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Found 97 Skills
AI Native Camp Day 3 Clarify & GitHub. Clarify 플러그인으로 모호한 요구사항을 명확하게 만들고, 나만의 스킬을 만들고, PRD를 작성하여 GitHub에 첫 PR을 제출한다. "3일차", "Day 3", "clarify", "클래리파이", "PRD", "GitHub" 요청에 사용.
Authors and updates customization overrides for installed BMad skills. Use when the user says 'customize bmad', 'override a skill', 'change agent behavior', or 'customize a workflow'.
Hotel booking assistant. Use this skill whenever a user asks about booking hotels, searching for accommodation, or making hotel reservations. Guides users through search → select → pay → confirm. No API key required from users.
Text-to-speech models, voices, formats, and streaming via Venice.ai. Useful for narration, voiceover, and conversational agent voices.
AI-powered image editing with style transfer and object removal
Interact with Google Contacts to search and create contacts.
This skill should be used when the user provides a strategy, plan, or decision document and wants to surface hidden assumptions and blind spots using the Known/Unknown 4-quadrant framework. Trigger on "known unknown", "4분면 분석", "blind spots", "뭘 놓치고 있지", "뭘 모르는지 모르겠어", "전략 점검", "전략 분석", "assumption check", "가정 점검", "quadrant analysis", "what am I missing". Strategy-level blind spot analysis with hypothesis-driven questioning. For requirement clarification use vague; for content-vs-form reframing use metamedium.
Image generation skill based on Alibaba Cloud DashScope, supporting the creation of high-quality hand-drawn or standard images from user descriptions.
Asks for user feedback after each task or cron job completion and runs a recursive learning flow. If output is good, asks what was good until 10 approvals; if needs improvement, asks why/how/what via multiple choice plus optional examples, uses web search and iterative thinking to resolve, and caps iterations by severity (slight 5, medium 10, severe 20). Keeps feedback non-intrusive. Use when completing discrete tasks or cron jobs for the user.
Provides image recognition capabilities for non-multimodal models (such as pure text models like deepseek-v4-pro, GLM-5.1, mimo-v2.5-pro, etc.). This skill is automatically triggered when the main model cannot recognize images, when users send screenshots/design drafts/UI screenshots for analysis, or when users say 'Look at this image', 'Analyze this screenshot', 'What's wrong with this image'. It also applies to any scenario where users paste images but the current model does not support image input. Supports simultaneous recognition of multiple images, with primary-backup fallback achieved by configuring multiple image recognition models. It can also be manually triggered using the commands /skill:vision-support or /vision. Iron Rule: The models configured for this skill are only used for image content recognition and will never participate in main logical reasoning. Note: If the current model is itself a multimodal model (such as Claude Sonnet 4, GPT-4o, Gemini, etc. that can directly recognize images), do not use this skill; let the main model recognize directly.
Determine the stage of a research task and route it to a main workflow. Use when the user asks for "beginner's guide", "start research process", "what should I use for this research task", "help me choose a research skill", or requests the rw-research-router workflow. Runs without a private local workspace or preset research-lab; use user-provided material and bundled public-source methods.
Conduct in-depth research on topics and automatically generate knowledge relationship graph PDFs. After receiving a research topic, it automatically performs web research, information collection, knowledge organization, and finally generates a professional visualized relationship graph. Suitable for scenarios such as "research...and diagram", "in-depth analysis...and visualization", "generate knowledge graph", etc.