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Found 1,587 Skills
Safe database schema migrations using the expand-and-contract pattern with Prisma ORM. Use when renaming columns/tables, changing column types, adding non-nullable columns, or any schema change requiring zero-downtime deployment.
GitHub Actions, GitLab CI/CD, Jenkins, Azure DevOps, build and test strategies, and deployment patterns
Foundry development workflow for Solidity smart contracts. Use when building, testing, or deploying with Foundry (forge, cast, anvil). Covers project setup, foundry.toml configuration, testing patterns, fuzz testing, invariant testing, fork testing, cheatcodes, deployment scripts, and debugging. Triggers on tasks involving forge build, forge test, forge script, cast, anvil, or Foundry-based Solidity development.
Configure auto-configure Ollama when user needs local LLM deployment, free AI alternatives, or wants to eliminate hosted API costs. Trigger phrases: "install ollama", "local AI", "free LLM", "self-hosted AI", "replace OpenAI", "no API costs". Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
Deploy Evernote integrations to production environments. Use when deploying to cloud platforms, configuring production, or setting up deployment pipelines. Trigger with phrases like "deploy evernote", "evernote production deploy", "release evernote", "evernote cloud deployment".
Configure Gamma across development, staging, and production environments. Use when setting up multi-environment deployments, configuring per-environment secrets, or implementing environment-specific Gamma configurations. Trigger with phrases like "gamma environments", "gamma staging", "gamma dev prod", "gamma environment setup", "gamma config by env".
Docker containerization for development and production. Covers Dockerfiles, multi-stage builds, layer caching, Compose services, networking, volumes, health checks, security hardening, and production deployment patterns. Use when writing Dockerfiles, optimizing image size, configuring Compose services, debugging container networking, setting up health checks, hardening containers for production, or troubleshooting build cache issues.
Guides teams through designing, implementing, and optimizing CI/CD pipelines, GitHub Actions workflows, deployment automation, and agentic workflow patterns. Provides production-ready templates, cost optimization strategies, quality gates, and multi-environment deployment planning for modern DevOps practices.
How an AI agent plans, builds, and deploys a complete Ethereum dApp. The three-phase build system for Scaffold-ETH 2 projects. Use when building a full application on Ethereum — from contracts to frontend to production deployment on IPFS.
Ethereum development knowledge for AI agents — from idea to deployed dApp. Fetch real-time docs on gas costs, Solidity patterns, Scaffold-ETH 2, Layer 2s, DeFi composability, security, testing, and production deployment. Use when: (1) building any Ethereum or EVM dApp, (2) writing or reviewing Solidity contracts, (3) deploying to mainnet or L2s, (4) the user asks about gas, tokens, wallets, or smart contracts, (5) any web3/blockchain/onchain development task. NOT for: trading, price checking, or portfolio management — use a trading skill for those.
Integrate and optimize Core ML models in iOS apps for on-device machine learning inference. Covers model loading (.mlmodelc, .mlpackage), predictions with auto-generated classes and MLFeatureProvider, compute unit configuration (CPU, GPU, Neural Engine), MLTensor, VNCoreMLRequest, MLComputePlan, multi-model pipelines, and deployment strategies. Use when loading Core ML models, making predictions, configuring compute units, or profiling model performance.
This skill should be used when the user asks to "build an MCP server", "create an MCP", "make an MCP integration", "wrap an API for Claude", "expose tools to Claude", "make an MCP app", or discusses building something with the Model Context Protocol. It is the entry point for MCP server development — it interrogates the user about their use case, determines the right deployment model (remote HTTP, MCPB, local stdio), picks a tool-design pattern, and hands off to specialized skills.