Total 54,172 skills, AI & Machine Learning has 9012 skills
Showing 12 of 9012 skills
TopAI.tools platform help — curated AI tools directory (2,700+ tools, 120+ categories, ~1-1.9M monthly visits, daily updates). Covers free submission (48-hour review), Fast Track ($39, 24-48 hours, no queue), Boosted listing ($229, featured site-wide 7 days, top category spots), listing optimization for search visibility, and SEO backlink value. Use when submitting an AI tool to TopAI.tools, wondering if the $39 Fast Track is worth it, want a Boosted featured listing on TopAI.tools, comparing TopAI.tools with TAAFT or Futurepedia, or trying to optimize your TopAI.tools listing for clicks. Do NOT use for multi-directory launch coordination (use /sales-launch-directory). Do NOT use for other AI directories like TAAFT (use /sales-theresanaiforthat) or Futurepedia (use /sales-futurepedia).
Process this skill enables AI assistant to forecast future values based on historical time series data. it analyzes time-dependent data to identify trends, seasonality, and other patterns. use this skill when the user asks to predict future values of a time ser... Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
Integrate PICA into a LangChain/LangGraph Python application via MCP. Use when adding PICA tools to a LangChain agent, setting up PICA MCP with LangChain, or when the user mentions PICA with LangChain or LangGraph.
利用多模态AI分析商品主图，提取视觉特征和提示词。当用户提到分析产品图片、从商品图中提取视觉属性、识别产品Listing中的颜色/形状/材质/风格、反推图片提示词、批量视觉特征提取、将产品图信息转化为结构化数据、视觉属性统计、基于图片的商品分类、main image analysis, image feature extraction, visual attribute recognition, product image analysis, image classification, batch image analysis时触发此技能。即使用户未明确提及"图片分析"，只要其需求涉及从商品主图或附图中提取结构化信息，也应触发此技能。
Event-sourced task system for agent collaboration. Use when managing tasks, tracking work, handing off between agents, checking task queues, or reporting progress. Provides both MCP tools and a CLI (ql).
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.
Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines
Use when analyzing patient records, clinical notes, medical PDFs, FHIR data, or advising on how to present medical data in health-tech products — OCR interpretation, clinical summarization, differential diagnosis support, drug interaction flags
Generate optimized prompts for YouThumb.ai YouTube thumbnails. Guided 4-step workflow: collect person name, map visual assets, describe the video, then generate 5 distinct ready-to-paste prompts. Use when the user says "thumbnail prompt", "YouThumb prompt", "generate thumbnail", "miniature YouTube", "prompt for my thumbnail", "help me with YouThumb", or when preparing YouTube thumbnail prompts.
Integrate a HuggingFace Computer Vision model into the NVIDIA TAO Toolkit ecosystem (tao-core config, tao-pytorch trainer, tao-deploy TensorRT pipeline). Use when the user asks to "integrate a HuggingFace model into TAO", "add an HF model to TAO Toolkit", "wire a HuggingFace ViT/DETR/ SegFormer into tao-pytorch", "build a TAO trainer + deploy pipeline for an HF CV model", or pastes a HuggingFace model URL/ID and wants it turned into a TAO model. Covers the full 7-phase loop: prerequisites check, HuggingFace inspection and validation, codebase exploration, tao-core configuration and native trainer implementation, ONNX export plus TensorRT deploy integration, packaging and L0 testing, container-based end-to-end validation, and (conditional) accuracy/latency tuning. Supports classification, object detection, semantic / instance / panoptic segmentation, zero-shot detection, and depth estimation.
Provision a zero-config, no-signup Upstash Redis database for an AI agent via a single POST to `https://upstash.com/start-redis`. Use when an agent needs scratch Redis for short-term memory, conversation history, sub-agent work queues, or ranked recall and the user has not provided credentials. The database lives 3 days unless the user claims it.
Build, scaffold, extend, deploy, and troubleshoot event-driven AI agents and scheduled serverless agent apps on Azure Functions using azurefunctions-agents-runtime. Use when the user wants a scheduled agent, morning briefing, daily digest, timer agent, inbox summary, email or Teams briefing, background AI workflow, connector-triggered agent, event-driven AI automation, HTTP/chat agent, webhook-style agent, or Azure Functions hosted agent. Covers .agent.md, agents.config.yaml, Foundry gpt-4.1/gpt-5.x model choice, dynamic sessions for code execution and web browsing, built-in chat/API/MCP endpoints, remote MCP servers, Connector Namespaces, Office 365 or Teams MCP tools/triggers, custom Python tools, Agent Skills, azd deployment, local.settings.json, Application Insights, local development, and troubleshooting.