tripy-compilationWork with the nvtripy compilation pipeline. Use when: using tp.compile, creating InputInfo or DimensionInputInfo, understanding the Trace → MLIR → TensorRT flow, configuring optimization levels, working with Executable objects, debugging compilation, using…tripy-constraintsAuthor input/output constraints for nvtripy operations using the declarative constraint DSL. Use when: defining input_requirements or output_guarantees, writing @wrappers.interface decorators, auto-casting dtypes, using GetInput/GetReturn/OneOf/If/Equal,…tripy-debuggingDebug and diagnose errors in nvtripy code. Use when: interpreting TripyException stack traces, enabling MLIR/TensorRT debug output, understanding error reporting with stack_info, using raise_error, configuring debug environment variables, tracing compilation…tripy-documentationWrite API documentation for nvtripy following project conventions. Use when: writing docstrings for ops or modules, adding code examples, using @export.public_api document_under paths, creating Sphinx RST cross-references, understanding the docs build…tripy-new-moduleAdd a new neural network module to nvtripy. Use when: creating an nn layer, implementing a Module subclass, adding a new layer like Linear/LayerNorm/Conv, defining parameters with DefaultParameter or OptionalParameter, using constant_fields decorator.tripy-new-operationAdd a new operation to nvtripy. Use when: implementing a new op, adding a frontend op, creating a trace op, registering an op in the API. Covers the full Frontend → Trace → MLIR pipeline including export decorators, constraint definitions, and init…tripy-testingWrite tests for nvtripy following project conventions. Use when: adding tests for ops, modules, trace operations, or compilation, using pytest parametrize, testing error cases with helper.raises, testing dtype combinations, understanding test directory…
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NVIDIA · Repositories und repräsentative Skills - Seite 4
Repository-Ansicht von 1.199 gesammelten Skills in 113 GitHub-Repositories.
srtctlRun srt-slurm (srtctl) inference benchmarks on a Slurm cluster. Use when setting up a checkout, writing or migrating a recipe, submitting a job, or reading its results.perf-goal-writerWrite or refine a ready-to-use /goal prompt for a performance benchmark, regression investigation or optimization campaign. Define measurable targets, a matched baseline, change boundaries, diagnostic evidence and completion criteria. Use for drafting the…add-config-fieldAdd, rename, or re-type a recipe or srtslurm.yaml field in srt-slurm so that it ships complete (schema, resolver, dry-run, docs, example, tests).dsight-queryAnalyze existing DSight reports through the read-only SQLite-backed CLI, Python or MCP query interface. Use when inspecting request latency, lifecycle, metrics, Nsight ranges or CPU samples, comparing runs, or gathering evidence for a dashboard view.slurm-job-sizingSize Slurm allocations, warmup and traffic for short debugging jobs or full srt-slurm benchmarks.design-rule-sweepPeriodic cleanup of srt-slurm drift - shrink the Design Rule baselines, fix stale agent docs, and open small focused PRs.validate-without-clusterVerify an srt-slurm change end to end without SLURM or GPUs, using dry-run, the mock orchestrator, and the launch snapshots.
docs-visual-reviewUse for docs visual audits, layout, typography, heroes, CSS, navigation, or interaction changes. Skip prose-only edits.review-codeReview a code repository for concrete issues in correctness, robustness, security, maintainability, tests, and integration. Use for repository-wide or focused code review where practical engineering judgment and strict scope control matter.review-technical-writingReview technical documents, guides, tutorials, proposals, reports, design documents, and technical blog posts for accuracy, clarity, completeness, structure, evidence, audience fit, and practical reader utility.review-commonShared evidence, scope, reporting, and scoring rules for the selected CI review task. Apply alongside one domain review skill.review-research-spikeReview exploratory experiments for valid methods, defensible evidence, reproducibility, and appropriately small implementations rather than production readiness.review-toolAssess a new reusable tool or library for correctness, usability, verification, and proportionate engineering.review-use-case-exampleAssess a new use case demonstration for a coherent, reproducible workflow that teaches its intended audience without unnecessary framework design.
cccl-styleUse when editing or reviewing CCCL code for style conventions; read common CCCL guidance and the path-specific references named by this skill.cccl-benchmarkingUse when asked to build/run a CCCL benchmark (CUB, Thrust, or libcu++), measure performance, or compare benchmark results between branches/commits.cccl-add-review-checkUse when adding or extending a rule in docs/cccl/development/review_checks.md; describes how to research, word, place, and validate a new review check.cccl-reviewUse when reviewing CCCL code changes (a working-tree diff, PR, or commit range); loads the cccl-style and cccl-test skills and the CCCL review checks.cccl-testUse when writing, updating, reviewing, or validating CCCL tests; read common CCCL test guidance and the path-specific references named by this skill.sass-diffUse when asked to check for SASS (or PTX) changes between commits, branches, or a local changeset; guides normalization, comparison, and reporting of CUDA disassembly diffs.
create-custom-graderUse when converting an existing benchmark, rubric, verifier, task YAML/JSON, or domain check into SkillEvaluator BYOG/BYOT custom evaluation.api-callerCall any REST API dynamically. Make GET, POST, PUT, DELETE requests to any endpoint with custom headers and JSON body.calculatorEvaluate mathematical expressions and unit conversions. Handles arithmetic, percentages, exponents, and common unit conversions (temperature, distance, weight). No external dependencies.task-listRequired for 4+ step requests; add tasks at start and update status after each step.text-analyzerAnalyze text content and produce statistics including word count, line count, character count, most frequent words, and readability metrics. Works on any plain text input provided inline or from a file path.simpleSummarize short user notes into clear action items.
analysis-scriptsWrite and run Python scripts to analyze quantum experiment data stored in HDF5 files. Use when the user asks to analyze experiment results, fit peaks or curves, extract features from measurement arrays, or when reusable analysis logic should be saved…experiment-executionReference guide for running individual quantum calibration experiments and interpreting their results. Use when the user asks to run a single experiment (e.g. resonator spectroscopy, qubit spectroscopy, T1, T2), inspect experiment plots with the VLM, or query…vlm-configurationConfigure the Vision Language Model (VLM) used for analyzing experiment plots. Use when the user asks to change the VLM provider or model, adjust temperature or max_tokens, enable or disable thinking mode, or troubleshoot VLM-related behavior in config.yaml.workflow-executionExecute a previously planned calibration workflow node by node, tracking progress and handling failures. Use when the user asks to run, resume, or continue an existing workflow, or to execute a sequence of calibration steps that has already been defined in…workflow-planningPlan a new calibration workflow by discussing experiment sequences, success/failure criteria, and extracted parameters with the user before any files are created. Use when the user asks to plan, design, or create a new calibration sequence, or to build a…writing-experiment-scriptsAuthor new experiment scripts that are compatible with the lab system's auto-discovery. Use when the user asks to create a new experiment type, add a custom measurement, or write a Python script that should be discoverable via the `lab` and `run_experiment`…
nreUse to drive NVIDIA Omniverse NuRec / Neural Reconstruction Engine (NRE) via the public NGC containers nvcr.io/nvidia/nre/nre and nvcr.io/nvidia/nre/nre-tools (NGC_API_KEY required) — train 3DGUT Gaussian reconstructions from NCore clips, generate aux data,…nurec-fixerUse to run NVIDIA DiffusionHarmonizer (public successor to the older Fixer recipes) to enhance, harmonize, evaluate, or fine-tune novel-view frames from NRE / NuRec / 3DGS / NeRF reconstructions. Do NOT use for training the 3D reconstruction itself (use…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…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…nurec-indexRouter for NVIDIA NuRec / NRE / 3DGUT / USDZ / NCore V4 / asset harvest / frame cleanup tasks — picks the right sibling (nre, ncore, asset-harvester, nurec-fixer, physical-ai-datasets). Use when the sub-skill is unclear or a multi-stage pipeline is needed; do…physical-ai-datasetsUse when the user wants to find, download, or pick a NVIDIA Physical AI dataset on Hugging Face for autonomous-vehicle, robotics, spatial intelligence, manipulation, or neural-reconstruction workflows. Catalog of every dataset under huggingface.co/nvidia with…
input-file-skillParse, modify, validate, and patch simulator input files. Use when working with reservoir simulation input files, testing scenarios, or validating simulation configurations. This implementation supports reference format (.DATA); other simulators use different…plot-skillPlot and compare simulation summary metrics. Use when visualizing time-series results, comparing multiple cases, or analyzing production performance. Supports single and multi-metric plots, case comparisons, and automatic metric keyword resolution.rag-skillRetrieve information from simulator manual and example DATA files. Use when answering keyword format questions, syntax queries, or when looking up official documentation and working examples. Essential for understanding keyword definitions, parameter tables,…results-skillRead and analyze simulation binary output files. Use when extracting summary data, grid properties, or running flow diagnostics (time-of-flight, tracer, allocation, F-Phi, Lorenz) from completed simulations.simulation-skillRun, monitor, and control simulations. Use when executing simulations, checking progress, or stopping running simulations. Supports foreground and background execution, progress monitoring, and process management.
opening-a-prUse when preparing or opening a pull request or issue for Megatron-Energon. Covers the PR template, the human-review checkbox, linked issues for external contributions, and what agents may and may not do on GitHub.pr-reviewReview a Megatron-Energon pull request in one pass for actionable bugs and regressions, then report a red/yellow/green verdict to help humans prioritize their review. Use when asked to review or triage a PR or branch diff.writing-docsUse when adding or changing user-facing behavior or documentation in Megatron-Energon, or when creating new .py, .sh or .md files that need license headers.writing-testsUse when adding or changing tests in Megatron-Energon, or when a code change needs test coverage. Covers the end-to-end test style, dataset fixtures, save/restore and multi-worker checks, and how to run focused tests.committingUse when creating git commits in Megatron-Energon. Covers Conventional Commit format, scopes, sign-off, and checking commits locally.
cloudai-docs-contributionWrite, edit, or review CloudAI documentation, including README.md, doc/, release notes, and docstrings.cloudai-remote-experimentRun, monitor, stop, and retrieve a CloudAI experiment (test scenario) on a remote Slurm or standalone cluster.cloudai-remote-installInstall or update a CloudAI checkout on a remote cluster for Slurm or standalone execution. Does not run benchmarks.cloudai-workload-contributionCreate, modify, or review CloudAI workload implementations. Use for workload Python code, not for TOML-only configuration changes.cloudai-config-contributionCreate, adapt, review, or troubleshoot CloudAI system, test, and test-scenario TOML configurations. Use for CloudAI config-file requests, not for implementing workload Python code.
add-sourceGuide for adding a new data source to PhysicsNeMo Curator. Use when adding a remote dataset (HuggingFace, S3, etc.) or local file-based source. Covers discovery questions, file format handling, Mesh/DataArray/AtomicData construction, parallel partitioning,…add-sinkGuide for adding a new sink to PhysicsNeMo Curator. Covers discovery questions, implementation patterns (simple writer, append-based, split-based), output naming, parallel partitioning, testing, and registration.add-filterGuide for adding a new filter to PhysicsNeMo Curator. Covers discovery questions, implementation patterns (pass-through, stateful, in-place), generator semantics, flush/artifacts, dashboard widgets, merge for parallel workers, testing, and registration.curator-reviewerReview PRs against PhysicsNeMo Curator standards. Runs 8 review passes covering API conformance, correctness, licensing, quality gates, test coverage, performance, code quality, and style consistency. Produces a prioritized report (P0/P1/P2/NIT) and…testingRun Python and Rust tests for physicsnemo-curator using uv + pytest with coverage reporting via pytest-cov, and cargo-nextest for Rust tests. Includes benchmark workflows with pytest-benchmark and criterion.
nemo-clinical-data-designerUse when generating synthetic tabular datasets via Data Designer — sampler columns, LLM columns, custom generators. Not for ASR audio.riva-nim-setupUse when getting started with NVIDIA Riva Speech NIMs: NGC access, Docker login for nvcr.io, NVIDIA Container Toolkit, GPU verification, Riva Python client.riva-ttsUse when the user wants to deploy, run, or test a TTS (speech-synthesis) Riva NIM — cloud-hosted (build.nvidia.com) or self-hosted Magpie / voice cloning.riva-asr-customUse when the user wants to deploy a custom-trained ASR model as a Riva NIM, or convert a NeMo model via nemo2riva / riva-build / riva-deploy / RMIR.riva-asrUse when the user wants to deploy, run, or test an ASR (speech-to-text) Riva NIM — cloud-hosted (build.nvidia.com) or self-hosted Parakeet/Canary/Whisper.