aiq-research
openbooklet.com/s/aiq-researchopenbooklet.com/s/[email protected]GET /api/v1/skills/aiq-researchUse when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.
Calibrate a new dataset from pre-recorded video files via the AutoMagicCalib REST API. Use when user has local MP4s and says 'calibrate my videos', 'run AMC on these videos', or similar. For RTSP/live streams, use amc-run-rtsp-calibration instead.
CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.
This skill is **Python only**. Routing has no C API in cuOpt.
This skill covers **starting the server** and **client examples** (curl, Python). Server has no separate C API (clients can be any language).
Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions.
Pre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
Load a sharded, on-disk dataset (sharded .npy, Parquet/Arrow, raw binary, sharded HDF5, custom layouts) into a distributed cuPyNumeric ndarray via a manual partition + leaf @task launch with CPU/OMP/GPU variants. Use when no single-call loader fits, including when per-shard row counts differ across files. Prefer cupynumeric.load or legate.io.hdf5.from_file when they apply.
This skill guides AI coding assistants in building, extending, and debugging the **NVIDIA DeepStream SOP (Standard Operating Procedure) Inference Microservice** â a GPU-accelerated pipeline for temporal action detection and VLM-based SOP compliance monitoring on industrial video feeds.
NVIDIA DeepStream SDK development with Python pyservicemaker API. Use when building video analytics pipelines, GStreamer-based video processing, TensorRT inference integration, object detection/tracking, or Kafka/message broker integration.
Use this skill to bring any vision model from HuggingFace or NVIDIA NGC into an NVIDIA DeepStream pipeline with end-to-end automation: ONNX download, SafeTensors export, TRT engine build, custom nvinfer bbox parser, multi-stream benchmark, and PDF report. Object detection models only.
Used for extracting selected metadata from one DICOM file and flagging standard-tag PHI presence. Not for anonymization or clinical use.
Stage 2 of the Clinical ASR Flywheel. Use when curating clinical terms, tagging IPA, and synthesizing a NeMo manifest. NOT for scoring (use /digital-health-clinical-asr-eval).
Stage 4 of the Clinical ASR Flywheel. Use when priority KER is above 0.3 to run stock NeMo SFT on Parakeet TDT v2 and offline cycle N+1 re-eval. NOT for generic word boosting (use /finetune-asr).
Stage 1 of Clinical ASR Flywheel. Use when bootstrapping a cycle: NVCF+MW disclosure, NVIDIA_API_KEY check, deps install, TTS+ASR smoke test.
**Where to start:** This skill assumes DOCA is already installed and the user is doing **hands-on AES-GCM-acceleration work** on a BlueField / ConnectX / host with DOCA. Open [`TASKS.md`](TASKS.md) if the user wants to *do* something (configure / build / modify / run / test / debug); open [`CAPABILI
**Where to start:** This is a tool skill for the **extension / plug-in framework** that augments [`doca-bench`](../doca-bench/SKILL.md) â NOT a workload-shape skill on its own. Open [`TASKS.md`](TASKS.md) and start at [`## configure`](TASKS.md#configure) to commit to the three-axis decision (workl
> â ï¸ **WARNING â irreversible hardware operations.** This skill guides > operators through potentially destructive, irreversible BlueField-4 > hardware operations: PLDM firmware burns, ISO reflashes, power > cycles, and BMC factory resets. These can brick firmware, corrupt > boot media, or cau
**Where to start:** This is a tool skill for invoking `doca_caps`, a side-effect-free CLI. Open [`TASKS.md`](TASKS.md) and start at [`## run`](TASKS.md#run) for the documented invocations, or [`## test`](TASKS.md#test) when using `doca_caps` as an install smoke-test. Open [`CAPABILITIES.md`](CAPABIL
**Where to start:** This skill assumes DOCA is already installed and the user is doing **hands-on Comch work** on a BlueField + host pair with DOCA. Open [`TASKS.md`](TASKS.md) if the user wants to *do* something (configure / build / modify / run / test / debug); open [`CAPABILITIES.md`](CAPABILITIE
Auto-indexed from NVIDIA/skills
Are you the author? Claim this skill to take ownership and manage it.
Related Skills
graceful-error-recovery
Use this skill when a tool call, command, or API request fails. Diagnose the root cause systematically before retrying or changing approach. Do not retry the same failing call without first understanding why it failed.
audience-aware-communication
Use this skill when writing any explanation, documentation, or response that will be read by someone else. Match vocabulary, depth, and format to the audience's expertise level before writing.
Refactoring Expert
Expert in systematic code refactoring, code smell detection, and structural optimization. Use PROACTIVELY when encountering duplicated code, long methods, complex conditionals, or any code quality issues. Detects code smells and applies proven refactoring techniques without changing external behavior.
Research Expert
Specialized research expert for parallel information gathering. Use for focused research tasks with clear objectives and structured output requirements.
clarify-ambiguous-requests
Use this skill when the user's request is ambiguous, under-specified, or could be interpreted in multiple ways. If proceeding with a wrong assumption would waste significant work, always ask exactly one focused clarifying question before doing anything.
structured-step-by-step-reasoning
Use this skill for any problem that involves multiple steps, tradeoffs, or non-trivial logic. Think out loud before answering to improve accuracy and transparency. Apply whenever the answer is not immediately obvious.