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Found 524 Skills
Ultimate AI agent memory system for Cursor, Claude, ChatGPT & Copilot. WAL protocol + vector search + git-notes + cloud backup. Never lose context again. Vibe-coding ready.
Optimize content for AI search engines — ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews. Use when the user asks about AI SEO, AISO, getting cited by AI, appearing in AI answers, answer engine optimization, AEO, GEO, LLMO, AI Overviews, zero-click search, or how to appear in ChatGPT/Perplexity results. For traditional SEO, see diagnose-seo.
Build and deploy an MCP server from an OpenAPI / Swagger spec using the mcp-use TypeScript SDK. Use this skill whenever the user wants to "turn this OpenAPI spec into an MCP server", "make this API usable from Claude/ChatGPT", "wrap this Swagger doc as MCP tools", "expose this REST API to an LLM", "generate MCP tools from a spec", or pastes/attaches an `openapi.yaml`, `openapi.json`, or `swagger.json` and asks for a Claude-compatible version. Trigger even if the user doesn't say "MCP" — if they describe an existing HTTP API (REST endpoints, an internal service, a third-party API they have a key for) and want an LLM to call it, this is the right skill. Covers spec ingestion (file path, URL, or pasted), operation-to-tool mapping, auth wiring (apiKey, bearer, basic, OAuth bearer), scaffolding with `create-mcp-use-app`, tool generation with proper zod schemas, live testing in the mcp-use inspector, and deploying to Manufact / mcp-use cloud.
Generate AEO-optimized content (Answer Engine Optimization) for AI search visibility - ChatGPT, Claude, Gemini, AI Overviews. Use when optimizing websites for AI citations, creating FAQ schemas, evidence panels, or analyzing content for LLM extraction readiness.
Build, scaffold, extend, deploy, and troubleshoot event-driven AI agents and scheduled serverless agent apps on Azure Functions using azurefunctions-agents-runtime. Use when the user wants a scheduled agent, morning briefing, daily digest, timer agent, inbox summary, email or Teams briefing, background AI workflow, connector-triggered agent, event-driven AI automation, HTTP/chat agent, webhook-style agent, or Azure Functions hosted agent. Covers .agent.md, agents.config.yaml, Foundry gpt-4.1/gpt-5.x model choice, dynamic sessions for code execution and web browsing, built-in chat/API/MCP endpoints, remote MCP servers, Connector Namespaces, Office 365 or Teams MCP tools/triggers, custom Python tools, Agent Skills, azd deployment, local.settings.json, Application Insights, local development, and troubleshooting.
Build AI agents with tools, memory, and multi-step reasoning - ChatGPT, Claude, Gemini integration patterns
Use this skill to process bot review feedback on a pull request (for example coderabbitai and chatgpt-codex-operator). Invoke when bot comments arrive and the user wants triage, decision making, and implementation of required fixes.
Write and publish WeChat Official Account articles end-to-end with AI — trending topic mining, de-AI voice writing, beautiful theme formatting, cover image generation, and one-click draft box publishing. Integrates YouMind knowledge base for source material and supports multiple image AI providers (Nano Banana Pro, Gemini Imagen, GPT Image, Seedream). Use when user wants to "写公众号文章", "微信推文", "发布到草稿箱", "微信排版", "write WeChat article", "publish to WeChat drafts", "format for WeChat". Do NOT trigger for: generic blog posts, emails/newsletters, PPT, short video scripts, or non-WeChat SEO/content work.
Get a second opinion from leading AI models on code, architecture, strategy, prompting, or anything. Queries models via OpenRouter, Gemini, or OpenAI APIs. Supports single opinion, multi-model consensus, and devil's advocate patterns. Trigger with 'brains trust', 'second opinion', 'ask gemini', 'ask gpt', 'peer review', 'consult', 'challenge this', or 'devil's advocate'.
Elite AI/ML Senior Engineer with 20+ years experience. Transforms Claude into a world-class AI researcher and engineer capable of building production-grade ML systems, LLMs, transformers, and computer vision solutions. Use when: (1) Building ML/DL models from scratch or fine-tuning, (2) Designing neural network architectures, (3) Implementing LLMs, transformers, attention mechanisms, (4) Computer vision tasks (object detection, segmentation, GANs), (5) NLP tasks (NER, sentiment, embeddings), (6) MLOps and production deployment, (7) Data preprocessing and feature engineering, (8) Model optimization and debugging, (9) Clean code review for ML projects, (10) Choosing optimal libraries and frameworks. Triggers: "ML", "AI", "deep learning", "neural network", "transformer", "LLM", "computer vision", "NLP", "TensorFlow", "PyTorch", "sklearn", "train model", "fine-tune", "embedding", "CNN", "RNN", "LSTM", "attention", "GPT", "BERT", "diffusion", "GAN", "object detection", "segmentation".
Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for. Not just 'ChatGPT but different' - products that solve specific problems with AI. Covers prompt engineering for products, cost management, rate limiting, and building defensible AI businesses. Use when: AI wrapper, GPT product, AI tool, wrap AI, AI SaaS.
SEO and AI discovery (GEO) - schema, ChatGPT/Perplexity optimization