Agent Skills Hub

tavily-web

Advanced web search, content extraction, and site crawling capabilities using the Tavily API, optimized for AI agent research and data gathering.

Security Code Review

Analyze source code for security vulnerabilities based on OWASP Top 10 guidelines and suggest remediation strategies.

minimax-tts

Perform internet searches using the Zhipu AI web search API to retrieve real-time information, news, and current data.

image-rotator

Reliably rotate images by 90-degree increments using a deterministic Python script. Supports PNG, JPG, GIF, BMP, and TIFF, preserving quality with automated file handling.

web-search-free

Free AI-powered web search via Exa MCP. Includes deep research, company/people lookup, and code context without API keys.

xp-practices

Implement Extreme Programming (XP) practices including TDD, pair programming, and continuous integration to enhance team collaboration and technical excellence in software engineering.

backend-development

Build, optimize, and maintain production-ready backend systems using Node.js, Python, Go, and Rust. Includes API design, database management, security, and DevOps best practices.

seo-optimizer

Comprehensive SEO optimization tool for web applications. Performs automated site audits, meta tag management, structured data implementation, and technical performance analysis for Next.js, Astro, React, and static sites.

building-ai-agent-on-cloudflare

Build stateful AI agents on Cloudflare Workers using the Agents SDK. Features real-time WebSockets, persistent state management, scheduled background tasks, and native tool integration for production-ready deployments.

kungfu

Search, retrieve, and manage your KUNGFU.SH bookmarks programmatically to streamline your research and knowledge management workflows.

stripe-patterns

Stripe payment integration patterns for checkout, webhooks, and subscriptions. Ensures safe API usage, idempotency, signature verification, and testing compliance.

markdown-token-optimizer

Analyzes markdown files to identify token-wasting patterns, providing actionable suggestions to optimize documentation for LLM consumption and token efficiency.