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概要と使いどころ
Use this skill whenever the user asks for an Excel spreadsheet, a .xlsx file, or a workbook with formulas/pivots/multiple sheets — creating one from scratch or editing an existing one. Covers the rule that computed values must be written as real Excel formulas (never hardcoded numbers), and a static formula-safety check. Formulas are NOT recalculated in this environment — see 'Not supported'.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill whenever the user asks for a PDF — generating a new one from scratch (reports, invoices, letters), extracting text/tables from an existing PDF, or filling in an existing PDF form. Does not cover converting an existing Word/PowerPoint/Excel file to PDF (that requires LibreOffice, not available in this environment — see file-conversion).
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill whenever the user asks for a Word document, a .docx file, or a report/memo/letter/proposal delivered as one — creating a new document from scratch, editing an existing .docx, or reading/summarizing the contents of one. Covers page layout, headings, tables, numbered/bulleted lists, page breaks, and a table of contents. Does not cover converting a .docx to PDF or .doc to .docx (see file-conversion for what conversions ARE supported in this environment).
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user asks about Codex Rules behavior, injected project rules, supported rule file locations, matching, or environment configuration.
日本語の概要は準備中です。原文の説明を表示しています。
Use when a PinMe Cloudflare Worker needs R2 object storage, including secure file or image upload, streaming download, metadata lookup, deletion, listing, Range requests, or R2+D1 coordination. Guides AI to use PinMe's automatically injected env.R2 binding without R2 credentials or manual Wrangler configuration.
日本語の概要は準備中です。原文の説明を表示しています。
Deterministic mathematical computation using SymPy. Use for ANY math operation requiring exact/verified results - basic arithmetic, algebra (simplify, expand, factor, solve equations), calculus (derivatives, integrals, limits, series), linear algebra (matrices, determinants, eigenvalues), trigonometry, number theory (primes, GCD/LCM, factorization), and statistics. Ensures mathematical accuracy by using symbolic computation rather than LLM estimation.
日本語の概要は準備中です。原文の説明を表示しています。
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.
日本語の概要は準備中です。原文の説明を表示しています。
Use when writing, reviewing, or refactoring SwiftUI code for iOS or macOS, including state and `@Observable` data flow, view composition, resizable layouts, safe areas, display scale, performance, lists, environment, localization, animation, Liquid Glass, and API migration. Also use for iPhone Duo, foldable, or large-display layouts (`NavigationSplitView` on large displays, iPhone tab sidebar, two-column reflow, foldable grids, `ArrangementView`, `ReservedRegion`), hinge effects, vertical bars, `@State` initialization or synthesized-property diagnostics, `@ContentBuilder` ambiguity, `reorderable` drag/drop, custom `AsyncImage` `URLSession`, swipe actions outside List, item-bound `alert`/`confirmationDialog`, `ToolbarOverflowMenu`, `AnimatableValues`, Document APIs (`Document`/`DocumentReader`), and Instruments `.trace` capture or analysis.
日本語の概要は準備中です。原文の説明を表示しています。
Interactive setup wizard for the claude-ops plugin. Installs missing CLIs, configures env vars for each channel (Telegram, WhatsApp, Email, Slack, Notion, Linear, Sentry, Vercel), builds the project registry, and saves user preferences. Run once after installing the plugin or any time to reconfigure.
日本語の概要は準備中です。原文の説明を表示しています。
Automate Vercel tasks via Rube MCP (Composio): manage deployments, domains, DNS, env vars, projects, and teams. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。
Automate DocuSign tasks via Rube MCP (Composio): templates, envelopes, signatures, document management. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。
Audit, prepare, and deploy PAIDF Orchestration on a Kubernetes GPU cluster - single-GPU H100/L40S hosts, managed Kubernetes, kubeadm, and similar. Select for requests to set up, install, deploy, configure, or check a PAIDF Orchestration environment; run a workflow on a new or unverified GPU host; connect via kubeconfig; validate GPU compute; deploy the Airflow controller; or choose external versus in-cluster model services. A plain SSH host is not a supported backend.
日本語の概要は準備中です。原文の説明を表示しています。
Run the PAIDF Orchestration Event Video Generation DAG on Kubernetes - image-to-video anomaly generation, auto-labeling, and anomaly dataset generation. Select for requests about event video generation, anomaly video generation, image-to-video synthesis, Cosmos3 image2video, anomaly dataset creation, safety/surveillance SDG, or generating person-falling, person-climbing, person-running, fighting, smoking/vaping, fire/smoke, or shoplifting video clips from a seed image. Runs environment setup first when controller readiness is unknown. Not for person-crop clothing/attribute augmentation (that is image-attribute-augmentation-workflow) and not for video style transfer.
日本語の概要は準備中です。原文の説明を表示しています。
Run the PAIDF Orchestration Image Attribute Augmentation DAG on Kubernetes - person-crop clothing augmentation, attribute search, and augmented dataset generation. Select for requests about image attribute augmentation, person attribute search, person re-identification data, clothing augmentation, attribute captions, augmentation payloads, run status, or result retrieval. Runs environment setup first when controller readiness is unknown. Not for video or defect-image generation.
日本語の概要は準備中です。原文の説明を表示しています。
Official NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse, generative). Points at existing files via live repo search; never writes code. Do NOT use for installation or environment setup, training-loop or other code authoring/scaffolding, contributor/CI/packaging questions, repo-specific questions in physicsnemo-sym/-cfd/-curator, or general (non-physics) ML/PyTorch.
日本語の概要は準備中です。原文の説明を表示しています。
Plan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or Megatron-Bridge), pretraining/CPT, RL alignment (DPO/RLVR/GRPO/RLHF), BYOB/MCQ benchmarks, checkpoint conversion, ModelOpt optimization, env profiles, and evaluation of trained checkpoints or existing/hosted endpoints. Use when a request names a Nemotron step or workflow, or asks to clean, translate, train, fine-tune, align, convert, optimize, evaluate, or compose these into a pipeline. Do NOT use for frontend/dashboard/visualization work, generic ML advice, billing/access, or non-Nemotron coding tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Brev instance operating guidance for NeMo-RL agents working in /home/ubuntu/RL with limited workspace disk, a larger /ephemeral volume, and optional /home/ubuntu/RL/.env secrets. Use when running nemo-rl-auto-research campaigns, experiments, training jobs, model or dataset downloads, shared cache-heavy commands, log-producing runs, checkpoint generation, W&B or Hugging Face authenticated workflows, or any workflow that may create large files on Brev.
日本語の概要は準備中です。原文の説明を表示しています。
Autonomous NeMo-RL research agent workflow for directed hypothesis testing and open-ended discovery. Guides agents through the full experiment lifecycle: understanding recipes and environments, wiring RL or NeMo-gym runs, launching reproducible baselines and iterations, analyzing results, preserving human oversight, and using git plus TSV logs as the research ledger. Do NOT use for: bug fixes, code review, documentation, refactoring, dependency updates, or single-file changes.
日本語の概要は準備中です。原文の説明を表示しています。
How to launch distributed Megatron-LM training jobs on a SLURM cluster. Covers a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDA_DEVICE_MAX_CONNECTIONS rules across hardware and parallelism modes, container conventions, monitoring, and per-rank failure diagnosis.
日本語の概要は準備中です。原文の説明を表示しています。
Preflight and set up the root-level workflow runtime. Use for installation, missing component environments, or third-party failures; do not use for rollout validation.
日本語の概要は準備中です。原文の説明を表示しています。
Install Holoscan SDK v4.3+ via Conda in a CUDA 13 environment. Use for Conda installs; redirect CUDA 12 hosts to container/wheel.
日本語の概要は準備中です。原文の説明を表示しています。
Install Holoscan SDK Python wheel via pip into a venv. Use for Python installs; not for native C++/apt or Conda installs.
日本語の概要は準備中です。原文の説明を表示しています。
Adapt BOP datasets, run the FoundationPose perception pipeline with TAO depth, and evaluate or re-score pose results. Use for dataset runs and result comparisons; environment installation belongs to foundationpose-setup.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill to locate authoritative NVIDIA DOCA information without the source tree: the docs.nvidia.com page for a library/service/tool, which DOCA libraries are installed and at what version, a sample on disk or GitHub, a path under /opt/mellanox/doca, or a 404'd/renamed doc URL. Activate on implicit phrasing only when the conversation already names DOCA, BlueField, ConnectX, or /opt/mellanox. Do not activate for generic 'which version is installed' or 'where is the sample' questions with none of that context. Refuse and route elsewhere for hands-on programming, env prep, API tutorials, or hardware/firmware mutation — those belong to doca-programming-guide, doca-setup, the per-library skills, and doca-hardware-safety.
日本語の概要は準備中です。原文の説明を表示しています。