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Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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Use whenever the agent creates, writes, moves, or renames a file in a team/delegate (shared) workspace, OR when the user asks to organize, clean up, restructure, audit, or find files in any workspace or the Vault, OR when starting a multi-file task or named project. Enforces a purpose-based folder convention (flat mode: notes/, data/, outputs/, scripts/, archive/; project mode: projects/<slug>/{docs,assets,source,reports,research}/), per-agent namespacing under shared/<agent_key>/, and pre-write discovery via memory_search, vault_search, knowledge_graph_search to surface related files and avoid duplicates. Trigger before any write_file or exec at workspace root, when starting a project, generating reports/assets/exports, delegating, or when the user says "messy", "where did I save", "tổ chức lại", "dọn workspace", "tạo report", "find related", "search vault". Do NOT trigger for read-only ops, edits inside an existing project tree (cloned repo), or short-lived files deleted in the same turn.

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Make a website's team or about page photos look like one set — scan the headshot folder locally, flag photos whose aspect ratio, brightness, colour temperature, background or resolution differ from the rest, write a shared photo spec, and optionally export every photo at the same crop and size. Use when building or fixing a team page, "our team photos look inconsistent", "make all headshots the same size", "standardize staff photos", or when adding a new hire's photo to an existing page. Uses the free ProfessionalHeadshot.io MCP for framing guidance and photo scores when connected; the local scan works without it.

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Insert urgent work as decimal phase (e.g., 72.1) between existing phases

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Submit an AI agent to agentlaunch (a Product Hunt-style directory for AI agents) and read the directory via a public, no-auth REST API. Use when listing, launching, publishing, or registering an agent, or browsing existing ones.

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Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

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。

Modern, clean UI/UX guidance + review skill. Use when you need actionable UX/UI recommendations, design principles, or a design review checklist for new features or existing systems (web/app). Focus on CRAP (Contrast/Repetition/Alignment/Proximity) plus task-first UX, information architecture, feedback & system status, consistency, affordances, error prevention/recovery, and cognitive load. Enforce a modern minimal style (clean, spacious, typography-led), reduce unnecessary copy, forbid emoji as icons, and recommend intuitive refined icons from a consistent icon set.

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Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

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Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.

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Writes an AI agent's ethos.md — a durable snapshot of its purpose, intended behavior, boundaries, and success criteria — from the answers gathered by ethos-explore. Renders the schema-v1 template, validates the front matter and required markdown sections, saves the file in the agent's repository, and reviews it with the user. Also edits an existing ethos.md. Use over generic planning skills for an agent's ethos.md.

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Use when accelerating existing genomics workflows with NVIDIA Parabricks, improving runtime or price/performance, converting pipeline steps to GPUs, or comparing CPU and GPU workflow outputs. Adds optional GPU steps in-place with runtime toggles (default off). Do NOT use for individual pbrun command routing — use parabricks.

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Set up or troubleshoot the Auto Ontology runtime. Use for Helm (the official install), Docker Compose, developer setup, and MCP connection to an existing deployment.

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Official NVIDIA-authored guidance for PhysicsNeMo ShardTensor domain parallelism — integrate domain parallelism into training/inference scripts (new or existing) with DDP or FSDP2, write and register shard patches to enable new layers/ops, and bootstrap multi-GPU correctness tests. Use when working with ShardTensor, scatter_tensor, domain parallelism, sequence/spatial sharding, ring attention, DeviceMesh + DDP/FSDP2 hybrid parallelism, or physicsnemo.domain_parallel. Do NOT use for generic PyTorch DDP/FSDP setup without domain parallelism, picking a PhysicsNeMo model or example (use physicsnemo-discover), or non-distributed training questions.

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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。

Use only to generate or update a governance skill card for a specified existing agent skill directory. Do not use for explaining, listing, comparing, or discussing skill capabilities.

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 for agent-assisted Auto-FL optimization of an existing NVFLARE job in simulation, POC, or production. Do not use for code conversion, diagnosis-only work, or deployment setup.

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Convert existing Hugging Face Transformers Trainer or TRL SFTTrainer training code into an NVFLARE federated job using flare.patch(trainer), local validation, and job export; use when the user names Hugging Face or preliminary source inspection identifies one Hugging Face owner, and not for manual PyTorch loops, Lightning, inference-only pipelines, deployment, or experiment workflows.

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Convert existing PyTorch Lightning training code into an NVFLARE federated job using the Lightning Client API patch, local validation, and job export; use only when the request names federated/NVFLARE conversion or asks multiple sites to train collaboratively while keeping each site's data local, and either names PyTorch Lightning or preliminary source inspection identifies one Lightning owner; do not use for non-federated Lightning work such as DDP, profiling, inference serving, or training-loop changes, nor for plain PyTorch, TensorFlow/Keras, other frameworks, deployment, POC/production lifecycle, or experiment workflows.

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。

Convert existing plain or manual PyTorch training code into an NVFLARE federated job using Client API model exchange, local validation, and job export; use when the user names plain PyTorch or preliminary source inspection identifies one plain-PyTorch owner, and not for Lightning, other frameworks, deployment, POC/production lifecycle, or experiment workflows.

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。

Generates BYO custom safety policies for NVIDIA Nemotron content-safety guardrails — Nemotron-Content-Safety-Reasoning-4B (text) and multimodal Nemotron-3-Content-Safety. Produces a Markdown policy, JSON taxonomy, and drop-in inference prompts. Maps rough words or an existing policy to V2 categories, adding custom categories or topic-following rules.

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Edit an existing workflow Scene or task contract. Use for assets, layout, cameras, randomization, task text, or success rules; do not use to create a new workflow.

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。

Switch the active Jetson target-platform pointer to an existing profile YAML. Use before customize/build/flash to change target; not for authoring profiles — use jetson-init-target instead.

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。

Author a new Jetson target-platform profile (reference_devkit + optional custom_carrier) and update the active pointer. Use to create a target; not for switching existing profiles.

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。