[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7CPC9X6CVATAFFANPVRKFWS":3,"skill-same:01M7CPC9X6CVATAFFANPVRKFWS":62},{"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":6,"ownerHtmlUrl":39,"ownerBlogUrl":6,"ownerDescription":40,"updatedAt":41,"install":42,"resources":55},"01M7CPC9X6CVATAFFANPVRKFWS","holoscan-install-source",null,"Build Holoscan SDK from source via the in-tree .\u002Frun script. Use only when published packages don't meet the user's needs.","om-scogo\u002Fskillsh-scraper","om-scogo","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F160466840?v=4","01M79AWB6DFVCQ7RK70CS34B96","Om Achrekar","01M79AWB6ZM9SKR8KDH1WSSM22",0,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fom-scogo\u002Fskillsh-scraper\u002Fblob\u002Fmain\u002Fdata\u002Fskills\u002Fnvidia-skills\u002Fholoscan-install-source\u002FSkill.md",[],[],"2026-11-15 14:19:17",false,"---\nname: holoscan-install-source\nversion: \"1.0.0\"\ndescription: \"Build Holoscan SDK from source via the in-tree .\u002Frun script. Use only when published packages don't meet the user's needs.\"\nlicense: Apache-2.0\nmetadata:\n  author: \"Holoscan Team \u003Choloscan-team@nvidia.com>\"\n  github-url: \"https:\u002F\u002Fgithub.com\u002Fnvidia-holoscan\u002Fholoscan-sdk\"\n  tags:\n    - holoscan\n    - install\n    - source\n    - build\n    - cmake\n---\n\n# Holoscan SDK — Build from Source\n\n## Purpose\n\nBuild the Holoscan SDK from the `nvidia-holoscan\u002Fholoscan-sdk` source tree using its `.\u002Frun` script (which builds inside a Docker container), producing a local install tree consumable as a CMake dependency.\n\n## Prerequisites\n\n- Linux host with NVIDIA GPU + driver (`nvidia-smi`).\n- `git`, Docker with NVIDIA Container Toolkit (`docker run --gpus all` works), and `docker-buildx-plugin`.\n- ~20 GB free disk for the build container + build\u002Finstall trees.\n- 10–30 min for a clean first build.\n\n## Limitations\n\n- Only recommended when published packages (Conda \u002F container \u002F apt \u002F wheel) don't fit — debug symbols, custom CMake options, or unsupported configs.\n- Still requires Docker — the `.\u002Frun` script builds inside a container; this is not a true bare-metal build.\n- Cross-compiling to aarch64 needs `qemu-user-static` on the host.\n\n## Step 0: Consult the Official Install Instructions\n\nAlways fetch the \"Build from Source\" section of `https:\u002F\u002Fdocs.nvidia.com\u002Fholoscan\u002Fsdk-user-guide\u002Fsdk_installation.html` (and the linked GitHub `README.md` \u002F `DEVELOP.md` for the chosen tag) before building. Extract: required `.\u002Frun` flags for the target architecture and CUDA major, supported branches\u002Ftags, any Dockerfile patches called out for the release, and the test names recommended for verification. If the doc disagrees with anything below, the doc wins.\n\n## Step 1: Prerequisites\n\nCheck that git and Docker (with GPU passthrough) are available:\n\n```bash\ngit --version\ndocker --version\ndocker run --rm --gpus all ubuntu:22.04 nvidia-smi\n```\n\n- If Docker is missing → help install from https:\u002F\u002Fdocs.docker.com\u002Fengine\u002Finstall\u002F\n- If GPU passthrough fails → install NVIDIA Container Toolkit:\n  ```bash\n  curl -fsSL https:\u002F\u002Fnvidia.github.io\u002Flibnvidia-container\u002Fgpgkey | sudo gpg --dearmor -o \u002Fusr\u002Fshare\u002Fkeyrings\u002Fnvidia-container-toolkit-keyring.gpg\n  curl -s -L https:\u002F\u002Fnvidia.github.io\u002Flibnvidia-container\u002Fstable\u002Fdeb\u002Fnvidia-container-toolkit.list \\\n    | sed 's#deb https:\u002F\u002F#deb [signed-by=\u002Fusr\u002Fshare\u002Fkeyrings\u002Fnvidia-container-toolkit-keyring.gpg] https:\u002F\u002F#g' \\\n    | sudo tee \u002Fetc\u002Fapt\u002Fsources.list.d\u002Fnvidia-container-toolkit.list\n  sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit\n  sudo nvidia-ctk runtime configure --runtime=docker && sudo systemctl restart docker\n  ```\n- If Docker buildx is missing: `sudo apt-get install docker-buildx-plugin`\n\n## Step 2: Clone the Repository\n\nClone repo to ~\u002Fholoscan\u002Fholoscan-sdk if needed\n\n```bash\nmkdir -p ~\u002Fholoscan\u002F\ngit clone https:\u002F\u002Fgithub.com\u002Fnvidia-holoscan\u002Fholoscan-sdk.git\ncd ~\u002Fholoscan\u002Fholoscan-sdk\n```\n\nTo build a specific release tag (recommended for stability):\n\n```bash\ngit tag | grep -E '^v[0-9]' | sort -V | tail -5   # list recent tags\ngit checkout v\u003CVERSION>                             # e.g. v4.1.0\n```\n\n## Step 3: Build\n\nThe `.\u002Frun build` script handles container creation, CMake configuration, compilation, and install in one step. Warn the user this takes **10–30 minutes** on first run (downloads base image + compiles).\n\n```bash\n.\u002Frun build\n```\n\nCommon options:\n\n| Flag | Purpose |\n|------|---------|\n| `--type debug` | Debug build (symbols, no optimization) |\n| `--type RelWithDebInfo` | Release + debug symbols |\n| `--arch aarch64` | Cross-compile for ARM64 (needs `sudo apt install qemu-user-static`) |\n| `--gpu igpu` | iGPU build for Jetson\u002FIGX |\n| `--dryrun` | Preview commands without executing |\n\nIf CMake cache errors occur after changing options:\n\n```bash\n.\u002Frun clear_cache && .\u002Frun build\n```\n\nOutput lands in these folders, and can be retrieved with `.\u002Frun get_build_dir` and `.\u002Frun get_install_dir`\n* Build dir: `build-cu\u003CN>-\u003Carch>\u002F`\n* Install dir: `install-cu\u003CN>-\u003Carch>\u002F`.\n\n## Step 4: Run Tests\n\nRun the following tests\n* EXAMPLE_CPP_HELLO_WORLD_TEST\n* EXAMPLE_PYTHON_HELLO_WORLD_TEST\n* EXAMPLE_CPP_TENSOR_INTEROP_TEST\n* EXAMPLE_PYTHON_TENSOR_INTEROP_TEST\n* EXAMPLE_CPP_VIDEO_REPLAYER_TEST\n* EXAMPLE_PYTHON_VIDEO_REPLAYER_TEST\n\n```bash\n.\u002Frun test\n```\n\nTo run all six required tests at once, use a single-quoted regex (the `|` must be quoted to prevent bash from treating it as a pipe):\n\n```bash\n.\u002Frun test --options \"-R 'EXAMPLE_CPP_HELLO_WORLD_TEST|EXAMPLE_PYTHON_HELLO_WORLD_TEST|EXAMPLE_CPP_TENSOR_INTEROP_TEST|EXAMPLE_PYTHON_TENSOR_INTEROP_TEST|EXAMPLE_CPP_VIDEO_REPLAYER_TEST|EXAMPLE_PYTHON_VIDEO_REPLAYER_TEST' --output-on-failure\"\n```\n\nRun a specific test by name or regex:\n\n```bash\n.\u002Frun test --name \u003Ctest_name>\n.\u002Frun test --options \"-R '\u003Cregex>' --output-on-failure\"\n.\u002Frun test --verbose\n```\n\n**Important:** Always single-quote the regex string when it contains `|` — without quotes, bash interprets `|` as a pipe and the command fails with `command not found`.\n\nExpected: all tests pass. Note any failures and report them to the user before continuing.\n\n## Step 5: Point Applications at the Install Tree\n\nOnce built, applications can use the install tree as a CMake dependency. Give the user this path:\n\n```\n\u002Fpath\u002Fto\u002Fholoscan-sdk\u002Finstall-cu\u003CN>-\u003Carch>\u002F\n```\n\nThey can set `Holoscan_ROOT` or `CMAKE_PREFIX_PATH` to this directory when building their own applications.\n\n## Troubleshooting\n\n| Symptom | Fix |\n|---------|-----|\n| `bash: \u003CTEST_NAME>: command not found` when running tests | The regex contains `\\|` — wrap it in single quotes: `--options \"-R '\u003Cregex>'\"` |\n| CMake cache errors after option change | `.\u002Frun clear_cache && .\u002Frun build` |\n| Docker buildx not found | `sudo apt-get install docker-buildx-plugin` |\n| GPU not visible inside build container | Verify NVIDIA Container Toolkit and re-run `sudo nvidia-ctk runtime configure --runtime=docker` |\n| Cross-compile fails (aarch64) | Install qemu: `sudo apt-get install qemu-user-static` |\n","# Holoscan SDK — Build from Source\n\n## Purpose\n\nBuild the Holoscan SDK from the `nvidia-holoscan\u002Fholoscan-sdk` source tree using its `.\u002Frun` script (which builds inside a Docker container), producing a local install tree consumable as a CMake dependency.\n\n## Prerequisites\n\n- Linux host with NVIDIA GPU + driver (`nvidia-smi`).\n- `git`, Docker with NVIDIA Container Toolkit (`docker run --gpus all` works), and `docker-buildx-plugin`.\n- ~20 GB free disk for the build container + build\u002Finstall trees.\n- 10–30 min for a clean first build.\n\n## Limitations\n\n- Only recommended when published packages (Conda \u002F container \u002F apt \u002F wheel) don't fit — debug symbols, custom CMake options, or unsupported configs.\n- Still requires Docker — the `.\u002Frun` script builds inside a container; this is not a true bare-metal build.\n- Cross-compiling to aarch64 needs `qemu-user-static` on the host.\n\n## Step 0: Consult the Official Install Instructions\n\nAlways fetch the \"Build from Source\" section of `https:\u002F\u002Fdocs.nvidia.com\u002Fholoscan\u002Fsdk-user-guide\u002Fsdk_installation.html` (and the linked GitHub `README.md` \u002F `DEVELOP.md` for the chosen tag) before building. Extract: required `.\u002Frun` flags for the target architecture and CUDA major, supported branches\u002Ftags, any Dockerfile patches called out for the release, and the test names recommended for verification. If the doc disagrees with anything below, the doc wins.\n\n## Step 1: Prerequisites\n\nCheck that git and Docker (with GPU passthrough) are available:\n\n```bash\ngit --version\ndocker --version\ndocker run --rm --gpus all ubuntu:22.04 nvidia-smi\n```\n\n- If Docker is missing → help install from https:\u002F\u002Fdocs.docker.com\u002Fengine\u002Finstall\u002F\n- If GPU passthrough fails → install NVIDIA Container Toolkit:\n  ```bash\n  curl -fsSL https:\u002F\u002Fnvidia.github.io\u002Flibnvidia-container\u002Fgpgkey | sudo gpg --dearmor -o \u002Fusr\u002Fshare\u002Fkeyrings\u002Fnvidia-container-toolkit-keyring.gpg\n  curl -s -L https:\u002F\u002Fnvidia.github.io\u002Flibnvidia-container\u002Fstable\u002Fdeb\u002Fnvidia-container-toolkit.list \\\n    | sed 's#deb https:\u002F\u002F#deb [signed-by=\u002Fusr\u002Fshare\u002Fkeyrings\u002Fnvidia-container-toolkit-keyring.gpg] https:\u002F\u002F#g' \\\n    | sudo tee \u002Fetc\u002Fapt\u002Fsources.list.d\u002Fnvidia-container-toolkit.list\n  sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit\n  sudo nvidia-ctk runtime configure --runtime=docker && sudo systemctl restart docker\n  ```\n- If Docker buildx is missing: `sudo apt-get install docker-buildx-plugin`\n\n## Step 2: Clone the Repository\n\nClone repo to ~\u002Fholoscan\u002Fholoscan-sdk if needed\n\n```bash\nmkdir -p ~\u002Fholoscan\u002F\ngit clone https:\u002F\u002Fgithub.com\u002Fnvidia-holoscan\u002Fholoscan-sdk.git\ncd ~\u002Fholoscan\u002Fholoscan-sdk\n```\n\nTo build a specific release tag (recommended for stability):\n\n```bash\ngit tag | grep -E '^v[0-9]' | sort -V | tail -5   # list recent tags\ngit checkout v\u003CVERSION>                             # e.g. v4.1.0\n```\n\n## Step 3: Build\n\nThe `.\u002Frun build` script handles container creation, CMake configuration, compilation, and install in one step. Warn the user this takes **10–30 minutes** on first run (downloads base image + compiles).\n\n```bash\n.\u002Frun build\n```\n\nCommon options:\n\n| Flag | Purpose |\n|------|---------|\n| `--type debug` | Debug build (symbols, no optimization) |\n| `--type RelWithDebInfo` | Release + debug symbols |\n| `--arch aarch64` | Cross-compile for ARM64 (needs `sudo apt install qemu-user-static`) |\n| `--gpu igpu` | iGPU build for Jetson\u002FIGX |\n| `--dryrun` | Preview commands without executing |\n\nIf CMake cache errors occur after changing options:\n\n```bash\n.\u002Frun clear_cache && .\u002Frun build\n```\n\nOutput lands in these folders, and can be retrieved with `.\u002Frun get_build_dir` and `.\u002Frun get_install_dir`\n* Build dir: `build-cu\u003CN>-\u003Carch>\u002F`\n* Install dir: `install-cu\u003CN>-\u003Carch>\u002F`.\n\n## Step 4: Run Tests\n\nRun the following tests\n* EXAMPLE_CPP_HELLO_WORLD_TEST\n* EXAMPLE_PYTHON_HELLO_WORLD_TEST\n* EXAMPLE_CPP_TENSOR_INTEROP_TEST\n* EXAMPLE_PYTHON_TENSOR_INTEROP_TEST\n* EXAMPLE_CPP_VIDEO_REPLAYER_TEST\n* EXAMPLE_PYTHON_VIDEO_REPLAYER_TEST\n\n```bash\n.\u002Frun test\n```\n\nTo run all six required tests at once, use a single-quoted regex (the `|` must be quoted to prevent bash from treating it as a pipe):\n\n```bash\n.\u002Frun test --options \"-R 'EXAMPLE_CPP_HELLO_WORLD_TEST|EXAMPLE_PYTHON_HELLO_WORLD_TEST|EXAMPLE_CPP_TENSOR_INTEROP_TEST|EXAMPLE_PYTHON_TENSOR_INTEROP_TEST|EXAMPLE_CPP_VIDEO_REPLAYER_TEST|EXAMPLE_PYTHON_VIDEO_REPLAYER_TEST' --output-on-failure\"\n```\n\nRun a specific test by name or regex:\n\n```bash\n.\u002Frun test --name \u003Ctest_name>\n.\u002Frun test --options \"-R '\u003Cregex>' --output-on-failure\"\n.\u002Frun test --verbose\n```\n\n**Important:** Always single-quote the regex string when it contains `|` — without quotes, bash interprets `|` as a pipe and the command fails with `command not found`.\n\nExpected: all tests pass. Note any failures and report them to the user before continuing.\n\n## Step 5: Point Applications at the Install Tree\n\nOnce built, applications can use the install tree as a CMake dependency. Give the user this path:\n\n```\n\u002Fpath\u002Fto\u002Fholoscan-sdk\u002Finstall-cu\u003CN>-\u003Carch>\u002F\n```\n\nThey can set `Holoscan_ROOT` or `CMAKE_PREFIX_PATH` to this directory when building their own applications.\n\n## Troubleshooting\n\n| Symptom | Fix |\n|---------|-----|\n| `bash: \u003CTEST_NAME>: command not found` when running tests | The regex contains `\\|` — wrap it in single quotes: `--options \"-R '\u003Cregex>'\"` |\n| CMake cache errors after option change | `.\u002Frun clear_cache && .\u002Frun build` |\n| Docker buildx not found | `sudo apt-get install docker-buildx-plugin` |\n| GPU not visible inside build container | Verify NVIDIA Container Toolkit and re-run `sudo nvidia-ctk runtime configure --runtime=docker` |\n| Cross-compile fails (aarch64) | Install qemu: `sudo apt-get install qemu-user-static` |\n",{"name":5,"license":15,"version":24,"metadata":25,"description":7},"1.0.0",{"tags":26,"author":32,"github-url":33},[27,28,29,30,31],"holoscan","install","source","build","cmake","Holoscan Team \u003Choloscan-team@nvidia.com>","https:\u002F\u002Fgithub.com\u002Fnvidia-holoscan\u002Fholoscan-sdk","main","8859218955d9504cd18b59e7892100718039d3b4","data\u002Fskills\u002Fnvidia-skills\u002Fholoscan-install-source",1,"https:\u002F\u002Fgithub.com\u002Fom-scogo\u002Fskillsh-scraper","https:\u002F\u002Fgithub.com\u002Fom-scogo","SDE-1 @ Scogo ","2026-07-18 12:22:46",{"source":8,"skillName":5,"commands":43,"prompt":53,"zipAvailable":54},[44,47,50],{"tool":45,"command":46},"npx","npx skills add om-scogo\u002Fskillsh-scraper --skill holoscan-install-source",{"tool":48,"command":49},"bunx","bunx skills add om-scogo\u002Fskillsh-scraper --skill holoscan-install-source",{"tool":51,"command":52},"pnpm","pnpm dlx skills add om-scogo\u002Fskillsh-scraper --skill holoscan-install-source","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fom-scogo\u002Fskillsh-scraper\u002Fblob\u002Fmain\u002Fdata\u002Fskills\u002Fnvidia-skills\u002Fholoscan-install-source\u002FSkill.md",true,[56],{"path":57,"resourceType":58,"resourceTypeDesc":59,"sizeBytes":60,"sourceHtmlUrl":61},"metadata.json","REFERENCE","参考文档",442,"https:\u002F\u002Fgithub.com\u002Fom-scogo\u002Fskillsh-scraper\u002Fblob\u002Fmain\u002Fdata\u002Fskills\u002Fnvidia-skills\u002Fholoscan-install-source\u002Fmetadata.json",[63,71,76,83,88,95],{"skillNo":64,"name":65,"nameZh":6,"description":66,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":67,"licenseFileUrl":6,"sourceHtmlUrl":68,"categories":69,"keywords":70,"publishedAt":19},"01M7D6MC9FAAEV4CMNYX8W7JTG","arxiv-search","Search arXiv physics, math, and computer science preprints using natural language queries. Powered by Valyu semantic search.","MIT","https:\u002F\u002Fgithub.com\u002Fom-scogo\u002Fskillsh-scraper\u002Fblob\u002Fmain\u002Fdata\u002Fskills\u002Fyorkeccak-scientific-skills\u002Farxiv-search\u002Fskills\u002Farxiv-search\u002FSKILL.md",[],[],{"skillNo":72,"name":65,"nameZh":6,"description":66,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":67,"licenseFileUrl":6,"sourceHtmlUrl":73,"categories":74,"keywords":75,"publishedAt":19},"01M7D6M85CKKN87TA98VCQV4H7","https:\u002F\u002Fgithub.com\u002Fom-scogo\u002Fskillsh-scraper\u002Fblob\u002Fmain\u002Fdata\u002Fskills\u002Fyorkeccak-scientific-skills\u002Farxiv-search\u002FSkill.md",[],[],{"skillNo":77,"name":78,"nameZh":6,"description":79,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":67,"licenseFileUrl":6,"sourceHtmlUrl":80,"categories":81,"keywords":82,"publishedAt":19},"01M7D4ZTCS4DR3CE4JY06X84T2","working-with-legacy-code","Safely change and test untested codebases using Feathers' \"Working Effectively with Legacy Code\". Use when the user mentions \"legacy code\", \"no tests\", \"untested codebase\", \"how do I test this\", \"seams\", \"characterization tests\", \"golden master\", \"sprout method\", \"afraid to change this code\", \"monster method\", \"dependency breaking\", or \"inherited a messy codebase\". Also trigger when changing code without tests safely, getting a class under test when constructors, statics, or singletons block it, adding features to tangled modules, or planning incremental test coverage for an old codebase. Covers the legacy-code change algorithm, seams, characterization tests, sprout\u002Fwrap, and dependency-breaking techniques. For refactoring code that already has tests, see refactoring-patterns. 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Use when the user mentions \"font pairing\", \"which typeface\", \"line height\", \"responsive typography\", \"web font loading\", \"type hierarchy\", \"variable fonts\", \"FOUT\u002FFOIT\", \"typographic scale\", or \"the text is hard to read\". Also trigger when choosing between system fonts and web fonts, optimizing font-loading performance, or designing readable long-form content. Covers readability evaluation, CSS implementation, and performance optimization. For overall UI design systems, see refactoring-ui. For dramatic typographic experiences, see top-design.","https:\u002F\u002Fgithub.com\u002Fom-scogo\u002Fskillsh-scraper\u002Fblob\u002Fmain\u002Fdata\u002Fskills\u002Fwondelai-skills\u002Fweb-typography\u002Fweb-typography\u002FSKILL.md",[],[],{"skillNo":96,"name":90,"nameZh":6,"description":91,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":67,"licenseFileUrl":6,"sourceHtmlUrl":97,"categories":98,"keywords":99,"publishedAt":19},"01M7D4Z4MVYVY3NMJ18BNV6WNA","https:\u002F\u002Fgithub.com\u002Fom-scogo\u002Fskillsh-scraper\u002Fblob\u002Fmain\u002Fdata\u002Fskills\u002Fwondelai-skills\u002Fweb-typography\u002FSkill.md",[],[]]