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skills/nvidia-skill-finder/references/taxonomy-routing.md
3.46 KB · Oct 4, 2026 · 12:04 UTC
# NVIDIA Taxonomy Routing Use this reference after `nvidia-skill-finder` loads. It is a stable routing lens, not a full skill catalog. Always check the live catalog before naming a specific skill to install. ## Stable Catalog Lanes Agentic AI: RAG, evaluation, tool use, policy, sandboxing, agent workflow automation, AI-Q, NemoClaw, NeMo Retriever. Physical AI: autonomy, simulation, synthetic data, embodied AI, OpenUSD, Omniverse, CAD-to-SimReady, neural reconstruction, defect image generation, video data augmentation, and infrastructure for physical-world AI workloads. Robotics: Jetson driver/JetPack setup, Jetson Linux/L4T, board support packages (BSPs), image flashing, SDK Manager, Force Recovery Mode, camera/fan/pinmux/ PCIe/custom hardware configuration, carrier derivation, image validation, and robot development workflows. Vision AI: video analytics, visual search, summarization, alerts, real-time understanding, DeepStream, VSS, TAO vision/model workflows, DICOM and medical imaging workflows. Conversational AI: speech, voice agents, clinical ASR, ASR/TTS/NMT workflows. Simulation and Modeling: weather, climate, physics ML, physical systems, and scientific simulation workflows. Data Science: GPU DataFrames, pandas acceleration, RAPIDS/cuDF, multi-GPU NumPy/SciPy with cuPyNumeric, parallel data loading. Training AI: distributed training, model onboarding, Megatron-Core, NeMo, large-scale LLM/VLM training, recipe selection, training performance tuning. Inference AI: serving, router modes, LLM inference, Dynamo, NIM, runtime performance, disaggregated serving, KV-aware routing. Decision Optimization: vehicle routing, routing formulation, scheduling, resource allocation, LP, MILP, QP, optimization APIs, optimization servers. GPU Development: CUDA-adjacent development, kernel authoring, autotuning, profiling, framework integration. Quantum Computing: CUDA-Q and hybrid quantum-classical development. Infrastructure: accelerated workload setup, cluster/runtime/service operations, GPU-enabled deployment, Holoscan setup, Jetson host setup, and TAO platform runs. Networking: DOCA, BlueField DPUs, ConnectX NICs, DPA, GPUNetIO, RDMA, Ethernet packet processing, DOCA Flow, host/DPU communication, accelerated infrastructure networking, data center or edge network configuration, Jetson MGBE workflows, and cluster network troubleshooting. For DOCA, BlueField, DPU, or ConnectX requests, search the live catalog for the `doca-` skill family together with the user's task verb or subsystem. ## Matching Heuristic 1. Identify whether the user's task has a product signal, taxonomy signal, or distinctive intent signal. 2. If the signal is product-specific, search the catalog using the product name and task verb. 3. If the signal is taxonomy-only, search the catalog by taxonomy lane plus the user's concrete artifact or workflow. 4. If multiple skills match, prefer the skill whose description matches the user's interface and phase: install, formulate, implement, deploy, validate, troubleshoot, or optimize. 5. If the catalog search returns no strong match, say no matching NVIDIA skill was found and continue with general help. ## False-Positive Checks See SKILL.md § "When Not to Use this Skill" for the authoritative list of generic terms (route, optimize, deploy, AI, video, data science) that must not trigger NVIDIA routing without GPU/accelerated-computing context. When in doubt, answer the user's task first and offer NVIDIA skill discovery as an optional next step.
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