Stack-agnostic UI/UX engineering v2.0 — 6 real subagents, 5-phase workflow with gates, Figma integration, WCAG 2.1 AA, audit hooks
10 skills · plugin
@klotzkette
Grosskanzlei Corporate Ma
Corporate/M&A-Plugin fuer Kanzlei- und Inhouse-Praxis: Deal-Intake, Datenraum, Legal DD, SPA/APA, Kaufpreis, W&I, Regulatory, Signing, Closing, Integration, Board Papers und Spezial-Workflows.
2 skills · plugin
@hekivo
Superpowers Sage
Modern WordPress development with Sage, Acorn & Lando. Workflow skills: /architecture-discovery, /plan-generator, /building, /designing, /verifying (+ /architecting compatibility alias), with design tool integration, content modeling, visual verification, and comprehensive hooks.
36 skills · plugin
Results for “workflow-integration”
15 skills
cloudthinker-ai managing-novu
Manages and analyzes Novu notification infrastructure, covering workflows, subscribers, messages, integrations, and delivery analytics via the Novu API.
7
leandrobenjaminl notebook-integration
Guides creating clean, reproducible Jupyter notebooks with structured workflows, best practices, and IPython magic for analysis and presentation.
0 · bundle
composiohq snowflake-automation
Automate Snowflake data warehouse operations: list databases, schemas, and tables, execute SQL statements, and manage data workflows via the Composio MCP integration.
66.9k
k-dense-ai latchbio-integration
Build and deploy bioinformatics workflows as serverless pipelines on the Latch platform using Python decorators, cloud data management, and GPU support.
30.2k · bundle
lingxling lamindb
Manages biological datasets and models with LaminDB, covering setup, artifact registration, querying, lineage tracking, validation, ontology annotation, collections, branches, storage, and workflow integrations.
253 · bundle
cloudthinker-ai managing-neon
Manages Neon serverless Postgres databases via the neonctl CLI and Neon API, covering projects, branches, databases, roles, endpoints, and compute scaling with a discovery-first workflow.
7
More results
cloudthinker-ai managing-qase
Monitors and analyzes Qase test management projects, test cases, runs, and defects via the Qase API, with a discovery-first workflow to avoid assumptions.
7
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
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
k-dense-ai lamindb
Manage biological datasets and models with LaminDB, an open-source lineage-native lakehouse. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation, collections, branches, storage, and workflow integrations.
30.2k · 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
k-dense-ai benchling-integration
Integrate with Benchling's Python SDK and REST API to manage registry entities, inventory, ELN entries, workflows, and Data Warehouse queries for life sciences R&D automation.
30.2k · bundle
timlai666 dask
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.
1 · bundle
levalencia dask
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.
3 · 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