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This skill provides AI-assisted capabilities for creating and managing Continuous Integration/Continuous Deployment (CI/CD) workflows using GitHub Actions. It can generate new workflows from project requirements, optimize existing pipelines, debug failures, and implement industry-standard security best practices, streamlining the entire development and deployment process.

This workflow suite provides robust tools for automating complex, multi-step software development tasks. It allows users to define reusable workflows (like feature scaffolding, deployment pipelines, and quality checks) that are triggered via slash commands. By integrating persistent 'Memories', it maintains project context across sessions, significantly reducing repetitive prompting and standardizing development practices.

Integrates Windsurf's native deployment features and Cascade workflows to automate the entire build, test, and deployment cycle. Supports major platforms like Netlify, Vercel, AWS, and Google Cloud Run, enabling users to manage the full CI/CD pipeline, including preview deployments and rollbacks, directly within the IDE.

This policy set establishes comprehensive guardrails for using AI coding assistants (like Windsurf/Cascade). It governs terminal commands, enforces workspace isolation (preventing access to secrets/credentials), and integrates CI/CD gates for code quality. Use this when setting up team development standards, mandatory code review policies for AI output, or implementing secure development pipelines.

Biopython provides Python APIs for sequence manipulation, database access, BLAST automation, structural bioinformatics, and phylogenetics, making it ideal for scripting custom pipelines and batch processing in computational molecular biology workflows.

LatchBio Integration provides a Python-first platform to compose, deploy, and monitor serverless bioinformatics pipelines with the Latch SDK, decorator-based tasks, cloud storage (LatchFile/Dir), GPU tuning, and Nextflow or Snakemake interoperability.

Polars is a blazing fast in-memory DataFrame library based on Apache Arrow that replaces pandas for 1-100GB workloads, offering expression-based lazy execution, parallel operators, and rich I/O for ETL pipelines.

PyOpenMS provides Python bindings for OpenMS to drive complete mass spectrometry workflows, covering data IO, spectral processing, feature/peptide-protein identification, quantitation, and metabolomics pipelines.

Cloud-native Rowan orchestrates medicinal chemistry and molecular modeling pipelines via a Python API, offering pKa prediction, docking, descriptors, dynamics, and AI-driven structure workflows for scalable batch screening without local HPC.

This guide provides a comprehensive walkthrough for developing and deploying Apify Actors. Actors are serverless, containerized applications designed for powerful tasks like web scraping, data processing, and complex automation. Learn the mandatory setup, template selection (Python, JS, TS), step-by-step development workflow, and crucial security best practices for building robust, production-ready data pipelines.

Apify Actorization is a process that transforms existing, standalone software or scripts (like CLI tools) into standardized, reusable serverless applications called Actors. Actors are packaged as Docker images, accepting structured JSON inputs and producing structured JSON outputs. This skill guides developers on migrating projects to the Apify platform, ensuring compatibility, and enabling scalable, event-driven data processing pipelines.

A comprehensive guide covering patterns and architectures for automating code execution using LLMs. It spans simple sequential pipelines (e.g., daily dev scripts) to advanced, RFC-driven multi-agent Directed Acyclic Graph (DAG) orchestration. Ideal for building CI/CD style continuous development pipelines, managing complex state, and automating quality gates without human intervention.