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Found 495 Skills
imagine is a multi-provider command-line tool for generating and editing images via Google Gemini, Google Vertex AI, and OpenAI (gpt-image-2).
Extract frames from video files using ffmpeg for AI/LLM analysis. Use when (1) the user asks to analyze, describe, or summarize a video file, (2) the user wants to extract frames or screenshots from a video, (3) the user provides a video file (.mp4, .mov, .avi, .mkv, .webm, etc.) and asks questions about its visual content, (4) the user wants to identify scenes, objects, or events in a video, (5) the user wants timestamps overlaid on extracted frames for temporal reference. Converts video into JPEG frames that can be attached to LLM prompts as images. Requires ffmpeg on PATH. Supports scene-change detection, model-aware optimization (Claude/OpenAI/Gemini), quality presets (efficient/balanced/detailed/ocr), grayscale and high-contrast OCR mode, and automatic FPS calculation via --max-frames.
Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.
Run cross-framework agent comparisons using evaluatorq from orqkit — compares any combination of agents (orq.ai, LangGraph, CrewAI, OpenAI Agents SDK, Vercel AI SDK) head-to-head on the same dataset with LLM-as-a-judge scoring. Use when comparing agents, benchmarking, or wanting side-by-side evaluation. Do NOT use when comparing only orq.ai configurations with no external agents (use run-experiment instead).
Universal AI image generation supporting OpenAI DALL·E / gpt-image, Google Gemini Image / Imagen, Replicate (Flux / SDXL / any model), Stability AI, FAL, Ark (Seedream 4.5), Bailian (qwen-image / wanx), and SiliconFlow. Use this skill whenever the user asks to generate, create, draw, illustrate, render, or synthesize images from text prompts or reference images. Typical phrases include "draw a ...", "generate an image of ...", "画一张 ...", "给我来张图", "make a poster of ...", "create an illustration ...", or any mention of image-generation model families like DALL·E, gpt-image, Flux, SDXL, Seedream, Imagen, Gemini image, Kolors, or Wanx. Always use this skill even if the user does not name a specific model — pick a provider based on their EXTEND.md defaults or available API keys in the environment. Do NOT use this skill when the user explicitly mentions 即梦 / Dreamina / Jimeng — those go to happy-dreamina instead.
Guide for implementing HolmesGPT - an AI agent for troubleshooting cloud-native environments. Use when investigating Kubernetes issues, analyzing alerts from Prometheus/AlertManager/PagerDuty, performing root cause analysis, configuring HolmesGPT installations (CLI/Helm/Docker), setting up AI providers (OpenAI/Anthropic/Azure), creating custom toolsets, or integrating with observability platforms (Grafana, Loki, Tempo, DataDog).
Transcribe non-realtime speech with Alibaba Cloud Model Studio Qwen ASR models (`qwen3-asr-flash`, `qwen-audio-asr`, `qwen3-asr-flash-filetrans`). Use when converting recorded audio files to text, generating transcripts with timestamps, or documenting DashScope/OpenAI-compatible ASR request and response fields.
Feature-complete companion for the actual CLI, an ADR-powered CLAUDE.md/AGENTS.md generator. Runs and troubleshoots actual adr-bot, status, auth, config, runners, and models. Covers all 5 runners (claude-cli, anthropic-api, openai-api, codex-cli, cursor-cli), all model patterns, all 3 output formats (claude-md, agents-md, cursor-rules), and all error types. Use when working with the actual CLI, running actual adr-bot, configuring runners or models, troubleshooting errors, or managing output files.
Atlas Cloud API integration skill — quickly call 300+ AI image generation, video generation, and LLM models through a unified API. Use this skill when the user needs to integrate AI image generation (e.g., Flux, Seedream, DALL-E), AI video generation (e.g., Kling, Sora, Seedance), or call LLM APIs (OpenAI-compatible format) into their project. Applicable scenarios include: generating images, generating videos, calling large language models, using Atlas Cloud API, configuring ATLASCLOUD_API_KEY, querying available model lists, searching models by keyword, uploading local images/media files, one-step quick generation, image-to-video, text-to-image, text-to-video, AI content creation tool integration. Even if the user doesn't explicitly mention Atlas Cloud, this skill should be considered whenever AI media generation API integration development is involved.
Universal AI video generation supporting OpenAI Sora, Google Veo 2/3, Runway Gen-3/Gen-4, Pika 2.2, Luma Dream Machine (Ray 2), FAL (Kling / Wan / Veo / Sora wrappers), Ark Seedance 1.5 Pro/Lite, Bailian Wanx (i2v), MiniMax Hailuo-02, and Vidu Q3. Use this skill whenever the user asks to generate, create, make, or synthesize a video from a text prompt or from a first-frame image. Covers text-to-video and image-to-video, with optional last-frame control on providers that support it. Typical phrases include "generate a video of ...", "make a 5-second clip of ...", "animate this image", "生成一段视频", "做个短片", or any mention of video-generation model families like Sora, Veo, Runway Gen, Kling, Wan, Seedance, Hailuo, Pika, Dream Machine, Vidu. Always use this skill even if the user does not name a specific model — pick a provider from their EXTEND.md defaults or available API keys. Do NOT use this skill when the user explicitly mentions 即梦 / Dreamina / Jimeng — those go to happy-dreamina instead.
[QianWen] Recommend the best Qwen model and parameters. TRIGGER when: choosing between Qwen models, comparing Qwen model pricing, understanding Qwen model capabilities, checking usage or billing, viewing cost history, when an execution skill needs model selection advice, or user explicitly invokes this skill by name (e.g. use qianwen-model-selector). DO NOT TRIGGER when: non-Qwen model discussions (OpenAI, Gemini, etc.), general AI questions unrelated to Qwen.
Use PAL MCP to orchestrate multiple AI models (Gemini, OpenAI, Grok, Ollama) for code reviews, debugging, planning, and CLI bridging