[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-nvidia-jetson-download-bsp":3,"mdc--2z283d-key":34,"related-org-nvidia-jetson-download-bsp":1714,"related-repo-nvidia-jetson-download-bsp":1873},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":23,"repoUrl":24,"updatedAt":25,"license":26,"forks":27,"topics":28,"repo":29,"sourceUrl":32,"mdContent":33},"jetson-download-bsp","download NVIDIA Jetson Linux BSP artifacts","Download NVIDIA Jetson Linux BSP artifacts (BSP tarball, sample rootfs, public_sources, x-tools, guides) for the active target. Use for Auto Setup; not for extraction or profile edits.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},"nvidia","NVIDIA","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fnvidia.png",[12,16,19,22],{"name":13,"slug":14,"type":15},"Hardware","hardware","tag",{"name":17,"slug":18,"type":15},"Linux","linux",{"name":20,"slug":21,"type":15},"Deployment","deployment",{"name":9,"slug":8,"type":15},2473,"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fskills","2026-07-14T05:30:32.917409","Apache-2.0",281,[],{"repoUrl":24,"stars":23,"forks":27,"topics":30,"description":31},[],"AI agent skills published by NVIDIA","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fskills\u002Ftree\u002FHEAD\u002Fskills\u002Fjetson-download-bsp","---\nname: jetson-download-bsp\ndescription: >-\n  Download NVIDIA Jetson Linux BSP artifacts (BSP tarball, sample\n  rootfs, public_sources, x-tools, guides) for the active target. Use\n  for Auto Setup; not for extraction or profile edits.\nversion: 0.0.1\nlicense: \"Apache-2.0\"\nmetadata:\n  data-classification: public\n  author: \"Jetson Team\"\n  tags: [setup, bootstrap, download]\n  domain: setup\n---\n\n# Download BSP Artifacts\n\n`jetson-download-bsp` owns network fetches for the Auto Setup path.\nIt does not extract archives, initialize source trees, register documents,\nor edit the active target profile. Those remain owned by\n`jetson-init-image`, `jetson-init-source`, and `jetson-link-docs`.\n\n## When to invoke\n\n- `\u002Fjetson-quick-start` selected `Auto Setup`.\n- The user wants NVIDIA BSP artifacts downloaded into the current\n  workspace before running setup skills.\n\n## Inputs and outputs\n\nResolve the active profile per\n[`..\u002F..\u002Fcontext\u002Ftarget-platform-contract.md`](..\u002F..\u002Fcontext\u002Ftarget-platform-contract.md).\nRefuse if no active profile exists.\n\nFollow the shared\n[`quick_start_prefill` contract](..\u002F..\u002Fcontext\u002Fbsp-customization-workflow.md#quick_start_prefill-contract).\nWhen invoked by `\u002Fjetson-quick-start`, this skill consumes\n`quick_start_prefill.mode` and `quick_start_prefill.download.bsp_release`\nas the requested release when present. Missing or invalid prefilled values\nare not fatal, but a concrete release is required before any download\nstarts.\n\nUse the workspace root as the parent of `target-platform\u002F`. Place files\nwhere downstream setup skills already search:\n\n| Artifact | Destination |\n|---|---|\n| Jetson Linux BSP tarball | `\u003Cbsp_image.root_path or workspace\u002FImage>\u002FJetson_Linux_R\u003Cver>_aarch64.tbz2` |\n| Sample rootfs tarball | `\u003Cbsp_image.root_path or workspace\u002FImage>\u002FTegra_Linux_Sample-Root-Filesystem_R\u003Cver>_aarch64.tbz2` |\n| `public_sources.tbz2` | `\u003Cworkspace>\u002FDownloads\u002Fpublic_sources.tbz2` |\n| `x-tools.tbz2` | `\u003Cworkspace>\u002FDownloads\u002Fx-tools.tbz2` |\n| Developer Guide | `\u003Cdocuments.root_path or workspace\u002FDocuments>\u002F` |\n| User Guide | `\u003Cdocuments.root_path or workspace\u002FDocuments>\u002F` |\n\nDo not write `bsp_image:`, `source:`, or `documents:` blocks. The next\nsetup skills will register derived metadata after extraction or user\nconfirmation.\n\n## Procedure\n\n### Resolve target release\n\nFetch the release list from:\n\u003Chttps:\u002F\u002Fdeveloper.nvidia.com\u002Fembedded\u002Fjetson-linux-archive>\n\nFrom the archive and linked release pages, list concrete releases that\nexplicitly support the active platform. Let the user choose a concrete\nJetson Linux \u002F L4T release token (`R36.4.4`, `36.4.4`, `38.2`,\n`38.2.1`, `38.4`, etc.); do not proceed with a family placeholder such\nas `R38.x`. A concrete release token is an optional leading `R` followed\nby two or three numeric dotted components. Preserve the token exactly as\nthe official page presents it; do not add `.0`, remove a patch component,\nor otherwise normalize it. Sort release choices by dotted numeric order\ndescending (newest first), comparing the components that are present; keep\nsource-provided recommendations in descriptions.\n\nResolve `quick_start_prefill.download.bsp_release` as follows:\n\n- Concrete and supported: continue with that release.\n- Missing, `skip`, blank, or a family placeholder (`R38.x`, `38.x`): show\n  supported concrete releases and ask the user to choose one.\n- Concrete but unsupported or ambiguous: stop before artifact discovery and\n  show the active platform, requested BSP release, supported concrete\n  releases, and source archive or release page.\n\nNever auto-substitute the requested release with a supported release, even\nwhen there is only one supported option.\n\nFor unsupported or ambiguous prefill, ask with the shared\n[`User input prompt style`](..\u002F..\u002Fcontext\u002Fbsp-customization-workflow.md#user-input-prompt-style),\nto choose exactly one click-to-select action:\n\n- `pick_supported_release` — user selects one supported concrete release.\n- `confirm_override` — user confirms the incompatible release and enters\n  an override reason.\n- `cancel` — stop with no downloads.\n\nDo not continue to \"Locate release artifacts\" until the selected release is concrete and\nsupported, or the user explicitly confirms override. Record any override\nreason in the final summary. If the user cancels, stop with no downloads.\nDo not claim support unless the archive or linked release page explicitly\nlists the active platform.\n\n### Discovery retries\n\nFor every artifact WebFetch in \"Resolve target release\" and \"Locate release artifacts\" (BSP, rootfs,\n`public_sources.tbz2`, `x-tools.tbz2`, Developer Guide, User Guide),\ntry 3 attempts before marking it missing:\n\n1. Focused prompt — artifact name + file type.\n2. Verbatim link dump on the same URL — *\"list every hyperlink, text\n   and href, no filtering\"*. Accept product-specific names and\n   `.html` indexes.\n3. Verbatim dump on a sibling page — Jetson Linux archive, JetPack\n   downloads, or `https:\u002F\u002Fdocs.nvidia.com\u002Fjetson\u002Farchives\u002Fr\u003Cver>\u002F`.\n\nOnly after all 3 fail, route to user-paste \u002F skip. Never fabricate\nURLs.\n\n### Locate release artifacts\n\nFollow links from the selected release page. Never construct NVIDIA\ndownload URLs by string concatenation.\n\nRequired artifacts:\n\n- Jetson Linux BSP image tarball.\n- Tegra Linux sample root filesystem tarball.\n- `public_sources.tbz2`.\n- `x-tools.tbz2` \u002F **Crosstool-NG Toolchain gcc** matching the selected\n  BSP release.\n- Developer Guide.\n- User Guide.\n\nIf a guide is not available as a direct file link, accept the release\ndocumentation URL as the artifact and record it in the final summary.\nIf the toolchain is listed on a JetPack downloads page instead of the\nrelease page, follow the official page link and match the selected BSP\nrelease; do not synthesize the URL from a release number.\nDo not proceed until each required artifact is downloaded, already\npresent at its destination, represented by a URL, or explicitly skipped\nby the user.\n\n### Show the fetch plan\n\nBefore changing the workspace, print a plan with:\n\n- selected release and release page URL;\n- active platform summary (`reference_devkit.name`, optional\n  `custom_carrier.name`, and `flash_config`);\n- source URL and destination path, or documentation URL, for every artifact;\n- any existing destination file that will be reused;\n- any artifact that requires browser\u002FEULA handling instead of `curl`.\n\nDefault to **Download all**. Do not ask an extra confirmation when every\nrequired artifact is downloadable, already present for reuse, or a\ndocumentation URL to record. Print the plan and continue to disk-space\nverification.\n\nStill stop and ask before side effects in any of these cases:\n\n- the release required an incompatibility override;\n- a required artifact is missing and needs user-paste \u002F skip;\n- a destination file would be overwritten rather than reused;\n- the artifact requires browser\u002FEULA handling;\n- disk-space verification fails or cannot be computed safely.\n\n### Verify disk space\n\nSum `Content-Length` across artifacts to download (`curl -sI \u003Curl>`);\nrefuse if `df -B1 --output=avail \u003Cworkspace>` headroom \u003C sum × 1.2.\nSkip URL-only artifacts.\n\n### Download safely\n\nCreate destination directories as needed. For direct file links, use a\ntemporary `.part` path and rename only after success:\n\n```bash\nmkdir -p \"\u003Cdestination-dir>\"\ncurl -fL --retry 3 --retry-all-errors --retry-delay 5 -o \"\u003Cdestination>.part\" \"\u003Cartifact-url>\"\nmv \"\u003Cdestination>.part\" \"\u003Cdestination>\"\n```\n\nIf a destination file already exists and is non-empty, reuse it by\ndefault after showing its path. Ask before overwriting. If an artifact\ndownload fails due to 404, 401\u002F403, EULA\u002Fbrowser authentication, or a\nnetwork error, stop and show the artifact URL plus expected destination\npath. Ask the user to download the file manually, skip that artifact, or\ncancel. Do not synthesize alternate NVIDIA URLs.\n\n### Validate filenames\n\nBefore finishing, verify the BSP and rootfs tarball filenames contain\nthe exact `R\u003Cver>` token from the official artifact URL or filename\ndiscovered in Step 2. `\u003Cver>` may have two or three numeric components\n(`R38.2`, `R38.2.1`, `R38.4`, etc.). Do not infer `R38.2.0` from\n`R38.2`, and do not assume that a selected two-component release maps to\na three-component tarball name:\n\n- `Jetson_Linux_R\u003Cver>_aarch64.tbz2`\n- `Tegra_Linux_Sample-Root-Filesystem_R\u003Cver>_aarch64.tbz2`\n\nVerify `public_sources.tbz2` is a bzip2 tarball when it exists locally:\n\n```bash\nfile -b \"\u003Cworkspace>\u002FDownloads\u002Fpublic_sources.tbz2\" | grep -q \"bzip2 compressed\"\n```\n\nVerify `x-tools.tbz2` the same way when it exists locally:\n\n```bash\nfile -b \"\u003Cworkspace>\u002FDownloads\u002Fx-tools.tbz2\" | grep -q \"bzip2 compressed\"\n```\n\nWarn, but do not fail, if document filenames differ from the release\nversion; NVIDIA documentation naming is less consistent than tarballs.\n\n## Finish\n\nReport the selected release, downloaded\u002Freused\u002Fskipped artifacts, and\nexact local paths. Then hand back to the caller with:\n\n1. `\u002Fjetson-init-image`\n2. `\u002Fjetson-init-source`\n3. `\u002Fjetson-link-docs`\n\n## Gotchas\n\n- Keep this skill download-only; extraction belongs to\n  `jetson-init-image` and `jetson-init-source`.\n- Put image tarballs in the image root, not `Downloads\u002F`, because\n  `jetson-init-image` searches the image root, workspace root, and\n  current directory.\n- Put `public_sources.tbz2` in `Downloads\u002F` because\n  `jetson-init-source` auto-discovers that path for Branch A.\n- Put `x-tools.tbz2` in `Downloads\u002F` because `jetson-init-source`\n  auto-extracts that path and writes the resulting `source.toolchain`\n  prefix.\n- The User Guide maps to `documents.bsp_user_guide` in the profile\n  schema (alongside `bsp_developer_guide`). `jetson-link-docs` writes\n  it when the user confirms; this skill only stages the file or URL.\n\n## Purpose\n\nStage the four NVIDIA-shipped artifacts (BSP, sample rootfs,\npublic_sources, x-tools) plus the Developer \u002F User Guides at the exact\npaths the Setup skills look in, so `\u002Fjetson-init-image`,\n`\u002Fjetson-init-source`, and `\u002Fjetson-link-docs` can run offline once\nthis skill is done.\n\n## Prerequisites\n\n- Active target profile resolved per\n  `..\u002F..\u002Fcontext\u002Ftarget-platform-contract.md`.\n- Network access to `developer.nvidia.com` and the Jetson Linux archive\n  page.\n- Workspace layout with the expected `Image\u002F`, `Source\u002F`,\n  `Downloads\u002F`, and `Documents\u002F` roots (default workspace shape).\n\n## Limitations\n\n- Download-only; never extracts, runs `apply_binaries.sh`, mounts\n  sources, registers documents, or mutates the active profile.\n- Release selection is bounded to entries published on the official\n  Jetson Linux archive; pre-release or internal builds are out of\n  scope.\n- No retry \u002F mirror logic — failures are surfaced to the user, not\n  silently retried.\n\n## Troubleshooting\n\n- **Release page not reachable** — check VPN \u002F proxy; do not invent\n  fallback URLs. Stop and report.\n- **Archive name mismatch with active platform** — verify the release\n  declares the active reference devkit; if not, ask the user to pick a\n  supported release or switch target via `\u002Fjetson-set-target`.\n- **`public_sources.tbz2` missing on archive** — some releases ship it\n  as a separate page; follow the release-page link rather than\n  guessing the URL.\n- **Existing files in the destination** — refuse to overwrite without\n  confirmation; downloads must be idempotent at the user's discretion.\n\n## References\n\n- [`..\u002F..\u002Fcontext\u002Ftarget-platform-contract.md`](..\u002F..\u002Fcontext\u002Ftarget-platform-contract.md)\n- [`..\u002Fjetson-quick-start\u002FSKILL.md`](..\u002Fjetson-quick-start\u002FSKILL.md)\n- [`..\u002Fjetson-init-image\u002FSKILL.md`](..\u002Fjetson-init-image\u002FSKILL.md)\n- [`..\u002Fjetson-init-source\u002FSKILL.md`](..\u002Fjetson-init-source\u002FSKILL.md)\n- [`..\u002Fjetson-link-docs\u002FSKILL.md`](..\u002Fjetson-link-docs\u002FSKILL.md)\n- Jetson Linux archive: \u003Chttps:\u002F\u002Fdeveloper.nvidia.com\u002Fembedded\u002Fjetson-linux-archive>\n",{"data":35,"body":44},{"name":4,"description":6,"version":36,"license":26,"metadata":37},"0.0.1",{"data-classification":38,"author":39,"tags":40,"domain":41},"public","Jetson Team",[41,42,43],"setup","bootstrap","download",{"type":45,"children":46},"root",[47,56,92,99,127,133,150,192,205,342,370,376,383,395,461,473,513,518,535,571,576,582,600,642,647,653,658,663,713,718,724,729,787,799,804,832,838,867,873,886,1036,1041,1047,1105,1126,1138,1198,1209,1263,1268,1274,1279,1309,1315,1441,1447,1471,1477,1537,1543,1569,1575,1630,1636,1708],{"type":48,"tag":49,"props":50,"children":52},"element","h1",{"id":51},"download-bsp-artifacts",[53],{"type":54,"value":55},"text","Download BSP Artifacts",{"type":48,"tag":57,"props":58,"children":59},"p",{},[60,66,68,74,76,82,84,90],{"type":48,"tag":61,"props":62,"children":64},"code",{"className":63},[],[65],{"type":54,"value":4},{"type":54,"value":67}," owns network fetches for the Auto Setup path.\nIt does not extract archives, initialize source trees, register documents,\nor edit the active target profile. Those remain owned by\n",{"type":48,"tag":61,"props":69,"children":71},{"className":70},[],[72],{"type":54,"value":73},"jetson-init-image",{"type":54,"value":75},", ",{"type":48,"tag":61,"props":77,"children":79},{"className":78},[],[80],{"type":54,"value":81},"jetson-init-source",{"type":54,"value":83},", and ",{"type":48,"tag":61,"props":85,"children":87},{"className":86},[],[88],{"type":54,"value":89},"jetson-link-docs",{"type":54,"value":91},".",{"type":48,"tag":93,"props":94,"children":96},"h2",{"id":95},"when-to-invoke",[97],{"type":54,"value":98},"When to invoke",{"type":48,"tag":100,"props":101,"children":102},"ul",{},[103,122],{"type":48,"tag":104,"props":105,"children":106},"li",{},[107,113,115,121],{"type":48,"tag":61,"props":108,"children":110},{"className":109},[],[111],{"type":54,"value":112},"\u002Fjetson-quick-start",{"type":54,"value":114}," selected ",{"type":48,"tag":61,"props":116,"children":118},{"className":117},[],[119],{"type":54,"value":120},"Auto Setup",{"type":54,"value":91},{"type":48,"tag":104,"props":123,"children":124},{},[125],{"type":54,"value":126},"The user wants NVIDIA BSP artifacts downloaded into the current\nworkspace before running setup skills.",{"type":48,"tag":93,"props":128,"children":130},{"id":129},"inputs-and-outputs",[131],{"type":54,"value":132},"Inputs and outputs",{"type":48,"tag":57,"props":134,"children":135},{},[136,138,148],{"type":54,"value":137},"Resolve the active profile per\n",{"type":48,"tag":139,"props":140,"children":142},"a",{"href":141},"..\u002F..\u002Fcontext\u002Ftarget-platform-contract.md",[143],{"type":48,"tag":61,"props":144,"children":146},{"className":145},[],[147],{"type":54,"value":141},{"type":54,"value":149},".\nRefuse if no active profile exists.",{"type":48,"tag":57,"props":151,"children":152},{},[153,155,167,169,174,176,182,184,190],{"type":54,"value":154},"Follow the shared\n",{"type":48,"tag":139,"props":156,"children":158},{"href":157},"..\u002F..\u002Fcontext\u002Fbsp-customization-workflow.md#quick_start_prefill-contract",[159,165],{"type":48,"tag":61,"props":160,"children":162},{"className":161},[],[163],{"type":54,"value":164},"quick_start_prefill",{"type":54,"value":166}," contract",{"type":54,"value":168},".\nWhen invoked by ",{"type":48,"tag":61,"props":170,"children":172},{"className":171},[],[173],{"type":54,"value":112},{"type":54,"value":175},", this skill consumes\n",{"type":48,"tag":61,"props":177,"children":179},{"className":178},[],[180],{"type":54,"value":181},"quick_start_prefill.mode",{"type":54,"value":183}," and ",{"type":48,"tag":61,"props":185,"children":187},{"className":186},[],[188],{"type":54,"value":189},"quick_start_prefill.download.bsp_release",{"type":54,"value":191},"\nas the requested release when present. Missing or invalid prefilled values\nare not fatal, but a concrete release is required before any download\nstarts.",{"type":48,"tag":57,"props":193,"children":194},{},[195,197,203],{"type":54,"value":196},"Use the workspace root as the parent of ",{"type":48,"tag":61,"props":198,"children":200},{"className":199},[],[201],{"type":54,"value":202},"target-platform\u002F",{"type":54,"value":204},". 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The next\nsetup skills will register derived metadata after extraction or user\nconfirmation.",{"type":48,"tag":93,"props":371,"children":373},{"id":372},"procedure",[374],{"type":54,"value":375},"Procedure",{"type":48,"tag":377,"props":378,"children":380},"h3",{"id":379},"resolve-target-release",[381],{"type":54,"value":382},"Resolve target release",{"type":48,"tag":57,"props":384,"children":385},{},[386,388],{"type":54,"value":387},"Fetch the release list from:\n",{"type":48,"tag":139,"props":389,"children":393},{"href":390,"rel":391},"https:\u002F\u002Fdeveloper.nvidia.com\u002Fembedded\u002Fjetson-linux-archive",[392],"nofollow",[394],{"type":54,"value":390},{"type":48,"tag":57,"props":396,"children":397},{},[398,400,406,407,413,414,420,422,428,429,435,437,443,445,451,453,459],{"type":54,"value":399},"From the archive and linked release pages, list concrete releases that\nexplicitly support the active platform. 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Covers acquiring and launching the CI container, uv package management, and updating uv.lock.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1740,1743,1744],{"name":1741,"slug":1742,"type":15},"Containers","containers",{"name":20,"slug":21,"type":15},{"name":1745,"slug":1746,"type":15},"Python","python",17049,"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FMegatron-LM","2026-07-27T06:06:11.249662",{"slug":1751,"name":1751,"fn":1752,"description":1753,"org":1754,"tags":1755,"stars":1747,"repoUrl":1748,"updatedAt":1760},"mcore-bump-base-image","update NVIDIA PyTorch base images","Bump the NVIDIA PyTorch base image (`nvcr.io\u002Fnvidia\u002Fpytorch:YY.MM-py3`) used by Megatron-LM CI. Covers the two pin sites (GitHub CI in `docker\u002F.ngc_version.dev` and GitLab CI in `.gitlab\u002Fstages\u002F01.build.yml`), the post-bump CI loop (re-run functional tests, refresh golden values, mark broken tests), and the gotchas that bit PRs",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1756,1759],{"name":1757,"slug":1758,"type":15},"CI\u002FCD","ci-cd",{"name":20,"slug":21,"type":15},"2026-07-14T05:25:59.97109",{"slug":1762,"name":1762,"fn":1763,"description":1764,"org":1765,"tags":1766,"stars":1747,"repoUrl":1748,"updatedAt":1772},"mcore-cicd","manage CI\u002FCD pipelines for Megatron-LM","CI\u002FCD reference for Megatron-LM. Covers CI pipeline structure, PR scope labels, triggering internal GitLab CI (which force-pushes the current branch to a pull-request\u002FBRANCH ref — always dry-run and verify the destination first; never run against shared or protected branches), and CI failure investigation.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1767,1768,1769],{"name":1757,"slug":1758,"type":15},{"name":20,"slug":21,"type":15},{"name":1770,"slug":1771,"type":15},"GitHub","github","2026-07-27T06:06:12.278222",{"slug":1774,"name":1774,"fn":1775,"description":1776,"org":1777,"tags":1778,"stars":1747,"repoUrl":1748,"updatedAt":1786},"mcore-create-issue","investigate CI failures and create issues","Investigate a failing GitHub Actions run or job and create a GitHub issue for the failure.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1779,1782,1783],{"name":1780,"slug":1781,"type":15},"Debugging","debugging",{"name":1770,"slug":1771,"type":15},{"name":1784,"slug":1785,"type":15},"Triage","triage","2026-07-14T05:25:57.442089",{"slug":1788,"name":1788,"fn":1789,"description":1790,"org":1791,"tags":1792,"stars":1747,"repoUrl":1748,"updatedAt":1799},"mcore-linting-and-formatting","lint and format Megatron-LM code","Linting and formatting for Megatron-LM. Covers running autoformat.sh, tools (ruff, black, isort, pylint, mypy), and code style rules.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1793,1796],{"name":1794,"slug":1795,"type":15},"Best Practices","best-practices",{"name":1797,"slug":1798,"type":15},"Code Analysis","code-analysis","2026-07-14T05:25:56.18433",{"slug":1801,"name":1801,"fn":1802,"description":1803,"org":1804,"tags":1805,"stars":1747,"repoUrl":1748,"updatedAt":1813},"mcore-migrate-gpt-to-hybrid","migrate Megatron-LM models to HybridModel","Migration guide for moving Megatron Core GPTModel checkpoints, model providers, training commands, and layer mappings to HybridModel.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1806,1809,1812],{"name":1807,"slug":1808,"type":15},"Machine Learning","machine-learning",{"name":1810,"slug":1811,"type":15},"Migration","migration",{"name":9,"slug":8,"type":15},"2026-07-17T06:07:11.777011",{"slug":1815,"name":1815,"fn":1816,"description":1817,"org":1818,"tags":1819,"stars":1747,"repoUrl":1748,"updatedAt":1826},"mcore-onboard-gb200-1node-tests","onboard functional tests for GB200","Onboard 1-node GitHub MR functional tests for GB200 from existing mr-scoped 2-node tests.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1820,1823],{"name":1821,"slug":1822,"type":15},"QA","qa",{"name":1824,"slug":1825,"type":15},"Testing","testing","2026-07-14T05:25:53.673039",{"slug":1828,"name":1828,"fn":1829,"description":1830,"org":1831,"tags":1832,"stars":1747,"repoUrl":1748,"updatedAt":1837},"mcore-run-on-slurm","launch distributed training jobs on SLURM","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.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1833,1834],{"name":20,"slug":21,"type":15},{"name":1835,"slug":1836,"type":15},"Infrastructure","infrastructure","2026-07-14T05:25:49.362534",{"slug":1839,"name":1839,"fn":1840,"description":1841,"org":1842,"tags":1843,"stars":1747,"repoUrl":1748,"updatedAt":1851},"mcore-split-pr","split pull requests to reduce review load","Split a PR into multiple PRs to reduce the number of required CODEOWNERS reviewer groups.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1844,1847,1848],{"name":1845,"slug":1846,"type":15},"Code Review","code-review",{"name":1770,"slug":1771,"type":15},{"name":1849,"slug":1850,"type":15},"Pull Requests","pull-requests","2026-07-14T05:26:01.226578",{"slug":1853,"name":1853,"fn":1854,"description":1855,"org":1856,"tags":1857,"stars":1747,"repoUrl":1748,"updatedAt":1860},"mcore-testing","run and manage Megatron-LM tests","Test system for Megatron-LM. Covers test layout, recipe YAML structure, adding and running unit and functional tests, golden values, marker filters, and CI parity.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1858,1859],{"name":1821,"slug":1822,"type":15},{"name":1824,"slug":1825,"type":15},"2026-07-14T05:25:54.928983",{"slug":1862,"name":1862,"fn":1863,"description":1864,"org":1865,"tags":1866,"stars":1747,"repoUrl":1748,"updatedAt":1871},"nightly-sync","manage nightly main-to-dev sync workflows","Domain knowledge for the nightly main-to-dev sync workflow. Covers merge strategy, CI architecture, failure investigation, and known issues.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1867,1870],{"name":1868,"slug":1869,"type":15},"Automation","automation",{"name":1757,"slug":1758,"type":15},"2026-07-30T05:29:03.275638",496,{"items":1874,"total":1970},[1875,1892,1902,1916,1926,1941,1956],{"slug":1876,"name":1876,"fn":1877,"description":1878,"org":1879,"tags":1880,"stars":23,"repoUrl":24,"updatedAt":1891},"accelerated-computing-cudf","accelerate data processing with cuDF","Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV\u002FParquet I\u002FO, nullable semantics, and multi-GPU DataFrame workloads.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1881,1884,1887,1888],{"name":1882,"slug":1883,"type":15},"Data Analysis","data-analysis",{"name":1885,"slug":1886,"type":15},"Data Engineering","data-engineering",{"name":9,"slug":8,"type":15},{"name":1889,"slug":1890,"type":15},"Performance","performance","2026-07-14T05:28:43.176466",{"slug":1893,"name":1893,"fn":1894,"description":1895,"org":1896,"tags":1897,"stars":23,"repoUrl":24,"updatedAt":1901},"aiq-deploy","deploy and manage NVIDIA AI-Q infrastructure","Use when asked to install, deploy, run, validate, troubleshoot, or stop NVIDIA AI-Q Blueprint infrastructure.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1898,1899,1900],{"name":20,"slug":21,"type":15},{"name":1835,"slug":1836,"type":15},{"name":9,"slug":8,"type":15},"2026-07-14T05:29:06.667109",{"slug":1903,"name":1903,"fn":1904,"description":1905,"org":1906,"tags":1907,"stars":23,"repoUrl":24,"updatedAt":1915},"aiq-research","conduct deep research with AI-Q","Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1908,1911,1912],{"name":1909,"slug":1910,"type":15},"Agents","agents",{"name":9,"slug":8,"type":15},{"name":1913,"slug":1914,"type":15},"Research","research","2026-07-14T05:28:06.816956",{"slug":1917,"name":1917,"fn":1918,"description":1919,"org":1920,"tags":1921,"stars":23,"repoUrl":24,"updatedAt":1925},"amc-run-sample-calibration","run AMC sample dataset calibration","Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1922,1923,1924],{"name":1882,"slug":1883,"type":15},{"name":9,"slug":8,"type":15},{"name":1824,"slug":1825,"type":15},"2026-07-17T05:29:03.913266",{"slug":1927,"name":1927,"fn":1928,"description":1929,"org":1930,"tags":1931,"stars":23,"repoUrl":24,"updatedAt":1940},"amc-run-video-calibration","calibrate video datasets with AutoMagicCalib","Calibrate a new dataset from pre-recorded video files via the AutoMagicCalib REST API. Use when user has local MP4s and says 'calibrate my videos', 'run AMC on these videos', or similar. For RTSP\u002Flive streams, use amc-run-rtsp-calibration instead.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1932,1933,1936,1937],{"name":1868,"slug":1869,"type":15},{"name":1934,"slug":1935,"type":15},"Imaging","imaging",{"name":9,"slug":8,"type":15},{"name":1938,"slug":1939,"type":15},"Video","video","2026-07-17T05:28:53.905004",{"slug":1942,"name":1942,"fn":1943,"description":1944,"org":1945,"tags":1946,"stars":23,"repoUrl":24,"updatedAt":1955},"amc-setup-calibration-stack","deploy AutoMagicCalib microservice with Docker","Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1947,1948,1951,1952],{"name":20,"slug":21,"type":15},{"name":1949,"slug":1950,"type":15},"Docker","docker",{"name":9,"slug":8,"type":15},{"name":1953,"slug":1954,"type":15},"Operations","operations","2026-07-17T05:28:56.913999",{"slug":1957,"name":1957,"fn":1958,"description":1959,"org":1960,"tags":1961,"stars":23,"repoUrl":24,"updatedAt":1969},"cudaq-guide","develop quantum applications with CUDA-Q","CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1962,1963,1966],{"name":9,"slug":8,"type":15},{"name":1964,"slug":1965,"type":15},"Quantum Computing","quantum-computing",{"name":1967,"slug":1968,"type":15},"Simulation","simulation","2026-07-14T05:26:58.898253",305]