Total 56,879 skills, AI & Machine Learning has 9458 skills
Showing 12 of 9458 skills
Analyze traces of Claude Code sessions. Use this Skill when users mention session IDs in UUID format (composed of numbers and lowercase letters), time clues such as "just now", "today", "last time", troubleshooting Agent behavior reasons, wanting to view the content of a specific Claude Code session, or analyzing trace content.
Wren Engine CLI workflow guide for AI agents. Answer data questions end-to-end using the wren CLI: gather schema context, recall past queries, write SQL through the MDL semantic layer, execute, and learn from confirmed results. Use when: user asks a data question, requests a report or analysis, asks about metrics, revenue, customers, orders, trends, or any business data; user says 'how many', 'show me', 'what is the', 'top N', 'compare', 'trend', 'growth', 'breakdown'; user wants to explore, analyze, filter, aggregate, or summarize data from a database; agent needs to query data, connect a data source, handle errors, or manage MDL changes via the wren CLI.
Build and operate predictive models for logistics networks—demand forecasting at SKU/location/lane granularity; inventory positioning and safety stock optimization interfaces; ETA and lead-time prediction; capacity and congestion signals; route and network flow forecasting at model-integration level; cold chain and perishables; promotion and seasonality; model monitoring, drift, and backtesting against operational KPIs (fill rate, OTIF, WMAPE/MAPE). Use for predictive logistics, demand forecasting logistics, ETA prediction, inventory positioning, safety stock optimization, OTIF forecast, lane demand, WMAPE, logistics ML, capacity forecasting logistics, or cold chain forecast—not pure OR/MIP without logistics domain (operations-research-algorithm-developer), supply chain strategy only (supply-chain-manager), WMS feature dev (wms-developer), fleet telematics ingestion (geospatial-telematics-developer), generic ML without logistics (data-scientist), or EDI document mapping (edi-engineer).
Guides ML/research engineering for safeguards—safety classifier development, harm benchmarks and eval suites, labeled dataset design, fine-tuning and ablations, calibration and slice analysis, attack-surface research memos, and promotion criteria for new moderation models. Use when building or evaluating guardrail models, designing safety benchmarks, measuring precision/recall on policy categories, comparing mitigation techniques, or writing research reports on classifier improvements—not for production inference gateways (ml-infrastructure-engineer-safeguards), PII/leakage privacy research (privacy-research-engineer-safeguards), red-team attack campaigns (ai-redteam), AI governance policy (ai-risk-governance), general non-safety research (ai-researcher), or token-efficiency studies (research-engineer-scientist-tokens).
MoveIt2 SRDF generation, validation, and planning-semantics workflow. Use when creating, editing, regenerating, inspecting, or validating `.srdf` files, `gen_srdf()` sources, MoveIt planning groups, virtual joints, passive joints, end effectors, group states, disabled collisions, URDF-linked planning semantics, or SRDF handoff to CAD Explorer review. Use the URDF skill for robot structure, the SDF skill for simulator descriptions, and the render skill for rendering, Explorer links, and optional MoveIt2 controls.
Install cuOpt for Python, C, or as a server (pip, conda, Docker) — system requirements, install commands, and verification. Use when the user wants to install or verify cuOpt for any user-facing interface. For building cuOpt from source or contributing to cuOpt, see cuopt-developer.
Debug AutoDeploy accuracy regressions vs a reference score (PyTorch backend or published baseline). Use when an AutoDeploy model's eval score is significantly below the reference and the root cause is unknown.
Deploy Nemotron Voice Agent on Workstation (x86), Jetson Thor, or Cloud NIMs. Real-time speech-to-speech using NVIDIA ASR, TTS, LLM with WebRTC/WebSocket transport.
Summarize a video by calling the VLM NIM or the Long Video Summarization (LVS) microservice directly. For short videos (under 60s) call the VLM's OpenAI-compatible chat completions endpoint; for long videos (60s or longer) call the LVS microservice. Use when asked to summarize a video, describe what happens in a video, analyze a recording, call or debug LVS summarize/model/health/recommended-config/metrics endpoints, or configure and troubleshoot the LVS service that backs long-video summarization.
Connects NemoClaw to a local inference server. Use when setting up Ollama, vLLM, TensorRT-LLM, NIM, or any OpenAI-compatible local model server with NemoClaw. Trigger keywords - nemoclaw local inference, ollama nemoclaw, vllm nemoclaw, local model server, openai compatible endpoint, switch nemoclaw inference model, change inference runtime, nemoclaw additional model, nemoclaw sub-agent model, openclaw sub-agent, agents.list, sessions_spawn, vlm-demo, nemoclaw tool calling, ollama tool calls, vllm tool-call-parser, raw json in tui, nemoclaw inference options, nemoclaw onboarding providers, nemoclaw inference routing.
Manage Claude Code agent skills using the `asc` CLI tool. Use this skill when: (1) Listing available skills: "asc skills list", "what skills are available", "show me asc skills" (2) Installing skills: "asc skills install --name asc-cli", "install all skills", "add asc skills to my agent" (3) Viewing installed skills: "asc skills installed", "what skills do I have", "show my installed skills" (4) Removing a skill: "asc skills uninstall --name asc-auth", "remove a skill" (5) Checking for skill updates: "asc skills check", "are my skills up to date" (6) Updating skills: "asc skills update", "update my asc skills" (7) User asks "how do I install asc skills", "set up asc CLI skills", or "get the latest asc skills" (8) Troubleshooting skill installation or update issues (npx, skills CLI)
Design system and guidelines for Claude's built-in generative UI — the show_widget tool that renders interactive HTML/SVG widgets inline in claude.ai conversations. This skill provides the complete Anthropic "Imagine" design system so Claude produces high-quality widgets without needing to call read_me first. Use this skill whenever the user asks to visualize data, create an interactive chart, build a dashboard, render a diagram, draw a flowchart, show a mockup, create an interactive explainer, or produce any visual content beyond plain text or markdown. Triggers include: "show me", "visualize", "draw", "chart", "dashboard", "diagram", "flowchart", "widget", "interactive", "mockup", "illustrate", "explain how X works" (with visual), or any request for visual/interactive output. Also triggers when the user wants to display financial data visually, create comparison grids, or build tools with sliders, toggles, or live-updating displays.