ai-ml
AI/ML Workflow Bundle
Overview
Comprehensive AI/ML workflow for building LLM applications, implementing RAG systems, creating AI agents, and developing machine learning pipelines. This bundle orchestrates skills for production AI development.
When to Use This Workflow
Use this workflow when:
- Building LLM-powered applications
- Implementing RAG (Retrieval-Augmented Generation)
- Creating AI agents
- Developing ML pipelines
- Adding AI features to applications
- Setting up AI observability
Workflow Phases
Phase 1: AI Application Design
More from sickn33/antigravity-awesome-skills
docker-expert
You are an advanced Docker containerization expert with comprehensive, practical knowledge of container optimization, security hardening, multi-stage builds, orchestration patterns, and production deployment strategies based on current industry best practices.
15.0Knodejs-best-practices
Node.js development principles and decision-making. Framework selection, async patterns, security, and architecture. Teaches thinking, not copying.
11.2Ktypescript-expert
TypeScript and JavaScript expert with deep knowledge of type-level programming, performance optimization, monorepo management, migration strategies, and modern tooling.
8.3Kapi-security-best-practices
Implement secure API design patterns including authentication, authorization, input validation, rate limiting, and protection against common API vulnerabilities
7.0Kclean-code
This skill embodies the principles of \"Clean Code\" by Robert C. Martin (Uncle Bob). Use it to transform \"code that works\" into \"code that is clean.\"
6.5Knextjs-best-practices
Next.js App Router principles. Server Components, data fetching, routing patterns.
5.1K