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Found 382 Skills
Auto-generates an LLM usage monitoring page in a PM admin dashboard. Tokuin CLI-based token/cost/latency tracking + user ranking system + inactive user tracking + data-driven PM insights + Cmd+K global search + per-user drilldown navigation. Supports OpenAI/Anthropic/Gemini/OpenRouter.
Autonomously set up an OpenClaw bot on a fresh Yandex Cloud VM in Kazakhstan (kz1-a, Karaganda). Asks the user for exactly two things — a Telegram bot token and one of three LLM access options (Anthropic API key, OpenRouter API key, or OpenAI Codex OAuth via ChatGPT Plus/Pro subscription) — then handles VM creation, hardening, OpenClaw install, CEO AI OS workspace seeding, Telegram pairing, chat_id auto-detection, and bot-reply verification on its own. The only other actions the user performs are pressing /start in Telegram once and (if Codex) confirming a device code on auth.openai.com. Use when the user says install OpenClaw to Yandex Cloud, deploy OpenClaw to YC Kazakhstan, set up my CEO bot in YC KZ, I am at OpenClaw workshop and need my own bot, create a Yandex Cloud VM for OpenClaw, or any close paraphrase. Targets a ~15-minute end-to-end run for non-DevOps users (founders, CEOs, marketing leads). Supports two modes of accessing Yandex Cloud — Plan A (the user's own YC Kazakhstan account via OAuth) and Plan B (a workshop-key bundle provided by the workshop organizer, for participants without their own YC account). The mode is auto-detected from the inputs. For local-machine OpenClaw install, use openclaw/install.sh in this repo instead. Companion skill openclaw-guide is required; prepare-yc-workshop is the matching organizer-side skill that produces the bundles consumed in Plan B; openclaw-user-onboarding is auto-invoked after Step 5 to collect the five basic facts about the user (identity, focus, style, tools, anti-patterns) and write them into USER.md so the bot is useful from message one.
See and understand images when you (the current model) have no native vision. Use this WHENEVER you need to look at, read, describe, OCR, or reason about the contents of an image, screenshot, photo, diagram, chart, UI mockup, or scanned page — including when the user references a local image file or an image URL and you cannot view it yourself. Also triggers on: 看图 / 识图 / 截图 / 图片内容 / OCR 文字识别 / 这张图是什么. Delegates the actual seeing to a configurable OpenAI-compatible vision model via a small script.
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.
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.
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.
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".
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 RAG pipelines with Exa.ai for real-time web retrieval. Use when building retrieval-augmented generation, integrating Exa with LangChain, LlamaIndex, Vercel AI SDK, or implementing AI agents with web search capabilities. Triggers on: RAG pipeline, retrieval augmented generation, Exa LangChain, Exa LlamaIndex, ExaSearchRetriever, ExaSearchResults, Exa MCP, Exa tool calling, Claude tool use, AI agent web search, grounded generation, citation generation, fact checking, hallucination detection, OpenAI compatibility, chat completions.
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.
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.