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Found 486 Skills
Use when an agent needs to delegate a task to the OpenAI Codex CLI from another agent environment such as Claude Code, OpenClaw, or similar. Covers checking whether Codex CLI is installed, running one-off Codex prompts with `codex exec`, resuming sessions, collecting outputs, attaching images or files as input with `-i`/stdin, and handling Codex image generation including finding and reporting generated image file paths.
AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream and Replicate APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
Build AI agents that interact with computers like humans do - viewing screens, moving cursors, clicking buttons, and typing text. Covers Anthropic's Computer Use, OpenAI's Operator/CUA, and open-source alternatives. Critical focus on sandboxing, security, and handling the unique challenges of vision-based control. Use when: computer use, desktop automation agent, screen control AI, vision-based agent, GUI automation.
Access and interact with Large Language Models from the command line using Simon Willison's llm CLI tool. Supports OpenAI, Anthropic, Gemini, Llama, and dozens of other models via plugins. Features include chat sessions, embeddings, structured data extraction with schemas, prompt templates, conversation logging, and tool use. This skill is triggered when the user says things like "run a prompt with llm", "use the llm command", "call an LLM from the command line", "set up llm API keys", "install llm plugins", "create embeddings", or "extract structured data from text".
LangChain / LangGraph engineering pitfalls and verified fixes. Covers DeepAgents, OpenAI-compatible model integration (including Chinese provider adapters: DeepSeek, Qwen, GLM, etc.), middleware, streaming, multi-agent orchestration, and other common development issues. Use when hitting unexpected behavior, making architecture decisions, or integrating Chinese LLM providers during LangChain development.
Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.
Char (formerly Hyprnote) platform help — open-source, bot-free, local-first AI meeting notepad with system audio capture, markdown output, plugin SDK, and optional cloud STT/LLM (GPL-3.0). Use when setting up Char on macOS for the first time, speaker identification not working in group meetings, configuring local-only transcription with Cactus or Ollama for full offline use, choosing between Char's cloud STT providers (Deepgram, AssemblyAI, Soniox, OpenAI, etc.), app not launching or bouncing on dock without opening, telemetry concerns with PostHog or Sentry in a local-first app, building a Char plugin or using the automation hooks system, comparing Char to Granola or Meetily or Fathom for privacy, or configuring the CLI for template management. Do NOT use for picking between note-takers generally (use /sales-note-taker) or reviewing a single call for coaching (use /sales-call-review).
AI Radar Skill — Zero-API, Zero-Key, Zero-Server Chinese AI News Query. Data comes from public static JSON files hosted on GitHub Pages by AI News Radar (automatically updated daily via GitHub Actions). You can retrieve data with curl, no authentication, no UA requirements, no rate limits, and you can fork the entire data pipeline to create your own version. This Skill should be triggered when users ask any Chinese AI news-related questions such as "What's happening in the AI circle today?", "AI news in the past 24 hours", "AI daily briefing", "Any recent large model releases?", "AI product updates", "What's new in Agent tools?", "What have OpenAI/Anthropic/Google released recently?", "Hot topics in the AI circle", "Check AI Radar", "Which AI news sources are worth following?", etc. Even if users only say "AI circle", "AI news", or "What's new today", as long as the context is in the AI / large model / Agent / developer tools domain, this Skill should be triggered. **Do NOT undertrigger** — if users ask for AI news and you don't invoke this Skill, you're treating outdated training data as today's news, which is harmful to users. Do NOT use this Skill for maintaining the AI News Radar repository itself (adding news sources, modifying crawling logic, deploying Pages — use Bole Skill / ai-news-radar for that); do NOT use it for non-AI general news queries; do NOT use it for private information sources that require login status.
Runs external LLM code reviews (OpenAI Codex or Google Gemini CLI) on uncommitted changes, branch diffs, or specific commits. Use when the user asks for a second opinion, external review, codex review, gemini review, or mentions /second-opinion.
Build AI-powered chat applications with TanStack AI and React. Use when working with @tanstack/ai, @tanstack/ai-react, @tanstack/ai-client, or any TanStack AI packages. Covers useChat hook, streaming, tools (server/client/hybrid), tool approval, structured outputs, multimodal content, adapters (OpenAI, Anthropic, Gemini, Ollama, Grok), agentic cycles, devtools, and type safety patterns. Triggers on AI chat UI, function calling, LLM integration, or streaming response tasks using TanStack AI.
Generate or edit images with gpt-image-2 through Codex/ChatGPT subscription authentication instead of OPENAI_API_KEY. Use for text-to-image, reference-image editing, or visual assets when the user wants local Codex auth, especially when no native image tool is available. Do not use for official OpenAI API-key billing or OpenAI-compatible gateways.
Setup Spanora AI observability in any project (JavaScript/TypeScript or Python). Use when user asks to "add spanora", "setup spanora", "integrate spanora", "add AI observability", "monitor LLM calls with spanora", "track AI costs", or mentions spanora in the context of adding observability to their project. Detects the language and installed AI SDKs (Vercel AI, Anthropic, OpenAI, LangChain) and configures the optimal integration pattern.