Total 51,097 skills, AI & Machine Learning has 8558 skills
Showing 12 of 8558 skills
Eval enablement accelerator — help customers think through "what does good look like" for their AI agent, then generate a structured eval plan and test cases they can use immediately. No running agent required. Works from a description, an idea, or even a vague goal. Use when anyone mentions agent evaluation, eval planning, "what should we test", "how do we know if the agent is good", test case generation, or interpreting eval results.
多模态产品图片相似度分析与分组。当用户提到产品图片相似度、视觉分组、查找外观相似的商品、基于图片去重、竞品同款检测、同款商品聚类、按外观分组、image similarity, product image comparison, visual clustering, same-style recognition, appearance deduplication, image grouping时触发此技能。即使用户未明确说"图片相似度"，只要其意图涉及商品主图对比、视觉聚类、识别视觉上相同或相似的商品，或根据外观、颜色、构图等视觉特征对商品列表进行后处理，也应触发此技能。
基于智慧芽的专利图片相似度搜索，支持通过图片URL检索外观设计专利和实用新型专利。当用户提到专利图片搜索、外观设计专利侵权检查、外观专利搜索、视觉专利查询、以图搜专利、专利相似度检测、专利图片匹配、洛迦诺分类搜索、检查产品设计是否侵犯已有专利、patent image search, design patent search, patent reverse image search, design patent lookup, PatSnap, patent similarity时触发此技能。即使用户未明确提及"智慧芽"或"专利图片"，只要其需求涉及通过图片查找相似专利或排查外观/实用新型专利风险，也应触发此技能。
Video outpainting on RunComfy via the `runcomfy` CLI — extend the spatial canvas of a video, change aspect ratio (9:16 vertical to 16:9 horizontal or vice versa), add environment beyond the original frame while preserving the central action. Routes prompt-shaped spatial extension through Wan 2-7 edit-video and points the agent at dedicated ComfyUI outpaint workflows when seam quality matters for hero delivery. Triggers on "video outpaint", "video outpainting", "extend video canvas", "expand video frame", "uncrop video", "aspect ratio change", "vertical to horizontal video", "16:9 from 9:16", "TikTok to YouTube", or any explicit ask to extend a video spatially beyond its original frame.
Go-to-market strategy for AI products. Use when positioning AI products, handling "who is responsible when it breaks" objections, pricing variable-cost AI, choosing between copilot/agent/teammate framing, or selling autonomous tools into enterprises.
Generate text-to-video with Wan 2.7 (Wan-AI's flagship motion model) on RunComfy. Documents Wan 2.7's strengths (multi-reference conditioning, audio-driven lip-sync via `audio_url`, smoother transitions, prompt expansion), the duration / resolution / aspect-ratio schema, and when to route to HappyHorse 1.0 / Seedance 2.0 / Kling / LTX 2 instead. Calls `runcomfy run wan-ai/wan-2-7/text-to-video` through the local RunComfy CLI. Triggers on "wan", "wan 2.7", "wan-2-7", "wan video", or any explicit ask to generate video with this model.
Start a new learning episode in the self-learning memory system with proper context. Use this skill when beginning a new task that should be tracked for learning from execution patterns.
Agno AI agent framework. Use for building multi-agent systems, AgentOS runtime, MCP server integration, and agentic AI development.
Complete setup for automated agent-driven development. Define features as user stories with testable acceptance criteria, then run AI agents in a loop until all stories pass.
Build new agent skills. Use when creating diagnostic frameworks, CLI tools, or data-driven generators that follow the established skill patterns.
This skill should be used whenever users request personal assistance tasks such as schedule management, task tracking, reminder setting, habit monitoring, productivity advice, time management, or any query requiring personalized responses based on user preferences and context. On first use, collects comprehensive user information including schedule, working habits, preferences, goals, and routines. Maintains an intelligent database that automatically organizes and prioritizes information, keeping relevant data and discarding outdated context.
Cost optimization patterns for LLM API usage — model routing by task complexity, budget tracking, retry logic, and prompt caching.