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Found 347 Skills
Multimodal UI understanding and single-step planning via OpenAI-compatible Responses APIs. Use when you need AIQuery/AIAssert and plan-next to extract UI element coordinates, validate UI assertions, summarize screenshots, or decide the next UI action from an image. External agents handle execution via adb/hdc and multi-step loops. Defaults to Doubao models but can be pointed at other multimodal providers via base URL, API key, and model name.
AI HOT (aihot.virxact.com) Chinese AI News Query Skill. Trigger this Skill when users ask any Chinese AI information queries such as "What's happening in the AI circle today", "AI Daily", "AI HOT", "AI News", "AI Hot Topics", "Latest AI Updates", "What have OpenAI/Anthropic/Google released recently", "AI hot today", "AI news today", "Check AI industry trends", "What large models are released today", "AI circle updates from yesterday", "Check selected items", "AI HOT Selected", "AI papers from the past week", "AI model releases", "AI product launches", "AI industry dynamics", "AI tips and insights". Even if users only say "AI circle", "AI news", "AI Daily", or just ask "What happened today" with context related to AI / large models / LLM / startup fields, this Skill should be triggered. The Skill directly pulls data via curl from public REST APIs and organizes it into Chinese markdown briefings, with no need for users to configure any API Key or MCP server. **Do NOT undertrigger**——If users ask for AI news and you don't invoke this Skill, you are treating outdated training data as today's news, which is harmful to users.
Implements Syncfusion SfSmartRichTextEditor, an AI-enhanced WYSIWYG editor extending SfRichTextEditor in Blazor. Use this when configuring AI backends (OpenAI, Azure OpenAI, Ollama, custom IChatClient), Smart Action toolbar, AI query dialog, AssistViewSettings, AI popup events and methods, or any inherited Rich Text Editor features in Blazor Server and Web App.
Generate, revise, translate, and manage App Store / Google Play marketing screenshots. Full flow: initialize a .shots workspace, scrape App Store metadata, research the product from the repo and listing, identify theme, colors, audience, and competitor space, save a strategy brief, craft benefit-driven headlines, and generate 3-up GPT-Image 2 composites via OpenAI direct or fal.ai before cropping them into upload-ready panels. Supports iPhone, iPad, and Android Phone platforms. Triggers: "app store screenshots", "marketing screenshots", "store listing images", "screenshot generation", "app store assets", "google play screenshots", "shots", ".shots", "revise shots", "change screenshots", "fix panels", "redo screenshots", "translate screenshots", "localize", "scrape app store", "fetch metadata", "import app store". Do NOT use for general image generation, social media graphics, or non-store marketing assets.
Build AI agents with in-process agent loops using Anthropic or OpenAI APIs, custom tools, MCP servers, and multi-turn conversations
Build high-quality /goal commands for OpenAI Codex CLI 0.128+ that maximize audit-friendliness and minimize false-completion. Use this skill whenever the user wants to write, draft, generate, improve, or refine a /goal prompt — even if they don't say "skill" — including phrases like "help me write a goal", "design a goal for X", "review my goal command", "make a goal for this repo", or any request involving long-running Codex tasks. Also trigger when the user mentions Ralph loop, persistent agent objectives, or asks Codex to "keep working until done". Produces a complete, copy-pasteable /goal command using the 5-section golden template (Objective/Scope/Constraints/Done when/Stop if), supports three interaction modes (step-by-step, full-description, hybrid), auto-detects project type (Node/Python/Swift/Go/Rust/static) by inspecting filesystem or repo URL, reads AGENTS.md/CLAUDE.md if present, and predicts audit-friendliness before output.
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.
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.
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.
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".
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.
AI coding agent skill for Antigravity Manager — a Tauri v2 + Rust desktop app and Docker service that manages multiple Google/Anthropic accounts and proxies them as standard OpenAI/Anthropic/Gemini API endpoints with intelligent account rotation.