- Simready Foundation Update RequirementUse for updating SimReady requirement docs, semantics, validator alignment, and profile impact notes.NVIDIA/simready-foundation50
- Simready Foundation Update ValidatorUse for updating SimReady validators, failure messages, edge cases, and tests while preserving requirement semantics.NVIDIA/simready-foundation50
- Simready Foundation Update ValidatorUse for updating SimReady validators, failure messages, edge cases, and tests while preserving requirement semantics.NVIDIA/simready-foundation50
- Simready Foundation Update ValidatorUse for updating SimReady validators, failure messages, edge cases, and tests while preserving requirement semantics.NVIDIA/simready-foundation50
- Simready Foundation Update ValidatorUse for updating SimReady validators, failure messages, edge cases, and tests while preserving requirement semantics.NVIDIA/simready-foundation50
- Simready Foundation Validate Foundation ChangeUse for auditing SimReady requirement, validator, feature, profile, adapter, test, and skill consistency.NVIDIA/simready-foundation50
- Simready Foundation Validate Foundation ChangeUse for auditing SimReady requirement, validator, feature, profile, adapter, test, and skill consistency.NVIDIA/simready-foundation50
- Simready Foundation Validate Foundation ChangeUse for auditing SimReady requirement, validator, feature, profile, adapter, test, and skill consistency.NVIDIA/simready-foundation50
- Simready Foundation Validate Foundation ChangeUse for auditing SimReady requirement, validator, feature, profile, adapter, test, and skill consistency.NVIDIA/simready-foundation50
- Simready PackageGuide a user from a folder of USD files to a validated SimReady package: set up the venv (including the user-provided WRAPP wheel) and then run ``create_simready_package.py``, which performs pre-validation, build, and post-validation in one shot.NVIDIA/simready-foundation50
- Deepstream SopUse this skill when building, deploying, evaluating, debugging, or measuring latency for the DeepStream SOP Inference Microservice — a GPU-accelerated FastAPI service that detects whether operators perform assembly-line steps in order via event boundary detection (GEBD) plus VLM classification. Trigger even if the user does not name it: verify operator step sequence, detect missing or out-of-order SOP steps, score factory/work-cell video for procedure compliance, run VLM-based SOP checking on inNVIDIA/sop-monitoring-blueprints38
- Sop BuildOrchestrate the end-to-end SOP pipeline, including preflight prerequisite checks, verifying models and downloading assets, generating the DeepStream SOP microservice with RTSP output, evaluating the microservice, and building, deploying, and testing the VSS SOP blueprint. Use when asked to run the full SOP pipeline, set up the SOP pipeline from scratch, execute preflight checks, verify models, download assets, generate the SOP microservice, evaluate the microservice, build the VSS blueprint, depNVIDIA/sop-monitoring-blueprints38
- Sop By Action EvalUse when running by-action VLM evaluation (per-action-clip inference + accuracy metrics) against the BP evaluation-ms HTTP API. Invoked as /sop-by-action-eval <inputs.yaml> [natural language parameter overrides]NVIDIA/sop-monitoring-blueprints38
- Sop Cr FinetuningFine-tune Cosmos-Reason2 (CR2) VLM for SOP monitoring. Use when you need to launch and monitor a VLM training run with a given dataset ID.NVIDIA/sop-monitoring-blueprints38
- Sop Data AugmentationUse when the user wants to run data augmentation on an annotated dataset, configure augmentation parameters, check augmentation status, or understand what each QA augmentation type does (BCQ, MCQ, GQA, DMCQ, DSQA, ENQA)NVIDIA/sop-monitoring-blueprints38
- Sop Ddm FinetuningFine-tune DDM-Net temporal boundary detector for SOP monitoring. Use when you need to launch and monitor a DDM-Net training run with a given dataset ID.NVIDIA/sop-monitoring-blueprints38
- Sop E2e InferenceUse when running the e2e evaluation pipeline (temporal segmentation + action recognition + accuracy) against the BP evaluation-ms HTTP API. Invoked as /sop-e2e-inference <inputs.yaml> [natural language parameter overrides]NVIDIA/sop-monitoring-blueprints38
- Sop Ft OrchestrateAutonomous end-to-end orchestrator for SOP fine-tuning. Runs the full Import → Augment → DDM Train → VLM Train → Evaluate → RCA loop. Interprets RCA findings across DDM, VLM and augment axes, applies config fixes autonomously, and iterates until success criteria are met or max_pipeline_iterations reached. Call with a path to an inputs.yaml or with natural language.NVIDIA/sop-monitoring-blueprints38
- Sop RcaRoot cause analysis for SOP monitoring pipeline failures. Analyzes end-to-end evaluation logs, DDM temporal segmentation, VLM action recognition, training data, and fine-tuning configs to identify failure patterns and produce an evidence-driven RCA report with actionable improvement recommendations.NVIDIA/sop-monitoring-blueprints38
- Vss Call Vios ApiInteract with the VIOS (Video IO & Storage) microservice in a running VSS profile — manage cameras/sensors, RTSP streams, recordings, snapshots, and storage. Use when asked to add a camera, add an RTSP stream, list sensors, show configured sensors/cameras/streams, what sources are available, check stream status, start/stop recording, get a snapshot, or manage video storage. Always query the VIOS API directly — do not navigate the UI to answer these questions.NVIDIA/sop-monitoring-blueprints38
- Vss Generate Video ReportGenerate and query incident reports from VSS — look up incidents in Elasticsearch, analyze incident patterns, generate narrative reports. Use when asked about incidents, incident reports, PPE violations, safety events, or "what happened". Requires the alerts profile to be deployed.NVIDIA/sop-monitoring-blueprints38
- Vss Query AnalyticsQuery video analytics incidents, alerts, sensor data, and metrics from Elasticsearch via the VA-MCP server (port 9901). Use for any question about what happened in video — PPE violations, alerts, incidents, object counts, speeds, occupancy, or anything that requires looking up recorded events. This is the primary way to answer "what happened", "show me alerts", "any violations", "how many people", etc.NVIDIA/sop-monitoring-blueprints38
- Vss Search ArchiveSearch video archives using natural language — find events, objects, actions, and people across recorded video using Cosmos Embed1 semantic search. Use when asked to search for something in video, find events, locate objects, or query video archives. Requires the search profile to be deployed.NVIDIA/sop-monitoring-blueprints38
- Vss Sop BuildBuild a custom VSS SOP blueprint from the VSS 3.1 base, then deploy and test in a loop until fully operational. Use when asked to create the SOP blueprint structure, customize VSS compose for SOP, configure SOP services, set up the VSS agent for SOP, or scaffold the SOP app layer on top of met-blueprints 3.1.NVIDIA/sop-monitoring-blueprints38
- Vss Sop DeployBuild the DS-SOP Docker image and deploy the VSS SOP blueprint end-to-end. Use when asked to deploy SOP, build DS SOP, install SOP, set up the SOP pipeline, verify SOP models, start the SOP blueprint, simulate RTSP for SOP, run the SOP API test, or tear down SOP.NVIDIA/sop-monitoring-blueprints38
- Vss Sop TestRun post-deployment tests for the VSS SOP blueprint. Checks service health, ELK data pipeline, VIOS recording/livestream, and VSS agent (MCP, LLM, VLM, snapshot, video, report). Auto-debugs failures. Use when asked to test SOP, verify SOP deployment, check SOP services, validate SOP, run SOP health checks, or troubleshoot SOP after deploy.NVIDIA/sop-monitoring-blueprints38
- Vss Summarize VideoSummarize long videos, generate shift reports, and analyze extended recordings. Use when asked to summarize a video, generate a shift summary, analyze a long recording, or create a daily activity report. Requires the LVS profile to be deployed.NVIDIA/sop-monitoring-blueprints38
- Sflow Error AnalysisDiagnose and troubleshoot sflow workflow errors from log output, error messages, and task failures. Covers config validation errors, expression resolution failures, SLURM backend issues, probe timeouts, task crashes, and batch submission problems. Use when the user encounters an sflow error, pastes error output, asks to debug a failed workflow, or asks about sflow troubleshooting.NVIDIA/nv-sflow36
- Writing Sflow YamlWrite, create, and modify sflow YAML workflow configuration files. Covers schema structure, variable declarations, task DAGs, backends, operators, probes, replicas, artifacts, and modular composition. Use when the user asks to create an sflow YAML, configure a workflow, set up inference serving, or asks about sflow YAML syntax.NVIDIA/nv-sflow36
- Benchmark IsaaclabRun Isaac Lab benchmark scripts and interpret their outputs. Covers RL training throughput, non-RL environment step FPS, camera/load/startup benchmarks, batch suites, parameter gotchas, output files, and JSON result structure. Use when the user asks to run or compare Isaac Lab benchmarks. NOT for RL convergence or policy-quality validation, profiling capture (use profiling), trace analysis (use nsys-analyze), or applying performance fixes (use perf-tuning).NVIDIA/omniperf31
- Benchmark IsaacsimRun Isaac Sim benchmark scripts and interpret benchmark outputs. Covers camera, SDG, scene-loading, robot, lidar/radar/sensor benchmark scripts, common parameters, output files, and benchmark-specific pitfalls. Use when the user asks to run or compare Isaac Sim benchmark results. NOT for initial bottleneck triage (use diagnose-perf), profiling capture (use profiling), trace analysis (use nsys-analyze), or applying performance fixes (use perf-tuning).NVIDIA/omniperf31
- Diagnose PerfFirst-responder performance triage for Isaac Sim and Isaac Lab. Identifies bottleneck category (GPU-bound, CPU-bound, VRAM, loading) using nvidia-smi and system tools without profiling. Use when a user reports slow FPS, stuttering, high latency, or wants a quick health check before profiling. NOT for applying specific fixes (use perf-tuning), capturing traces (use profiling), or analyzing traces (use nsys-analyze).NVIDIA/omniperf31
- Install IsaaclabInstall Isaac Lab for Isaac Sim-backed workflows or Isaac Lab 3.0+ kit-less/Newton workflows, then verify the setup. Use when the user asks to install, set up, or build Isaac Lab.NVIDIA/omniperf31
- Install IsaacsimInstall Isaac Sim via pip or source build. Covers Docker setup, verification, and common install issues. Use when the user asks to install, set up, or build Isaac Sim.NVIDIA/omniperf31
- Install ProfilersInstall profiling tools for Isaac Sim / Isaac Lab / Kit-based applications. Covers Nsight Systems (`nsys` CLI), `sqlite3`, Tracy `csvexport`, canonical Tracy `capture`/`capture-release`, and `update` for memory strip tests, with optional `tracy-capture`/`tracy-update` aliases. Use when setting up a profiling environment, when nsys/sqlite3/csvexport/capture/update tools are missing, or before running profiling, nsys-analyze, or tracy-memory.NVIDIA/omniperf31
- Kit App Streaming DebugUse when investigating Kit app livestream performance bottlenecks, WebRTC/native StreamSDK lag, freezes, dropped frames, browser WebRTC stats, copy fence timeouts, NVST_R_BUSY, disconnects, or resolution mismatch warnings in omni.kit.livestream.NVIDIA/omniperf31
- Nsys AnalyzeAnalyze profiling data from Kit-based apps. Covers Omniverse-specific NVTX zone interpretation, phase detection using sqlite3, Tracy Statistics/Range Limit analysis, csvexport fallback queries, and two-version comparison methodology. Use after capturing profiles with the profiling skill. NOT for capturing traces (use profiling), adding zones to code (use profiling-api), or applying fixes (use perf-tuning).NVIDIA/omniperf31
- Nvtx PythonProfile Python functions with NVTX in non-Kit environments (Isaac Lab 3.0+ standalone, any Python app without Carbonite). Uses a bundled PYTHONPATH-scoped sitecustomize.py with sys.setprofile hook, NVTX push/pop ranges, module include/exclude filtering, and Nsight Systems integration. Use when CARB_PROFILING_PYTHON doesn't work (no Kit/Carbonite runtime), when profiling standalone Isaac Lab scripts, or when you need per-function Python tracing in nsys captures outside Kit.NVIDIA/omniperf31
- Perf TuningResolve common Kit/Isaac Sim/Isaac Lab performance issues using specific settings and configuration changes. Covers PresentFrame stalls, resolveSamplerFeedback, headless mode, multi-GPU tradeoffs, DLSS/DLSS-G, PhysX tuning, RTX presets (isaaclab_performance/balanced/quality), viewport gizmos, HydraEngine waitIdle, fsWatcher overhead, and CPU governor. Use when profiling data shows a specific bottleneck and you need the fix, when someone asks "why is it slow" and you have Tracy/nsys evidence, or NVIDIA/omniperf31
- ProfilingCapture performance traces using CPU ChromeTrace, Tracy, and Nsight Systems/NVTX for Kit-based applications (Isaac Sim, Isaac Lab, Kit SDK). Covers COLD/WARM/TRACY measurement separation, canonical Tracy capture sequence, last-resort force-kill handling, nsys profile commands, Kit profiler args, and lightweight export handoff to nsys-analyze. Use when running profiling captures, setting up trace collection, or troubleshooting capture failures. NOT for adding profiling zones (use profiling-api), NVIDIA/omniperf31
- Profiling ApiAdd profiling zones, metrics, and annotations to Kit-based C++ and Python code. Covers Carbonite macros (CARB_PROFILE_ZONE, CARB_PROFILE_FUNCTION, GPU zones), Python profiler API (decorators, begin/end), profiler masks, channels, Tracy plot data, event annotations, and automatic Kit Python function capture (CARB_PROFILING_PYTHON). Use when a developer asks how to add profiling spans to Kit/Carbonite code, configure masks/channels, record custom Tracy plots, or annotate traces with event markers.NVIDIA/omniperf31
- Resolve IssueTriggers when you are asked to resolve a specific GitHub issue for the sphinx-llm project. Guides you through a test-driven workflow to resolve the issue, ensuring it is ready for work and following project conventions.NVIDIA/sphinx-llm31
- Tracy MemoryProfile CPU and GPU memory allocations using Tracy in Kit-based applications after Tracy capture tooling is installed. Covers LD_PRELOAD setup for liballocwrapper.so, Kit memory-channel flags, capture binary isolation (unset LD_PRELOAD), tracy-update strip-test verification, Tracy Memory tab analysis, and debug symbol requirements. Use when investigating memory leaks, allocation hotspots, or VRAM growth in Isaac Sim, Isaac Lab, or Kit apps. Requires profiling capture setup plus install-profilersNVIDIA/omniperf31
- Using HolodeckUse when the user wants to provision, manage, or destroy GPU-enabled test environments via the holodeck CLI. Covers env.yaml config, create/dryrun/list/status/ssh/scp/delete/cleanup/get/os workflows, and common pitfalls.NVIDIA/holodeck31
- AccessibilityUnified accessibility auditing workflow across static analysis, runtime testing, ARIA patterns, keyboard navigation, and color contrast. Use this skill whenever the user mentions accessibility, a11y, WCAG, ARIA roles, axe tests, screen readers, focus management, keyboard navigation, color contrast, or wants to audit, verify, or fix accessibility on any component. Also use when writing or debugging .test.axe.ts files, checking tabindex management, or reviewing focus trapping behavior.NVIDIA/elements23
- Api DesignComponent API design patterns following Elements conventions for properties, attributes, CSS custom properties, slots, and events. Use this skill whenever the user is designing or deciding on a component API, choosing between properties vs attributes vs slots, naming CSS custom properties, designing events, avoiding impossible states, deciding whether to reflect to an attribute, using CSS Parts, implementing the DataElement interface, or applying the internal-host pattern. Also trigger when the NVIDIA/elements23
- Availability ReportGenerate a production availability report for NVIDIA Elements packages and documentation.NVIDIA/elements23
- Build SystemWireit orchestration, build optimization, caching strategies, and build troubleshooting for the Elements monorepo. Use this skill whenever the user asks about Wireit configuration, build tasks, build dependencies, cache invalidation, build performance, adding new build tasks to package.json, cross-package dependency patterns, sideEffects declarations, CI pipeline configuration, or diagnosing slow or failing builds. Also trigger when the user mentions wireit, vite build issues, pnpm run ci, or buNVIDIA/elements23
- Code ReviewComprehensive code review process for Elements monorepo changes. Provides structured feedback on type safety, testing, documentation, and adherence to project guidelines. Use this skill whenever the user asks you to review code, check staged changes, look at a diff, give feedback before committing, review a PR or merge request, or evaluate code quality. Trigger on phrases like "review my changes," "check my code," "give me feedback," "look at my staged files," "review this PR," or "before I commNVIDIA/elements23
- Component CreationGuide for creating new Elements components with all required files, base classes, metadata patterns, and test boilerplate. Use this skill whenever the user wants to create, scaffold, or set up a new component from scratch, needs to understand the required 10-file structure, asks about base classes and mixins (LitElement vs ButtonFormControlMixin), define.ts vs index.ts patterns, static metadata, component registration, or sub-component parent relationships. Also trigger when the user mentions crNVIDIA/elements23
- DocumentationGuidelines for writing documentation files including 11ty templates, Eleventy shortcodes, JSDoc annotations, and markdown content. Use this skill whenever the user works with documentation markdown files, Vale prose linting errors, Eleventy shortcodes (dodont, example), frontmatter, JSDoc annotations that must pass Vale, or the documentation site. Also trigger when the user mentions Vale errors, adding terms to the vocabulary, suppressing Vale rules, or writing and fixing prose in .md or .ts filNVIDIA/elements23
- Pattern CreationConvert validated playground templates or HTML compositions into reusable pattern files (*.examples.ts) in the pattern library. Use this skill whenever the user wants to save, persist, store, or catalog a template, prototype, composition, or playground result as a reusable pattern. Trigger on phrases like "save as pattern," "create pattern," "add to pattern library," "persist this template," "convert to examples.ts," or when the user has validated HTML and wants it stored in projects/internals/pNVIDIA/elements23
- TestingWrite and run automated tests for Elements components including unit, accessibility, visual, SSR, and lighthouse tests. Use this skill whenever the user wants to write, create, update, or debug test files (.test.ts, .test.axe.ts, .test.visual.ts, .test.ssr.ts, .test.lighthouse.ts). Also trigger when the user asks about createFixture, removeFixture, elementIsStable, emulateClick, untilEvent, runAxe, visual baselines, theme testing, or test structure patterns like describe block naming.NVIDIA/elements23
- TroubleshootingDiagnose and resolve common issues including test failures, build errors, performance regressions, and development environment problems. Use this skill whenever the user reports something broken, failing, timing out, hanging, or producing unexpected results. Trigger on test failures (elementIsStable timeouts, flaky tests, screenshot diffs), build errors (Cannot find module, wireit cache issues, stale output), CI/CD failures, Git LFS problems, port conflicts, lighthouse score regressions, SSR errNVIDIA/elements23
- TypescriptBest practices for TypeScript code including type safety, discriminated unions, type guards, and exhaustive checking. Use this skill whenever the user asks about TypeScript patterns, type safety, type assertions (as any, as unknown), non-null assertions, discriminated unions, exhaustive switch/never patterns, type guards, boolean trap parameters, race conditions in async code, memory leaks from closures, or sequential vs parallel async operations. Also trigger when reviewing TypeScript code for NVIDIA/elements23
- Physical Ai Defect Image GenerationUse when the user wants to orchestrate defect image generation with NVIDIA Cosmos AnomalyGen (Cosmos-Predict2-derived) on OSMO for PCBA, metal surface, and glass inspection. The Day 0 path handles cold-start with USD-to-ROI, image-edit augmentation, and AnomalyGen to create initial PCBA datasets. The Day 1 path performs inference and labeling on real images. This skill helps with first-time asset setup, creation of finetuning checkpoints, and configuring deployment. Trigger keywords: defect imagNVIDIA/physical-ai-data-factory17
- Physical Ai People Attribute SearchUse when running people attribute search (PAS) image augmentation and auto-labeling workflows on OSMO: flow selection, preflight, submit-time interpolation, monitoring, and output retrieval. Trigger keywords: people attribute search, PAS, person augmentation, attribute search, person re-identification, clothing augmentation, person crop augmentation.NVIDIA/physical-ai-data-factory17
- Physical Ai Video Data AugmentationUse when running video data augmentation and auto-labeling workflows on OSMO: flow selection, preflight, submit-time interpolation, monitoring, and output retrieval. Trigger keywords: video data augmentation, data enrichment, auto labeling, VDA demo, OSMO workflow, pseudo labeling.NVIDIA/physical-ai-data-factory17
- Asset HarvesterUse to install and run NVIDIA Asset Harvester (Apache-2.0) to extract per-object 3D Gaussian Splat assets (`gaussians.ply`) from AV NCore V4 clips or masked single images via SparseViewDiT + TokenGS, optionally producing `metadata.yaml` for NuRec object insertion. Do NOT use for full-scene reconstruction (use `nre`) or for inputs without per-object masks.NVIDIA/nurec-skills15
- NcoreUse when converting any sensor dataset into NVIDIA NCore V4 format (and feeding it to NuRec or a robotics-to-sim "r2s" pipeline). Covers ingesting raw cameras, LiDARs, radars, IMUs, depth or stereo into V4 sequences; authoring a new converter from the template; adapting PAI / Waymo / PandaSet / NuScenes to V4; handling non-AV rigs (mono+depth, mono+lidar, stereo, multi-stereo, RGB-D, COLMAP / SfM, ROS2 bag); and diagnosing a broken converter against `validate.py`. Do NOT use to train reconstructNVIDIA/nurec-skills15