Total 56,952 skills, AI & Machine Learning has 9468 skills
Showing 12 of 9468 skills
OpenClaw stock analysis skill for US/HK/CN markets. Combines QVeris data sources (THS, Caidazi, Alpha Vantage, Finnhub, X sentiment) for quote, fundamentals, technicals, news radar, morning/evening brief, and actionable investment insights.
Bulk AI image generation via the BulkGen API. Use whenever users ask to generate one or many AI images — even simple requests like "generate an image", "edit this image", "make variations", or "create AI art" should trigger this skill. Handles single images, grids, batches, variations, reference-image editing, expiring result downloads, and HTML preview handoff pages. Works for English and Chinese requests like "生成图片", "批量生成", "图生图", "做一个 3x3 宫格", or "给我做九宫格变体".
Use Chanjing Avatar API for lip-syncing video generation
Multi-agent orchestration layer for OpenAI Codex CLI. Provides 30 specialized agents, 40+ workflow skills, team orchestration in tmux, persistent MCP servers, and staged pipeline execution.
Integration patterns for Mapbox MCP Server in AI applications and agent frameworks. Covers runtime integration with pydantic-ai, mastra, LangChain, and custom agents. Use when building AI-powered applications that need geospatial capabilities.
Use when low-latency realtime speech recognition is needed with Alibaba Cloud Model Studio Qwen ASR Realtime models, including streaming microphone input, live captions, or duplex voice agents.
Use when designing custom voices with Alibaba Cloud Model Studio CosyVoice customization models, especially cosyvoice-v3.5-plus or cosyvoice-v3.5-flash, from a voice prompt plus preview text before using the returned voice_id in TTS.
Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.
Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
Text-to-speech and voice narration. Triggers on: "朗读这段", "配音", "TTS", "语音合成", "text to speech", "read this aloud", "convert to speech", "voice narration", "read aloud".
Generate AI images from text prompts. Triggers on: "生成图片", "画一张", "AI图", "generate image", "配图", "create picture", "draw", "visualize", "generate an image".