Skills AI Agent Skills

Observe and troubleshoot WhatsApp in Kapso: debug message delivery, inspect webhook deliveries/retries, triage API errors, and run health checks. Use when investigating production issues, message failures, or webhook delivery problems.

Use when the request is end-to-end, spans multiple workflow phases, or the correct tracking-workflow entry point is still unclear.

Generate AI-powered podcast-style audio narratives using Azure OpenAI's GPT Realtime Mini model via WebSocket. Use when building text-to-speech features, audio narrative generation, podcast creation from content, or integrating with Azure OpenAI Realtime API for real audio output. Covers full-stack implementation from React frontend to Python FastAPI backend with WebSocket streaming.

Analyzes web performance using Chrome DevTools MCP. Measures Core Web Vitals (FCP, LCP, TBT, CLS, Speed Index), identifies render-blocking resources, network dependency chains, layout shifts, caching issues, and accessibility gaps. Use when asked to audit, profile, debug, or optimize page load performance, Lighthouse scores, or site speed.

Use when user requests diagrams, flowcharts, architecture charts, or visualizations. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Generates .excalidraw files and exports to PNG/SVG via Kroki API or locally using excalidraw-brute-export-cli.

Create a new App Store Connect app record via browser automation. Use when there is no public API for app creation and you need an agent to drive the New App form.

Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks.

Create and review Cloudflare Durable Objects. Use when building stateful coordination (chat rooms, multiplayer games, booking systems), implementing RPC methods, SQLite storage, alarms, WebSockets, or reviewing DO code for best practices. Covers Workers integration, wrangler config, and testing with Vitest.

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Plan, draft, audit, and publish LinkedIn posts and comments. Use when the user wants to write a viral LinkedIn post, draft a comment or reply on any LinkedIn post URL, audit a draft against 2026 algorithm heuristics, remove AI tells, extract hook formulas from viral posts, or plan a week of content. Powered by the Publora API for publishing. User provides post/comment URLs, skill drafts content, user approves, then publishes.

Agent Skill Loader is a Model Context Protocol (MCP) server that acts as a bridge between your static Claude Code Skills library and dynamic AI agents (like Antigravity, Claude Desktop, or Cursor). It allows agents to "learn" skills on demand without requiring you to manually copy files into every project. Discovery: listskills - Scans your configured skill directories. Dynamic Learning: readskill

Connect WhatsApp to your product with Kapso: onboard customers with setup links, detect connections, receive events via webhooks, and send messages/templates/media. Also manage WhatsApp Flows (create/update/publish, data endpoints, encryption). Use when integrating WhatsApp end-to-end.

Integrate AbacatePay in code or interact directly with the API (list customers, create checkouts, check balance, etc.)

Convert raw notes, error logs, voice dictation, or screenshots into crisp GitHub-flavored markdown issue reports. Use when the user pastes bug info, error messages, or informal descriptions and wants a structured GitHub issue. Supports images/GIFs for visual evidence.

A multi-model AI orchestration MCP server for automated code review and LLM-powered analysis. Multi-MCP integrates with Claude Code CLI to orchestrate multiple AI models (OpenAI GPT, Anthropic Claude, Google Gemini) for code quality checks, security analysis (OWASP Top 10), and multi-agent consensus. Built on the Model Context Protocol (MCP), this tool enables Python developers and DevOps teams to

Claude Code plugins for AWS development with specialized knowledge and MCP server integrations, including CDK, serverless architecture, cost optimization, and Bedrock AgentCore for AI agent deployment. Shared AWS agent skills including AWS Documentation MCP configuration for querying up-to-date AWS knowledge. - AWS MCP server configuration guide - Documentation MCP setup for querying AWS knowledge

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Secure environment variable management with Varlock. Use when handling secrets, API keys, credentials, or any sensitive configuration. Ensures secrets are never exposed in terminals, logs, traces, or Claude's context. Trigger phrases include "environment variables", "secrets", ".env", "API key", "credentials", "sensitive", "Varlock".

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Recursive Decomposition Skill Handle long-context tasks with Claude Code through recursive decomposition What It Does • Installation • How It Works • Benchmarks • Acknowledgments When analyzing large codebases, processing many documents, or aggregating information across dozens of files, Claude's context window becomes a bottleneck. As context grows, "context rot" degrades performance: - Missed de

A personal filesystem that works as your life operating system — designed to be read, queried, and operated on by an AI agent. Life OS is a structured set of markdown files that give an AI agent (Goose, Claude, or any LLM with filesystem access via MCP) persistent context about your life — who you are, what you're working on, what you're learning, and what's happened. The AI reads these files at t

A Model Context Protocol server for generating charts using AntV. We can use this mcp server for chart generation and data analysis. This is a TypeScript-based MCP server that provides chart generation capabilities. It allows you to create various types of charts through MCP tools. You can also use it in Dify. - ✨ Features - 🎨 Skill Usage - 🚰 Run with SSE or Streamable transport - 🎮 CLI Options

The semantic engine for MCP clients. Define metrics once, query from anywhere. Docs · Getting Started · Changelog · Discord · Bonnard is an agent-native semantic layer CLI. Deploy an MCP server and governed analytics API in minutes -for AI agents, BI tools, and data teams. Define metrics and dimensions in YAML, validate locally, and ship to production. Works with Snowfl

A feedback loop for people building AI skills and MCP servers. You're building a skill, an MCP server, or a custom prompt strategy that's supposed to make an AI coding assistant better at a specific job. But how do you know it actually works? How do you know your latest commit made things better and not worse? Pitlane gives you the answer. Define the tasks your skill should help with, set up a bas