[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7A6MTS7ADEVZ6ZMZHNHESA8":3,"skill-same:01M7A6MTS7ADEVZ6ZMZHNHESA8":76},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":34,"commitSha":35,"skillDirectory":36,"forksCount":37,"repositoryHtmlUrl":38,"repositoryHomepageUrl":39,"ownerHtmlUrl":40,"ownerBlogUrl":41,"ownerDescription":42,"updatedAt":43,"install":44,"resources":57},"01M7A6MTS7ADEVZ6ZMZHNHESA8","earth2studio-install",null,"Guide installing Earth2Studio via uv or pip, selecting model extras, and configuring the environment. Do NOT use for writing inference code, choosing models, or PhysicsNeMo questions.","themusebook\u002Fskills","themusebook","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F349927247?v=4","01M7A5C1RV5S3V5FF6ZACVDNRN","musebook","01M7A5C1SFC3KRZAXNN60XJ7KM",0,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fthemusebook\u002Fskills\u002Fblob\u002Fmain\u002Fpublic\u002Fapi\u002Fskills\u002Fnvidia\u002Fearth2studio-install\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: earth2studio-install\nversion: 0.16.0\nlicense: Apache-2.0\nmetadata:\n  author: NVIDIA Earth-2 Team\n  tags:\n    - earth2studio\n    - earth2\n    - python\n    - install\n    - deployment\n    - environment\ndescription: >\n  Guide installing Earth2Studio via uv or pip, selecting model extras, and\n  configuring the environment. Do NOT use for writing inference code, choosing\n  models, or PhysicsNeMo questions.\n---\n\n# Earth2Studio Installation Skill\n\n## Never install packages automatically\n\nYou **MUST NOT** install, upgrade, or modify packages on the user's\nbehalf. Provide the exact command; the user runs it. No exceptions.\n\n**Forbidden:** running `pip install`, `uv pip install`, `uv add`,\n`uv sync`, `conda install`, `apt install`, or any package manager.\n\n**Instead:** give the exact command and ask the user to run it.\nExplain why the package is needed.\n\nWhen a package is needed:\n\n1. Identify it\n2. Provide the exact command\n3. Explain why it is needed\n4. **Wait for the user to confirm they ran it**\n\nEven if the user says \"just install it\", give the command and require\nthem to execute it themselves.\n\n## Purpose\n\nHelp users install Earth2Studio and its optional model dependencies correctly for\ntheir use case. This skill handles package installation, optional-extra selection,\nenvironment variable configuration, and install verification.\n\n## Prerequisites\n\n- Python 3.10+ (3.13 recommended)\n- CUDA-capable GPU with compatible drivers for GPU extras\n- uv (recommended) or pip package manager\n- Internet access (packages installed from PyPI and GitHub)\n\nYou are helping a user install Earth2Studio and its optional model\ndependencies. Your only job is to get the package installed correctly\nfor their use case — do not write inference code, do not compose\nworkflows.\n\n## Core principle: docs are the source of truth\n\nEarth2Studio installation commands, version tags, and extra names change\nbetween releases. **Before executing or recommending any install command,\nfetch the live installation docs:**\n\n```text\nhttps:\u002F\u002Fnvidia.github.io\u002Fearth2studio\u002Fuserguide\u002Fabout\u002Finstall.html\n```\n\nParse the page for the current version tag, available extras, and any\nspecial build notes. The workflow below is structural guidance — the\nspecific commands come from the live page.\n\n## Instructions\n\n### Step 1. Fetch live docs\n\nUse WebFetch on the install URL above. Extract:\n\n- Current release version tag (e.g. `@0.14.0`)\n- Available optional extras by category\n- Known build quirks (e.g. `--no-build-isolation` for pip,\n  manual pre-installs)\n\nKeep this data in working memory for all subsequent steps.\n\n### Step 2. Understand the user's environment\n\nAsk (cap at 3 questions, skip what the user already answered):\n\n1. **Package manager** — uv (recommended) or pip? If unsure, recommend\n   uv and link \u003Chttps:\u002F\u002Fdocs.astral.sh\u002Fuv\u002Fgetting-started\u002Finstallation\u002F>\n2. **Project context** — new project or adding to existing?\n3. **Python version** — recommend the version from the docs\n   (currently 3.13)\n\n### Step 3. Base install\n\nProvide commands from the live docs based on their answers:\n\n- **uv** uses a git source (not PyPI) to handle URL-based transitive dependencies\n- **pip** installs from PyPI but some extras require manual pre-install steps\n\nAfter the user runs the install, verify:\n\n```python\nimport earth2studio\nearth2studio.__version__\n```\n\n### Step 4. Select models and extras\n\nPresent the available extras organized by use case. Ask what the user\nplans to do — don't dump all options unprompted. Categories from the\ndocs:\n\n| Category | Example extras |\n|----------|---------------|\n| Prognostic (forecasting) | aifs, aurora, graphcast, pangu, sfno, stormcast, ... |\n| Diagnostic (post-processing) | corrdiff, climatenet, precip-afno, ... |\n| Data assimilation (beta) | da-healda, da-interp, da-stormcast |\n| Submodules | data, perturbation, statistics |\n\nThe exact list comes from the live docs — cite those, not this table.\n\nAsk:\n\n1. Which models do you plan to use?\n2. Do you need submodule extras (data sources, perturbation methods,\n   statistics)?\n3. Or install everything? (uv only: `--extra all`)\n\n### Step 5. Install selected extras\n\nProvide the exact commands from the live docs for their selections.\nKey warnings to surface:\n\n- **Slow builds**: flash-attention (AIFS variants), natten\n  (Atlas, StormScope), torch-harmonics CUDA extensions (FCN3, SFNO)\n  — can take 10-30+ minutes\n- **pip-specific manual steps**: some models require\n  `--no-build-isolation` or pre-installing packages like earth2grid,\n  torch-harmonics, or makani\n- **Data assimilation models**: require CuPy + cuDF (CUDA 12)\n\n### Step 6. Configuration (offer, don't force)\n\nMention environment variables the user might want to set — only if\nrelevant (e.g. limited disk, shared filesystem, CI environment):\n\n| Variable | Purpose |\n|----------|---------|\n| `EARTH2STUDIO_CACHE` | General cache directory |\n| `EARTH2STUDIO_DATA_CACHE` | Data source cache (overrides general) |\n| `EARTH2STUDIO_MODEL_CACHE` | Model checkpoint cache (overrides general) |\n| `EARTH2STUDIO_PACKAGE_TIMEOUT` | Max seconds for model downloads |\n\n## Troubleshooting\n\nIf installation fails, point the user to:\n\n- \u003Chttps:\u002F\u002Fnvidia.github.io\u002Fearth2studio\u002Fuserguide\u002Fsupport\u002Ftroubleshooting.html>\n- \u003Chttps:\u002F\u002Fnvidia.github.io\u002Fearth2studio\u002Fuserguide\u002Fsupport\u002Ffaq.html>\n\nCommon issues:\n\n- **PyTorch\u002FCUDA mismatch**: verify `torch.cuda.is_available()` first\n- **flash-attention build failure**: CUDA toolkit version must match\n  PyTorch CUDA\n- **ONNX Runtime GPU**: may need version-specific install for their CUDA\n- **ecCodes missing**: required for GRIB data handling; install via\n  `sudo apt-get install libeccodes-dev` (Debian\u002FUbuntu) or\n  `conda install -c conda-forge eccodes`\n- **Python.h: No such file or directory**: missing Python development\n  headers; install via `sudo apt-get install python3-dev`\n\n## Limitations\n\n- Cannot help with runtime errors unrelated to missing dependencies\n- Does not cover model checkpoint downloads (those happen at first inference)\n- Data source setup beyond the `data` extra is out of scope\n- Cannot write inference or training code, or compose Earth2Studio workflows\n\n## Ownership and out-of-scope\n\n**Owns:** package installation, optional-extra selection, environment\nvariable configuration, install verification.\n\n**Does not own:** writing inference or training code, composing\nEarth2Studio workflows, data source setup beyond the `data` extra,\nmodel checkpoint downloads (those happen at runtime), troubleshooting\nruntime errors unrelated to missing dependencies.\n","# Earth2Studio Installation Skill\n\n## Never install packages automatically\n\nYou **MUST NOT** install, upgrade, or modify packages on the user's\nbehalf. Provide the exact command; the user runs it. No exceptions.\n\n**Forbidden:** running `pip install`, `uv pip install`, `uv add`,\n`uv sync`, `conda install`, `apt install`, or any package manager.\n\n**Instead:** give the exact command and ask the user to run it.\nExplain why the package is needed.\n\nWhen a package is needed:\n\n1. Identify it\n2. Provide the exact command\n3. Explain why it is needed\n4. **Wait for the user to confirm they ran it**\n\nEven if the user says \"just install it\", give the command and require\nthem to execute it themselves.\n\n## Purpose\n\nHelp users install Earth2Studio and its optional model dependencies correctly for\ntheir use case. This skill handles package installation, optional-extra selection,\nenvironment variable configuration, and install verification.\n\n## Prerequisites\n\n- Python 3.10+ (3.13 recommended)\n- CUDA-capable GPU with compatible drivers for GPU extras\n- uv (recommended) or pip package manager\n- Internet access (packages installed from PyPI and GitHub)\n\nYou are helping a user install Earth2Studio and its optional model\ndependencies. Your only job is to get the package installed correctly\nfor their use case — do not write inference code, do not compose\nworkflows.\n\n## Core principle: docs are the source of truth\n\nEarth2Studio installation commands, version tags, and extra names change\nbetween releases. **Before executing or recommending any install command,\nfetch the live installation docs:**\n\n```text\nhttps:\u002F\u002Fnvidia.github.io\u002Fearth2studio\u002Fuserguide\u002Fabout\u002Finstall.html\n```\n\nParse the page for the current version tag, available extras, and any\nspecial build notes. The workflow below is structural guidance — the\nspecific commands come from the live page.\n\n## Instructions\n\n### Step 1. Fetch live docs\n\nUse WebFetch on the install URL above. Extract:\n\n- Current release version tag (e.g. `@0.14.0`)\n- Available optional extras by category\n- Known build quirks (e.g. `--no-build-isolation` for pip,\n  manual pre-installs)\n\nKeep this data in working memory for all subsequent steps.\n\n### Step 2. Understand the user's environment\n\nAsk (cap at 3 questions, skip what the user already answered):\n\n1. **Package manager** — uv (recommended) or pip? If unsure, recommend\n   uv and link \u003Chttps:\u002F\u002Fdocs.astral.sh\u002Fuv\u002Fgetting-started\u002Finstallation\u002F>\n2. **Project context** — new project or adding to existing?\n3. **Python version** — recommend the version from the docs\n   (currently 3.13)\n\n### Step 3. Base install\n\nProvide commands from the live docs based on their answers:\n\n- **uv** uses a git source (not PyPI) to handle URL-based transitive dependencies\n- **pip** installs from PyPI but some extras require manual pre-install steps\n\nAfter the user runs the install, verify:\n\n```python\nimport earth2studio\nearth2studio.__version__\n```\n\n### Step 4. Select models and extras\n\nPresent the available extras organized by use case. Ask what the user\nplans to do — don't dump all options unprompted. Categories from the\ndocs:\n\n| Category | Example extras |\n|----------|---------------|\n| Prognostic (forecasting) | aifs, aurora, graphcast, pangu, sfno, stormcast, ... |\n| Diagnostic (post-processing) | corrdiff, climatenet, precip-afno, ... |\n| Data assimilation (beta) | da-healda, da-interp, da-stormcast |\n| Submodules | data, perturbation, statistics |\n\nThe exact list comes from the live docs — cite those, not this table.\n\nAsk:\n\n1. Which models do you plan to use?\n2. Do you need submodule extras (data sources, perturbation methods,\n   statistics)?\n3. Or install everything? (uv only: `--extra all`)\n\n### Step 5. Install selected extras\n\nProvide the exact commands from the live docs for their selections.\nKey warnings to surface:\n\n- **Slow builds**: flash-attention (AIFS variants), natten\n  (Atlas, StormScope), torch-harmonics CUDA extensions (FCN3, SFNO)\n  — can take 10-30+ minutes\n- **pip-specific manual steps**: some models require\n  `--no-build-isolation` or pre-installing packages like earth2grid,\n  torch-harmonics, or makani\n- **Data assimilation models**: require CuPy + cuDF (CUDA 12)\n\n### Step 6. Configuration (offer, don't force)\n\nMention environment variables the user might want to set — only if\nrelevant (e.g. limited disk, shared filesystem, CI environment):\n\n| Variable | Purpose |\n|----------|---------|\n| `EARTH2STUDIO_CACHE` | General cache directory |\n| `EARTH2STUDIO_DATA_CACHE` | Data source cache (overrides general) |\n| `EARTH2STUDIO_MODEL_CACHE` | Model checkpoint cache (overrides general) |\n| `EARTH2STUDIO_PACKAGE_TIMEOUT` | Max seconds for model downloads |\n\n## Troubleshooting\n\nIf installation fails, point the user to:\n\n- \u003Chttps:\u002F\u002Fnvidia.github.io\u002Fearth2studio\u002Fuserguide\u002Fsupport\u002Ftroubleshooting.html>\n- \u003Chttps:\u002F\u002Fnvidia.github.io\u002Fearth2studio\u002Fuserguide\u002Fsupport\u002Ffaq.html>\n\nCommon issues:\n\n- **PyTorch\u002FCUDA mismatch**: verify `torch.cuda.is_available()` first\n- **flash-attention build failure**: CUDA toolkit version must match\n  PyTorch CUDA\n- **ONNX Runtime GPU**: may need version-specific install for their CUDA\n- **ecCodes missing**: required for GRIB data handling; install via\n  `sudo apt-get install libeccodes-dev` (Debian\u002FUbuntu) or\n  `conda install -c conda-forge eccodes`\n- **Python.h: No such file or directory**: missing Python development\n  headers; install via `sudo apt-get install python3-dev`\n\n## Limitations\n\n- Cannot help with runtime errors unrelated to missing dependencies\n- Does not cover model checkpoint downloads (those happen at first inference)\n- Data source setup beyond the `data` extra is out of scope\n- Cannot write inference or training code, or compose Earth2Studio workflows\n\n## Ownership and out-of-scope\n\n**Owns:** package installation, optional-extra selection, environment\nvariable configuration, install verification.\n\n**Does not own:** writing inference or training code, composing\nEarth2Studio workflows, data source setup beyond the `data` extra,\nmodel checkpoint downloads (those happen at runtime), troubleshooting\nruntime errors unrelated to missing dependencies.\n",{"name":5,"license":15,"version":24,"metadata":25,"description":7},"0.16.0",{"tags":26,"author":33},[27,28,29,30,31,32],"earth2studio","earth2","python","install","deployment","environment","NVIDIA Earth-2 Team","main","1c523aba5cdf867a79f078847075492d7778092a","public\u002Fapi\u002Fskills\u002Fnvidia\u002Fearth2studio-install",1,"https:\u002F\u002Fgithub.com\u002Fthemusebook\u002Fskills","https:\u002F\u002Fskills.x402.wtf","https:\u002F\u002Fgithub.com\u002Fthemusebook","https:\u002F\u002Fmusebook.trade","The official Github of musebook","2026-11-02 23:42:26",{"source":8,"skillName":5,"commands":45,"prompt":55,"zipAvailable":56},[46,49,52],{"tool":47,"command":48},"npx","npx skills add themusebook\u002Fskills --skill earth2studio-install",{"tool":50,"command":51},"bunx","bunx skills add themusebook\u002Fskills --skill earth2studio-install",{"tool":53,"command":54},"pnpm","pnpm dlx skills add themusebook\u002Fskills --skill earth2studio-install","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fthemusebook\u002Fskills\u002Fblob\u002Fmain\u002Fpublic\u002Fapi\u002Fskills\u002Fnvidia\u002Fearth2studio-install\u002FSKILL.md",true,[58,64,68,72],{"path":59,"resourceType":60,"resourceTypeDesc":61,"sizeBytes":62,"sourceHtmlUrl":63},"BENCHMARK.md","REFERENCE","参考文档",3852,"https:\u002F\u002Fgithub.com\u002Fthemusebook\u002Fskills\u002Fblob\u002Fmain\u002Fpublic\u002Fapi\u002Fskills\u002Fnvidia\u002Fearth2studio-install\u002FBENCHMARK.md",{"path":65,"resourceType":60,"resourceTypeDesc":61,"sizeBytes":66,"sourceHtmlUrl":67},"metadata.json",393,"https:\u002F\u002Fgithub.com\u002Fthemusebook\u002Fskills\u002Fblob\u002Fmain\u002Fpublic\u002Fapi\u002Fskills\u002Fnvidia\u002Fearth2studio-install\u002Fmetadata.json",{"path":69,"resourceType":60,"resourceTypeDesc":61,"sizeBytes":70,"sourceHtmlUrl":71},"skill-card.md",4027,"https:\u002F\u002Fgithub.com\u002Fthemusebook\u002Fskills\u002Fblob\u002Fmain\u002Fpublic\u002Fapi\u002Fskills\u002Fnvidia\u002Fearth2studio-install\u002Fskill-card.md",{"path":73,"resourceType":60,"resourceTypeDesc":61,"sizeBytes":74,"sourceHtmlUrl":75},"verification.json",1393,"https:\u002F\u002Fgithub.com\u002Fthemusebook\u002Fskills\u002Fblob\u002Fmain\u002Fpublic\u002Fapi\u002Fskills\u002Fnvidia\u002Fearth2studio-install\u002Fverification.json",[77,86,93,100,107,114],{"skillNo":78,"name":79,"nameZh":6,"description":80,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":82,"sourceHtmlUrl":83,"categories":84,"keywords":85,"publishedAt":19},"01M7AB34SPKVSDRRG009PM1CZH","youtube-clipper","YouTube 视频智能剪辑工具。下载视频和字幕，AI 分析生成精细章节（几分钟级别）， 用户选择片段后自动剪辑、翻译字幕为中英双语、烧录字幕到视频，并生成总结文案。 使用场景：当用户需要剪辑 YouTube 视频、生成短视频片段、制作双语字幕版本时。 关键词：视频剪辑、YouTube、字幕翻译、双语字幕、视频下载、clip video","MIT","https:\u002F\u002Fgithub.com\u002Fthemusebook\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fyoutube-clipper\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fthemusebook\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fyoutube-clipper\u002FSKILL.md",[],[],{"skillNo":87,"name":88,"nameZh":6,"description":89,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":6,"sourceHtmlUrl":90,"categories":91,"keywords":92,"publishedAt":19},"01M7AB18BH6N7KR7939HRNWVMQ","viem-integration","Integrate EVM blockchains using viem. 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Use when building custom swap logic, async swaps, hook-owned liquidity, custom curves, dynamic fees, MEV protection, limit orders, or oracle hooks.","https:\u002F\u002Fgithub.com\u002Fthemusebook\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fv4-hook-generator\u002FSKILL.md",[],[],{"skillNo":115,"name":116,"nameZh":6,"description":117,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":6,"sourceHtmlUrl":118,"categories":119,"keywords":120,"publishedAt":19},"01M7AAZYH75H4CS03WSW2EZ8DM","testing","For testing with Light Protocol programs and clients on localnet, devnet, and mainnet validation.","https:\u002F\u002Fgithub.com\u002Fthemusebook\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Ftesting\u002FSKILL.md",[],[]]