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Found 276 Skills
Speech-to-text transcription using Whisper with word-level timestamps. Use when users ask to transcribe audio or video to text, generate subtitles, or recognize speech.
OpenAI Privacy Filter — bidirectional token-classification model for PII detection and masking in text
Generate images with Gemini (default) or fal.ai FLUX.2 klein 4B (--cheap for fast/low-cost). Generate videos with Grok Imagine (default) or fal.ai LTX-2 (--cheap). Use for: create image, generate visual, AI image generation, poster, video generation.
Self-evolving AI agent system with 26 tools, three-layer memory, MCP plugins, and 24/7 self-repair in pure Python.
AI voice assistants with custom instructions, knowledge bases, and tool integrations.
Install, configure, and start FireRed-OpenStoryline from source on a local machine. Use when a user asks to set up OpenStoryline, troubleshoot installation, download required resources, fill config.toml API keys, or launch the MCP and web services, as well as Chinese requests like “安装 OpenStoryline”, “配置 OpenStoryline”, “启动 OpenStoryline”, “把 OpenStoryline 跑起来”, “修复 OpenStoryline 安装问题”, or “排查 OpenStoryline 启动失败”.
Create Claude Code custom slash commands with proper structure, frontmatter, and best practices. Use this skill whenever the user wants to create a new command, add a slash command, build a custom command, or mentions "create-command", "new command", "add command", or "make a command" for Claude Code. Also trigger when the user wants to turn a workflow into a reusable command.
Answer ZenMux questions by reading the latest official docs. Use for product features, APIs, integration, pricing, models/providers, routing, fallback, streaming, multimodal, structured output, tool calling, reasoning, prompt caching, image/video generation, web search, long context, observability, logs, cost tracking, subscriptions, PAYG, invoices, FAQ, privacy, terms, compliance, and tool guides for Claude Code, Cursor, Cline, Codex, Gemini CLI, opencode, Cherry Studio, Obsidian, Sider, Open-WebUI, Dify, and GitHub Copilot. Trigger on "ZenMux docs", "ZenMux API", "how to use ZenMux", "models", "pricing", "ZenMux 怎么用", "文档", "快速开始", "API 参考", "模型路由", "供应商路由", "订阅", "按量计费", "接入", "配置". Also use when ZenMux is the project context and the user asks about LLM API aggregation, model routing, or provider fallback.
Explains how OpenClaw, OpenShell, and NemoClaw form the ecosystem, NemoClaw's position in the stack, what NemoClaw adds beyond the community sandbox, and when to prefer NemoClaw versus integrating OpenShell and OpenClaw directly. Use when users ask about the relationship between OpenClaw, OpenShell, and NemoClaw, or when to use NemoClaw versus OpenShell. Trigger keywords - nemoclaw ecosystem, openclaw openshell, nemoclaw vs openshell, sandboxed openclaw, how nemoclaw works, nemoclaw sandbox lifecycle blueprint, nemoclaw overview, openclaw always-on assistants, nvidia openshell, nvidia nemotron, nemoclaw release notes, nemoclaw changelog.
Generate project context summaries for AI tool handovers. Use this tool when switching AI tools, starting new sessions, or onboarding team members. It triggers on keywords such as "project context", "handover", "onboard", "project context", "handover", and "taking over a project".
Automatically collect hot topics in the AI field or complete AI technical article writing in the writing style of 'Second Brother' according to specified topics. It focuses on actual tests of AI Coding tools (Claude Code, Qoder, Cursor, TRAE, etc.), engineering implementation of large models (SpringAI, LangChain, RAG, etc.), AI Agent and workflow orchestration, evaluation of domestic large models (GLM, Tongyi Qianwen, DeepSeek, MiniMax, Kimi, etc.), and evaluation of various AI tools and Agent tools. Trigger keywords: write an AI article, AI technical article, large model evaluation, AI tool actual test, GLM, Claude Code, Qoder, Cursor, TRAE, SpringAI, RAG, Agent, workflow, domestic large model, collect AI hot topics, AI topic, etc.
Use this when you are exploring the codebase. It lets you ask the AI who wrote code questions about how things work and why they chose to build things the way they did. Think of it as asking the engineer who wrote the code for help understanding it.