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AI Code Safety Guardrails Policy

windsurf-policy-guardrails

jeremylongshore/claude-code-plugins-plus-skills

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 Molecular Toolkit

K-Dense-AI/claude-scientific-skills

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.

Latch Bioinformatics Workflows

latchbio-integration

K-Dense-AI/claude-scientific-skills

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 Fast DataFrame

K-Dense-AI/claude-scientific-skills

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 Mass Spectrometry

K-Dense-AI/claude-scientific-skills

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 Molecular Modeling Workflows

K-Dense-AI/claude-scientific-skills

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.

Apify Actor Development and Deployment

apify-actor-development

sickn33/antigravity-awesome-skills

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.

Autonomous Loop Patterns For Code Development

autonomous-loops

affaan-m/everything-claude-code

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.

Auditing AI Agent Security in Workflows

agentic-actions-auditor

sickn33/antigravity-awesome-skills

Performs static security analysis on GitHub Actions workflows that incorporate AI coding agents (e.g., Claude, Gemini, OpenAI). This skill helps identify critical data flow vulnerabilities, such as where attacker-controlled input can reach AI agent prompts or internal systems via CI/CD pipelines, going beyond simple expression checks.

Feature Development Pipeline Management

sickn33/antigravity-awesome-skills

This command guides the entire lifecycle of major feature development, providing a structured, multi-phase workflow. It helps users move a feature from initial concept (research) through planning, implementation, and progress tracking. Use it when you need to coordinate status, next steps, and phased delivery for complex features.

Practical Async Error Handling With TaskEither

sickn33/antigravity-awesome-skills

This guide demonstrates how to implement clean and robust asynchronous pipelines in TypeScript using `TaskEither` from `fp-ts`. It solves the common problem of deeply nested, unmanageable `try/catch` blocks, allowing developers to compose sequential API calls and operations while correctly handling success and failure paths in a functional, immutable manner. Ideal for complex data fetching and workflow orchestration.

Pipe And Flow Utility Reference

sickn33/antigravity-awesome-skills

This guide provides a quick reference for 'pipe' and 'flow' utilities in fp-ts. The `pipe` function is used to chain multiple operations to transform a specific value, while `flow` allows you to create reusable, composed functions (pipelines). It is essential for implementing clean, declarative data manipulation and functional composition in TypeScript.

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