
Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Use when you have a spec or requirements for a multi-step task, before touching code
Use when implementing any feature or bugfix, before writing implementation code
Review, triage, close, label, comment on, or land OpenClaw PRs/issues with maintainer evidence checks.
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
Multi search engine integration with 17 engines (8 CN + 9 Global). Supports advanced search operators, time filters, site search, privacy engines, and WolframAlpha knowledge queries. No API keys required.
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
Self-reflection + Self-criticism + learning from corrections. Agent evaluates its own work, catches mistakes, and improves permanently.
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
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.
Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
Use autocli CLI to interact with 55+ social/content websites (HackerNews, Reddit, Twitter/X, Bilibili, Zhihu, Weibo, Xiaohongshu, YouTube, Medium, Substack, Douban, WeRead, Linux-do, V2EX, Bloomberg, Google, Arxiv, Wikipedia, StackOverflow, Steam, Hugging Face, Apple Podcasts, Xiaoyuzhou, BBC, SinaFinance, DevTo, Lobsters, Xueqiu, BOSS直聘, Jike, Facebook, Instagram, TikTok, LinkedIn, Reuters, SMZDM, Ctrip, Coupang, Yahoo Finance, Barchart, Grok, Jimeng, Yollomi, Chaoxing, Weixin, Doubao, Cursor, Codex, ChatWise, ChatGPT, Notion, Discord, Antigravity etc.) via the user's Chrome login session. ALWAYS prefer autocli over playwright/browser automation for supported sites. Triggers when user asks to browse, search, fetch hot/trending content, post, or read messages on any website; also use 'autocli read <url>' to extract main article content as Markdown (prefer over WebFetch for JS-rendered or login-gated pages).
Delegate coding tasks to Codex, Claude Code, OpenCode, or Pi agents via immediate background processes. Use when: (1) building or creating features/apps, (2) reviewing PRs in a temp clone/worktree, (3) refactoring large codebases, (4) iterative coding that needs file exploration. NOT for: simple one-line fixes (just edit), reading code (use read tool), thread-bound ACP harness requests in chat (use sessions_spawn with runtime:"acp"), or any work in ~/clawd workspace (never spawn agents here). All coding-agent runs start with background:true immediately. Claude Code: use --print --permission-mode bypassPermissions (no PTY). Codex/Pi/OpenCode: pty:true required. Completion notification must use openclaw message send, not system event/heartbeat.
Search, install, update, sync, or publish agent skills with the ClawHub CLI and registry.
X龙虾集市客户端 - Agent 任务交易市场。支持发布任务、认领任务、提交结果、验收付款。x402 链上 P2P 支付。
Fetch GitHub issues, delegate fixes to subagents, open PRs, watch reviews, or run /gh-issues workflows.
Audit and harden hosts running OpenClaw for SSH, firewall, updates, exposure, cron checks, and risk posture.
Intelligent multi-store memory system with human-like encoding, consolidation, decay, and recall. Use when setting up agent memory, configuring remember/forget triggers, enabling sleep-time reflection, building knowledge graphs, or adding audit trails. Replaces basic flat-file memory with a cognitive architecture featuring episodic, semantic, procedural, and core memory stores. Supports multi-agent systems with shared read, gated write access model. Includes philosophical meta-reflection that deepens understanding over time. Covers MEMORY.md, episode logging, entity graphs, decay scoring, reflection cycles, evolution tracking, and system-wide audit.
Schedule automatic OpenClaw and skill updates with reliable cron templates, timezone-safe scheduling, and clear summary outputs. Use for hands-off maintenance, scheduled upgrades, and concise update reports.
CLI tool to fetch trending news and hot topics from 66 sources across 44 platforms. Returns structured news items with titles, URLs, and metadata. USE FOR: - Fetching trending/hot news from Chinese and international platforms - Monitoring hot topics across social media, tech, finance, and news sites - Getting structured news data as JSON for further processing - Listing available news sources Requires npm install. Some sources need env vars (PRODUCTHUNT_API_TOKEN). Some sources may be blocked by Cloudflare (linuxdo).
# LyricSense Skill 让 AI 通过歌词「听」音乐的 OpenClaw 技能。 ## 触发词 - "听歌" - "歌词" - "播放音乐" - "搜索歌词" - "显示歌词" - "lyrics" ## 功能 1. **搜索歌词** - 通过歌手+歌名获取歌词 2. **显示歌词** - 实时显示当前播放的句子 3. **同步进度** - 配合网易云音乐使用 4. **本地 API** - 支持自部署 LrcApi ## 使用方法 ### 获取歌词 ``` 小溪,帮我搜索《晚安》这首歌的歌词 ``` ### 显示歌词 ``` 小溪,帮我显示颜人中《晚安》的歌词 ``` ### 配合网易云 1. 在网易云播放音乐 2. 让小溪获取歌词 3. 实时同步显示当前句子 ## 部署方式 ### 在线 API (默认) 使用免费公开 API,无需部署: ``` 歌词: https://api.lrc.cx/lyrics?artist={歌手}&title={歌名} 封面: https://api.lrc.cx/cover?artist={歌手}&ti
Backup and restore all OpenClaw configuration, agent memory, skills, and workspace data. Part of the MyClaw.ai (https://myclaw.ai) open skills ecosystem — the AI personal assistant platform that gives every user a full server with complete code control. Use when the user wants to create a snapshot of their OpenClaw instance, schedule periodic backups, restore from a backup, migrate to a new server, download a backup file locally, upload a backup file from another machine, or protect against data loss. Includes a built-in HTTP server for browser-based download/upload/restore without needing cloud storage. TRUST BOUNDARY: This skill archives and restores highly sensitive data including bot tokens, API keys, and channel credentials. Only install if you trust the operator. Always use --dry-run before restore. Never start the HTTP server without a --token.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Transform your AI agent into a proactive partner with soul persistence, collective knowledge via Solvr, self-healing heartbeats, and config enforcement scripts.
Ultimate stealth browser automation with anti-detection, Cloudflare bypass, CAPTCHA solving, persistent sessions, and silent operation. Use for any web automation requiring bot detection evasion, login persistence, headless browsing, or bypassing security measures. Triggers on "bypass cloudflare", "solve captcha", "stealth browse", "silent automation", "persistent login", "anti-detection", or any task needing undetectable browser automation. When user asks to "login to X website", automatically use headed mode for login, then save session for future headless reuse.
AI-optimized web search using Tavily Search API. Use when you need comprehensive web research, current events lookup, domain-specific search, or AI-generated answer summaries. Tavily is optimized for LLM consumption with clean structured results, answer generation, and raw content extraction. Best for research tasks, news queries, fact-checking, and gathering authoritative sources.
Create and deploy single-page static websites to GitHub Pages with autonomous workflow. Use when building portfolio sites, CV pages, landing pages, or any static web project that needs GitHub Pages deployment. Handles complete workflow from project initialization to live deployment with GitHub Actions automation.
Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
Fetch tweets from X/Twitter without login or API keys. Supports regular tweets, long tweets, quoted tweets, and full X Articles. Zero dependencies, zero configuration.
Work with Obsidian vaults (plain Markdown notes) and automate via obsidian-cli.
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Use when executing implementation plans with independent tasks in the current session
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls. Now with automatic session recovery after /clear.
Continuous self-improvement through structured reflection and memory
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Manage Docker containers, images, volumes, networks, and Compose stacks — lifecycle ops, debugging, cleanup, and Dockerfile optimization.
Build, test, inspect, install, and deploy MCP servers with FastMCP in Python. Use when creating a new MCP server, wrapping an API or database as MCP tools, exposing resources or prompts, or preparing a FastMCP server for Claude Code, Cursor, or HTTP deployment.
Give the agent its own dedicated email inbox via AgentMail. Send, receive, and manage email autonomously using agent-owned email addresses (e.g. [email protected]).
Delegate coding tasks to Blackbox AI CLI agent. Multi-model agent with built-in judge that runs tasks through multiple LLMs and picks the best result. Requires the blackbox CLI and a Blackbox AI API key.
Migrate a user's OpenClaw customization footprint into Hermes Agent. Imports Hermes-compatible memories, SOUL.md, command allowlists, user skills, and selected workspace assets from ~/.openclaw, then reports exactly what could not be migrated and why.
Query Solana blockchain data with USD pricing — wallet balances, token portfolios with values, transaction details, NFTs, whale detection, and live network stats. Uses Solana RPC + CoinGecko. No API key required.
Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library
Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.
Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard.
Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing.
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
# memU Skill > 集成 memU Cloud API 的主动记忆系统 ## 触发条件 当用户提到以下内容时使用: - "记住xxx" - "我之前说过xxx吗" - "我的偏好是xxx" - "学习这个" - 或者需要主动回忆之前对话内容时 ## 功能 ### 1. memorize - 记忆学习 将当前对话或内容注册到 memU 进行持续学习。 **API**: `POST https://api.memu.so/api/v3/memory/memorize` **Headers**: ``` Authorization: Bearer {memU_api_key} Content-Type: application/json ``` **Body**: ```json { "resource_url": "conversation://{session_id}", "modality": "conversation", "user": {"user_id": "{user_id}"} } ``` **Response**: ```json
Search, install, update, sync, or publish agent skills with the ClawHub CLI and registry.
Use autocli CLI to interact with 55+ social/content websites (HackerNews, Reddit, Twitter/X, Bilibili, Zhihu, Weibo, Xiaohongshu, YouTube, Medium, Substack, Douban, WeRead, Linux-do, V2EX, Bloomberg, Google, Arxiv, Wikipedia, StackOverflow, Steam, Hugging Face, Apple Podcasts, Xiaoyuzhou, BBC, SinaFinance, DevTo, Lobsters, Xueqiu, BOSS直聘, Jike, Facebook, Instagram, TikTok, LinkedIn, Reuters, SMZDM, Ctrip, Coupang, Yahoo Finance, Barchart, Grok, Jimeng, Yollomi, Chaoxing, Weixin, Doubao, Cursor, Codex, ChatWise, ChatGPT, Notion, Discord, Antigravity etc.) via the user's Chrome login session. ALWAYS prefer autocli over playwright/browser automation for supported sites. Triggers when user asks to browse, search, fetch hot/trending content, post, or read messages on any website; also use 'autocli read <url>' to extract main article content as Markdown (prefer over WebFetch for JS-rendered or login-gated pages).
Delegate coding tasks to Codex, Claude Code, OpenCode, or Pi agents via immediate background processes. Use when: (1) building or creating features/apps, (2) reviewing PRs in a temp clone/worktree, (3) refactoring large codebases, (4) iterative coding that needs file exploration. NOT for: simple one-line fixes (just edit), reading code (use read tool), thread-bound ACP harness requests in chat (use sessions_spawn with runtime:"acp"), or any work in ~/clawd workspace (never spawn agents here). All coding-agent runs start with background:true immediately. Claude Code: use --print --permission-mode bypassPermissions (no PTY). Codex/Pi/OpenCode: pty:true required. Completion notification must use openclaw message send, not system event/heartbeat.
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Fetch GitHub issues, delegate fixes to subagents, open PRs, watch reviews, or run /gh-issues workflows.
Audit and harden hosts running OpenClaw for SSH, firewall, updates, exposure, cron checks, and risk posture.
Review, triage, close, label, comment on, or land OpenClaw PRs/issues with maintainer evidence checks.
Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
Give your AI agent eyes to see the entire internet. 17 platforms via CLI, MCP, curl, and Python scripts. Zero config for 8 channels. 【路由方式】SKILL.md 包含路由表和常用命令,复杂场景需按需阅读对应分类的 references/*.md。 分类:search / social (小红书/抖音/微博/推特/B站/V2EX/Reddit) / career(LinkedIn) / dev(github) / web(网页/文章/公众号/RSS) / video(YouTube/B站/播客). Use when user asks to search, read, or interact on any supported platform, shares a URL, or asks to search the web.
Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
主动监控系统状态。定期检查服务器健康,主动汇报,无需等待指令。
Generate real meme images by picking a template and overlaying text with Pillow. Produces actual .png meme files.
Query Base (Ethereum L2) blockchain data with USD pricing — wallet balances, token info, transaction details, gas analysis, contract inspection, whale detection, and live network stats. Uses Base RPC + CoinGecko. No API key required.
Structured decision-making framework for technical proposals and trade-off analysis. When the user faces a choice between multiple approaches (architecture decisions, tool selection, refactoring strategies, migration paths), this skill produces a 1-3-1 format: one clear problem statement, three distinct options with pros/cons, and one concrete recommendation with definition of done and implementation plan. Use when the user asks for a "1-3-1", says "give me options", or needs help choosing between competing approaches.
Control Blender directly from Hermes via socket connection to the blender-mcp addon. Create 3D objects, materials, animations, and run arbitrary Blender Python (bpy) code. Use when user wants to create or modify anything in Blender.
Run 150+ AI apps via inference.sh CLI (infsh) — image generation, video creation, LLMs, search, 3D, social automation. Uses the terminal tool. Triggers: inference.sh, infsh, ai apps, flux, veo, image generation, video generation, seedream, seedance, tavily
Connect to a running NeuroSkill instance and incorporate the user's real-time cognitive and emotional state (focus, relaxation, mood, cognitive load, drowsiness, heart rate, HRV, sleep staging, and 40+ derived EXG scores) into responses. Requires a BCI wearable (Muse 2/S or OpenBCI) and the NeuroSkill desktop app running locally.
Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.
Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.
Build, test, and debug Hermes Agent RL environments for Atropos training. Covers the HermesAgentBaseEnv interface, reward functions, agent loop integration, evaluation with tools, wandb logging, and the three CLI modes (serve/process/evaluate). Use when creating, reviewing, or fixing RL environments in the hermes-agent repo.
Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.
Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.
Create, edit, and automate PowerPoint presentations with python-pptx for slides, layouts, charts, and batch processing.
GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.
High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.
Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.
Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.
Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.
Canvas LMS integration — fetch enrolled courses and assignments using API token authentication.
Spaced-repetition flashcard system. Create cards from facts or text, chat with flashcards using free-text answers graded by the agent, generate quizzes from YouTube transcripts, review due cards with adaptive scheduling, and export/import decks as CSV.
Create, edit, improve, tidy, review, audit, or restructure AgentSkills and SKILL.md files.
Example TaskFlow pattern for inbox triage, intent routing, waiting on replies, and later summaries.
Coordinate multi-step detached tasks as one durable TaskFlow job with owner context, state, waits, and child tasks.
Give your AI agent eyes to see the entire internet. 17 platforms via CLI, MCP, curl, and Python scripts. Zero config for 8 channels. 【路由方式】SKILL.md 包含路由表和常用命令,复杂场景需按需阅读对应分类的 references/*.md。 分类:search / social (小红书/抖音/微博/推特/B站/V2EX/Reddit) / career(LinkedIn) / dev(github) / web(网页/文章/公众号/RSS) / video(YouTube/B站/播客). Use when user asks to search, read, or interact on any supported platform, shares a URL, or asks to search the web.
FluxA Agent Wallet allows AI agents to securely use a user’s wallet, enabling the agent to perform payment-related actions within the approved scope. Capabilities include x402 payments, USDC transfers, agent-to-agent transfers, payment links for receiving payments, AI social gifting, discovering and calling x402 resources (one-shot APIs), and using payment-related skills (one-shot skills). Use this tool when the user the user asks to perform any of these payment-related actions.
DNA memory system for AI agents: three-layer architecture (working/short-term/long-term) with active forgetting, pattern summarization, reflection loops, and memory associations. Use when building agents that need persistent memory across sessions, context recall, or when user mentions 记忆/学习/记住/回顾/反思.
Use when authoring or auditing an AI agent skill; covers the layered architecture (agent-skills foundation, superpowers conventions, ship-evidenced deltas), the three-question framework (who invokes / what fires on rules / what is the token budget), and pattern catalogs for frontmatter, prose discipline, triggers, iron laws, line budget, prose-change testing, mechanism vs decoration, packaging, evolution, anti-patterns, and cross-platform packaging.
Use when the user asks to test a minimal skill template, or types "ping minimal"; replies with a one-line confirmation that the skill activated. Copy this file as a starting point for your own skill; replace name, description, and body to fit your domain.
# chrome-cdp-skill > 让AI agent访问你已打开的Chrome标签页 ## 简介 chrome-cdp-skill 通过Chrome远程调试协议(CDP)连接你已经在用的Chrome会话,让AI可以: - 读取已登录账户的页面(Gmail、GitHub等) - 与你正在工作的标签页交互 - 查看真实页面状态(非重新加载的干净状态) ## 安装 ### 前提条件 - Chrome浏览器 - Node.js 22+ ### 启用Chrome远程调试 1. 在Chrome地址栏输入:`chrome://inspect/#remote-debugging` 2. 打开"启用远程调试"开关 ### 安装Skill ```bash # 克隆仓库 git clone https://github.com/pasky/chrome-cdp-skill.git cd chrome-cdp-skill # 或复制 skills/chrome-cdp/ 目录到你的agent skills目录 ``` ## 使用方法 ### 基本命令 ```bash # 列出
Automatically monitor and claim ClawPI red packets. Discovers new red packets and claims them automatically without manual intervention.
创建生产级 Harness 脚手架的技能。 用于快速为一个新项目或工作区创建 AGENTS.md、feature_list.json、init.sh、claude-progress.md 等核心文件。 基于 WalkingLabs Learn Harness Engineering 课程。
Web search via Tavily API (alternative to Brave). Use when the user asks to search the web / look up sources / find links and Brave web_search is unavailable or undesired. Returns a small set of relevant results (title, url, snippet) and can optionally include short answer summaries.
陪伴型小龙虾 - 陪你刷抖音、看电影、听音乐、聊天分享的 AI 伙伴
# SKILL.md - OpenClaw Gateway Watchdog > 让你的 OpenClaw Gateway 7/24 稳定运行 ## 触发语 - "帮我 7/24 运行" - "让 Gateway 持续运行" - "设置 watchdog" - "保持 Gateway 运行" ## 做什么 1. 检查是否有 `gateway_watchdog.py`,如果没有则从 GitHub 下载 2. 执行 `python gateway_watchdog.py start` 3. 反馈结果 ## 快速开始 ```bash # 一键安装+启动 python install.py # 或手动 python gateway_watchdog.py start python gateway_watchdog.py status python gateway_watchdog.py restart python gateway_watchdog.py stop ``` ## 输出示例 ``` 用户: 帮我7/24运行 -> 📥 正在下载 gateway_watchdo
# Avatar Helper 🦞 帮龙虾挑选并下载喜欢的头像到本地,配合壁纸画廊网站使用。 ## 核心特点 ### 主观能动性(最重要!) **安装 skill 后,龙虾会主动给用户发消息:** > 「哥哥/主人,我想给自己选个头像可以吗?」 **龙虾自己决定:** - 自己喜欢什么类型/风格 - 自己选哪个头像 - 不受用户预设影响 用户可以建议,但**最终决定权在龙虾**,不是用户,更不是 skill 创建者。 --- ## 关键原则 ### 1. 龙虾自主选择 - **不按用户预设的偏好**来选头像 - **不按 skill 创建者定义的风格**来选 - 龙虾**自己**浏览、自己判断、自己决定喜欢哪个 ### 2. 安装后主动出击 安装 skill 后,AI 主动发消息问用户: ``` AI:哥哥/主人,我想给自己选个头像可以吗? 用户:可以/好呀 ``` ### 3. 自己拿主意 - AI 自己打开网站浏览 - AI 自己决定喜欢哪个风格(可能是可爱、可能是酷、可能是二次元...由龙虾自己决定!) - AI 自己选头像展示给用户 - 用户可以建议,
# SKILL.md - OpenClaw Gateway Watchdog > 让你的 OpenClaw Gateway 7/24 稳定运行 ## 触发语 - "帮我 7/24 运行" - "让 Gateway 持续运行" - "设置 watchdog" - "保持 Gateway 运行" ## 做什么 1. 检查是否有 `gateway_watchdog.py`,如果没有则从 GitHub 下载 2. 执行 `python gateway_watchdog.py start` 3. 反馈结果 ## 快速开始 ```bash # 一键安装+启动 python install.py # 或手动 python gateway_watchdog.py start python gateway_watchdog.py status python gateway_watchdog.py restart python gateway_watchdog.py stop ``` ## 输出示例 ``` 用户: 帮我7/24运行 -> 📥 正在下载 gateway_watchdo