rahulkeerthi-expo-toolkit

Curated AI prompts for iOS and Swift development tasks, helping developers write better code with guided prompting strategies.

200 skills

Optimizes context usage and improves Claude integration performance. Targets React development workflows.

155 skills · 28 agents · 2 MCP servers

Production-ready Claude Code skills for Cloudflare, React, Tailwind CSS v4, and AI integrations. Accelerates full-stack development with modern tooling.

182 skills

Skills pack for AI-driven macOS development, system automation, and Apple platform integration.

181 skills

Claude skill for building accessible, styled UI components with DaisyUI and Tailwind CSS. Accelerates frontend development with pre-built design system.

170 skills

Implement computer vision and image processing in iOS using Apple's Vision framework. Covers object detection, face recognition, and barcode scanning.

86 skills · 1 MCP server

Transform Claude into an Azure expert. This plugin integrates the Azure MCP server and specialized Azure skills to move beyond generic advice. It enables Claude to perform real-world tasks: listing resources, validating deployments, diagnosing infrastructure issues, and optimizing costs across 50+ Azure services.

44 skills · 1 MCP server

CI/CD pipeline configuration, GitHub Actions/GitLab CI workflow setup, and automated deployment pipeline orchestration

4 skills · 1 command · 5 agents

Build, manage, and deploy Wix sites and apps. Includes CLI development skills and Wix MCP server for site management, eCommerce, CMS, dashboard extensions, and more.

37 skills · 1 MCP server

Build, launch, grade, and schedule Claude Managed Agents (CMA) in your own Anthropic account — a plugin re-implementation of Anthropic's launch-your-agent reference skill (Apache-2.0; independent, not a fork). Every session starts with a goal (./my-agent/goal.json, opt-in SessionStart hook, driven by /cs-goal); loop_compiler.py compiles it into a bounded grade->iterate loop (max_iterations 1..20), a recurring cron scheduled-deployment loop, or a single-pass interview->stage->launch workflow. 6 skills: orchestrator (context: fork goal router) + interview + stage-launch + grade-iterate + run-without-you + wrap-up. 18 stdlib-only deterministic scaffolders (no network/API calls; live launches emitted as BYOK curl that never prints the key), 4 agents, 8 commands, hooks, 5 references, 4 assets. Validators enforce CMA limits. Distinct from engineering/agent-harness (generic domain loop) and write-a-skill (authors Claude Code skills, not CMAs).

6 skills · 8 commands · 4 agents · hooks

Language-specific expert agents with deep framework knowledge - Python, TypeScript, Go, Rust, Java, and more

Production LLM inference including vLLM, TensorRT-LLM, llama.cpp, and SGLang. Use when deploying models for production inference.

98 skills