Deployment AI Agent Skills

When the user wants to create or update a README.md file for a project. Also use when the user says "write readme," "create readme," "document this project," "project documentation," or asks for help with README.md. This skill creates absurdly thorough documentation covering local setup, architecture, and deployment.

Build comprehensive ML pipelines, experiment tracking, and model

Master Django 5.x with async views, DRF, Celery, and Django

Build Unity games with optimized C# scripts, efficient rendering,

Master Flutter development with Dart 3, advanced widgets, and

Build production ML systems with PyTorch 2.x, TensorFlow, and

Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.

Execute database migrations across ORMs and platforms with zero-downtime strategies, data transformation, and rollback procedures. Use when migrating databases, changing schemas, performing data transformations, or implementing zero-downtime deployment strategies.

Archive session learnings, debugging solutions, and deployment logs to .archive/yyyy-mm-dd/ as indexed markdown with searchable tags. Use when completing a significant task, resolving a tricky bug, deploying, or when the user says \"archive this\". Maintains .archive/MEMORY.md index for cross-session knowledge reuse.

Docker containerization expert with deep knowledge of multi-stage builds, image optimization, container security, Docker Compose orchestration, and production deployment patterns. Use PROACTIVELY for Dockerfile optimization, container issues, image size problems, security hardening, networking, and orchestration challenges.

Orchestrate end-to-end backend feature development from requirements to deployment. Use when coordinating multi-phase feature delivery across teams and services.

Deploy applications and websites to Vercel. Use this skill when the user requests deployment actions such as "Deploy my app", "Deploy this to production", "Create a preview deployment", "Deploy and give me the link", or "Push this live". No authentication required - returns preview URL and claimable deployment link.

Master end-to-end testing with Playwright and Cypress to build reliable test suites that catch bugs, improve confidence, and enable fast deployment. Use when implementing E2E tests, debugging flaky tests, or establishing testing standards.

A Postgres MCP server with index tuning, explain plans, health checks, and safe sql execution. Overview • Quick Start • Technical Notes • Related Projects • Postgres MCP Pro is an open source Model Context Protocol (MCP) server built to support you and your AI agents throughout the entire development process—from initial coding, through testing and deployment, and to production tuning and maintena

Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.

Act as an expert senior Elixir engineer.

End-to-end GenAIOps template for building LLM-infused apps with Prompt Flow, including CI/CD pipelines, A/B deployment, and lifecycle management.

Backend: Node.js with Express.js

Expert C4 Container-level documentation specialist. Synthesizes

Batch process books through the complete pipeline - generate cropped images for split pages, OCR all pages, then translate with context. Use when asked to process, OCR, translate, or batch process one or more books.

Chat with your Kubernetes cluster using natural language! This project connects OpenWebUI to Kubernetes, letting you manage your cluster through conversational AI. Ask questions like "What pods are running?" or "Scale my deployment to 5 replicas" and get instant results. - Quick Start - Configure Open-WebUI - Step 1: Access Open-WebUI - Step 2: Add the MCP Bridge Tool Server - Step 3: Add Connecti

A powerful Model Context Protocol (MCP) server for Docker operations, enabling seamless container and compose stack management through Claude AI. - 🚀 Container creation and instantiation - 📦 Docker Compose stack deployment - 🔍 Container logs retrieval - 📊 Container listing and status monitoring To try this in Claude Desktop app, add this to your claude config files: To install Docker MCP for C

This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence.

A Model Context Protocol (MCP) server that provides AWS EC2 instance pricing data. This project includes both a traditional server implementation and a serverless Lambda function. The Lambda function provides the same functionality as the server but with serverless benefits: For detailed Lambda documentation, see LAMBDA.md. - EC2 Pricing Data: Find the cheapest EC2 instances based on specification