Results for “buildkite”

7 skills

buildkite-automation

Automate Buildkite CI/CD operations through Composio's toolkit via Rube MCP, including pipeline management and job execution.

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Build onchain applications with React components and TypeScript utilities from Coinbase's OnchainKit, supporting wallet connection, token swaps, NFT minting, and payment processing.

claude-dev-suite

CMake build system for C/C++ projects. Modern CMake (3.20+) with targets, properties, presets (CMakePresets.json), FetchContent, find_package, generator expressions, install rules, vcpkg/Conan integration. USE WHEN: user mentions "CMake", "CMakeLists.txt", "CMakePresets", "find_package", "FetchContent", "target_link_libraries", "vcpkg", "Conan", "C++ build" DO NOT USE FOR: Make, autotools, Bazel, Meson, Visual Studio .vcxproj direct editing

minecraft-plugin-development

Build and modify Minecraft server plugins for Paper, Spigot, or Bukkit, covering plugin.yml setup, commands, listeners, schedulers, player state, team/arena systems, persistent progression, economy, configuration, and Adventure text.

36.2k · bundle

Configure Vite build tool, use its plugin API, set up SSR, and migrate to Vite 8 with Rolldown.

GitHub Spec-Kit integration for constitution-based spec-driven development. 7-phase workflow (constitution, specify, clarify, plan, tasks, analyze, implement). Use when working with spec-kit CLI, .specify/ directories, or creating specifications with constitution-driven development. Triggered by "spec-kit", "speckit", "constitution", "specify", references to .specify/ directory, or spec-kit commands.

Cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Enables building and training quantum circuits with automatic differentiation, seamless integration with PyTorch/JAX/TensorFlow, and device-independent execution across simulators and quantum hardware (IBM, Amazon Braket, Google, Rigetti, IonQ, etc.). Use when working with quantum circuits, variational quantum algorithms (VQE, QAOA), quantum neural networks, hybrid quantum-classical models, molecular simulations, quantum chemistry calculations, or any quantum computing tasks requiring gradient-based optimization, hardware-agnostic programming, or quantum machine learning workflows.