[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-nvidia-dgx-station":3,"mdc-nzmenl-key":31,"related-repo-nvidia-dgx-station":296,"related-org-nvidia-dgx-station":396},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":20,"repoUrl":21,"updatedAt":22,"license":23,"forks":24,"topics":25,"repo":26,"sourceUrl":29,"mdContent":30},"dgx-station","manage NVIDIA DGX Station development","Inspect and guide NVIDIA DGX Station GB300 development using the local dgx-assist CLI and pinned NVIDIA playbooks. Use for general Station platform questions, Software 1.0 or 2.0 compatibility, GB300 or RTX GPU selection, UUID ordering, mixed ATS\u002FHMM coherency, CDMM, general containers, CDI, CUDA visibility, or vsloshd power-sloshing behavior. Do not use for vLLM or SGLang container selection or tuning, serving a named model, changing MIG, or troubleshooting a reported failure when the dedicated Station skill applies.",{"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],{"name":13,"slug":14,"type":15},"Operations","operations","tag",{"name":17,"slug":18,"type":15},"CLI","cli",{"name":9,"slug":8,"type":15},1144,"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fdgx-spark-playbooks","2026-08-05T05:58:16.736667",null,249,[],{"repoUrl":21,"stars":20,"forks":24,"topics":27,"description":28},[],"Collection of step-by-step playbooks for setting up AI\u002FML workloads on NVIDIA DGX Spark devices with Blackwell architecture.","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fdgx-spark-playbooks\u002Ftree\u002FHEAD\u002Fnvidia\u002Fstation-ai-skills\u002Fassets\u002Fskills\u002Fdgx-station","---\nname: dgx-station\ndescription: Inspect and guide NVIDIA DGX Station GB300 development using the local dgx-assist CLI and pinned NVIDIA playbooks. Use for general Station platform questions, Software 1.0 or 2.0 compatibility, GB300 or RTX GPU selection, UUID ordering, mixed ATS\u002FHMM coherency, CDMM, general containers, CDI, CUDA visibility, or vsloshd power-sloshing behavior. Do not use for vLLM or SGLang container selection or tuning, serving a named model, changing MIG, or troubleshooting a reported failure when the dedicated Station skill applies.\n---\n\n# DGX Station\n\nGround every Station-specific answer in current host evidence and a retrieved NVIDIA passage.\n\n## Workflow\n\n1. Run `scripts\u002Fdgx-assist system inspect --json`.\n2. Read [references\u002Fsoftware-compatibility.md](references\u002Fsoftware-compatibility.md). Use `compatibility.profile_id`, `support_level`, and `capabilities`; do not branch on a version prefix.\n3. Form a narrow playbook query from the user's question and run `scripts\u002Fdgx-assist playbook search \"\u003Cquery>\" --json`.\n4. Apply the source-precedence rules in [references\u002Fsources.md](references\u002Fsources.md). Use only passages applicable to the detected profile. Cite their URL, heading, line span, source commit, and source-file digest.\n5. On the Software 1.0 capability-scoped profile, provide the supported inspection, diagnostics, compatibility guidance, and exact recipes qualified for that profile. Do not treat an absent Software 2.0-only service as a fault.\n6. Before any platform action, require its named capability to be `true`. If it is false, explain the profile restriction separately from relevant read-only guidance.\n7. If `version_specific_guidance` is false or retrieval abstains, say no applicable version-specific passage was found and avoid inventing a platform command.\n8. Answer from the combined profile and applicable passage. Label unknown evidence as unknown.\n\n## Safety requirements\n\n- Before any mutating action, display the exact command to be run and obtain explicit user approval immediately before executing it. Never batch approvals or carry one forward to a later action.\n- Never assume an `nvidia-smi` index is a CUDA ordinal.\n- Use GPU UUIDs for every proposed launch. When multiple GPUs are deliberately visible, place the GB300 UUID first.\n- Do not apply either legacy or Software 2.0 mixed-device behavior without checking the detected profile and observed ATS\u002FHMM state.\n- Do not tell the user to install or operate Fabric Manager as a normal Station requirement.\n- When `mixed_coherency_service` is true, inspect `mixed-coherency-gpu-select.service`, its generated environment, and container exposure separately.\n- When `dynamic_power_sloshing` is true, inspect `vsloshd`. Always inspect observed caps and never propose an ad hoc power-cap change.\n- Never install or change the driver, kernel, OS, firmware, or packages.\n- Never display credential values.\n\nRead [references\u002Fplatform.md](references\u002Fplatform.md) when interpreting coherency, container ordering, power, memory placement, or qualification evidence. Read [references\u002Fsoftware-compatibility.md](references\u002Fsoftware-compatibility.md) before applying version-specific guidance. Read [references\u002Fsources.md](references\u002Fsources.md) when guidance may come from the Development Guide or bring-up guide. Read [references\u002Fcli.md](references\u002Fcli.md) for command and JSON details.\n",{"data":32,"body":33},{"name":4,"description":6},{"type":34,"children":35},"root",[36,44,50,57,173,179,266],{"type":37,"tag":38,"props":39,"children":40},"element","h1",{"id":4},[41],{"type":42,"value":43},"text","DGX Station",{"type":37,"tag":45,"props":46,"children":47},"p",{},[48],{"type":42,"value":49},"Ground every Station-specific answer in current host evidence and a retrieved NVIDIA passage.",{"type":37,"tag":51,"props":52,"children":54},"h2",{"id":53},"workflow",[55],{"type":42,"value":56},"Workflow",{"type":37,"tag":58,"props":59,"children":60},"ol",{},[61,76,113,125,137,142,155,168],{"type":37,"tag":62,"props":63,"children":64},"li",{},[65,67,74],{"type":42,"value":66},"Run ",{"type":37,"tag":68,"props":69,"children":71},"code",{"className":70},[],[72],{"type":42,"value":73},"scripts\u002Fdgx-assist system inspect --json",{"type":42,"value":75},".",{"type":37,"tag":62,"props":77,"children":78},{},[79,81,87,89,95,97,103,105,111],{"type":42,"value":80},"Read ",{"type":37,"tag":82,"props":83,"children":85},"a",{"href":84},"references\u002Fsoftware-compatibility.md",[86],{"type":42,"value":84},{"type":42,"value":88},". Use ",{"type":37,"tag":68,"props":90,"children":92},{"className":91},[],[93],{"type":42,"value":94},"compatibility.profile_id",{"type":42,"value":96},", ",{"type":37,"tag":68,"props":98,"children":100},{"className":99},[],[101],{"type":42,"value":102},"support_level",{"type":42,"value":104},", and ",{"type":37,"tag":68,"props":106,"children":108},{"className":107},[],[109],{"type":42,"value":110},"capabilities",{"type":42,"value":112},"; do not branch on a version prefix.",{"type":37,"tag":62,"props":114,"children":115},{},[116,118,124],{"type":42,"value":117},"Form a narrow playbook query from the user's question and run ",{"type":37,"tag":68,"props":119,"children":121},{"className":120},[],[122],{"type":42,"value":123},"scripts\u002Fdgx-assist playbook search \"\u003Cquery>\" --json",{"type":42,"value":75},{"type":37,"tag":62,"props":126,"children":127},{},[128,130,135],{"type":42,"value":129},"Apply the source-precedence rules in ",{"type":37,"tag":82,"props":131,"children":133},{"href":132},"references\u002Fsources.md",[134],{"type":42,"value":132},{"type":42,"value":136},". Use only passages applicable to the detected profile. Cite their URL, heading, line span, source commit, and source-file digest.",{"type":37,"tag":62,"props":138,"children":139},{},[140],{"type":42,"value":141},"On the Software 1.0 capability-scoped profile, provide the supported inspection, diagnostics, compatibility guidance, and exact recipes qualified for that profile. Do not treat an absent Software 2.0-only service as a fault.",{"type":37,"tag":62,"props":143,"children":144},{},[145,147,153],{"type":42,"value":146},"Before any platform action, require its named capability to be ",{"type":37,"tag":68,"props":148,"children":150},{"className":149},[],[151],{"type":42,"value":152},"true",{"type":42,"value":154},". If it is false, explain the profile restriction separately from relevant read-only guidance.",{"type":37,"tag":62,"props":156,"children":157},{},[158,160,166],{"type":42,"value":159},"If ",{"type":37,"tag":68,"props":161,"children":163},{"className":162},[],[164],{"type":42,"value":165},"version_specific_guidance",{"type":42,"value":167}," is false or retrieval abstains, say no applicable version-specific passage was found and avoid inventing a platform command.",{"type":37,"tag":62,"props":169,"children":170},{},[171],{"type":42,"value":172},"Answer from the combined profile and applicable passage. Label unknown evidence as unknown.",{"type":37,"tag":51,"props":174,"children":176},{"id":175},"safety-requirements",[177],{"type":42,"value":178},"Safety requirements",{"type":37,"tag":180,"props":181,"children":182},"ul",{},[183,188,201,206,211,216,237,256,261],{"type":37,"tag":62,"props":184,"children":185},{},[186],{"type":42,"value":187},"Before any mutating action, display the exact command to be run and obtain explicit user approval immediately before executing it. Never batch approvals or carry one forward to a later action.",{"type":37,"tag":62,"props":189,"children":190},{},[191,193,199],{"type":42,"value":192},"Never assume an ",{"type":37,"tag":68,"props":194,"children":196},{"className":195},[],[197],{"type":42,"value":198},"nvidia-smi",{"type":42,"value":200}," index is a CUDA ordinal.",{"type":37,"tag":62,"props":202,"children":203},{},[204],{"type":42,"value":205},"Use GPU UUIDs for every proposed launch. When multiple GPUs are deliberately visible, place the GB300 UUID first.",{"type":37,"tag":62,"props":207,"children":208},{},[209],{"type":42,"value":210},"Do not apply either legacy or Software 2.0 mixed-device behavior without checking the detected profile and observed ATS\u002FHMM state.",{"type":37,"tag":62,"props":212,"children":213},{},[214],{"type":42,"value":215},"Do not tell the user to install or operate Fabric Manager as a normal Station requirement.",{"type":37,"tag":62,"props":217,"children":218},{},[219,221,227,229,235],{"type":42,"value":220},"When ",{"type":37,"tag":68,"props":222,"children":224},{"className":223},[],[225],{"type":42,"value":226},"mixed_coherency_service",{"type":42,"value":228}," is true, inspect ",{"type":37,"tag":68,"props":230,"children":232},{"className":231},[],[233],{"type":42,"value":234},"mixed-coherency-gpu-select.service",{"type":42,"value":236},", its generated environment, and container exposure separately.",{"type":37,"tag":62,"props":238,"children":239},{},[240,241,247,248,254],{"type":42,"value":220},{"type":37,"tag":68,"props":242,"children":244},{"className":243},[],[245],{"type":42,"value":246},"dynamic_power_sloshing",{"type":42,"value":228},{"type":37,"tag":68,"props":249,"children":251},{"className":250},[],[252],{"type":42,"value":253},"vsloshd",{"type":42,"value":255},". Always inspect observed caps and never propose an ad hoc power-cap change.",{"type":37,"tag":62,"props":257,"children":258},{},[259],{"type":42,"value":260},"Never install or change the driver, kernel, OS, firmware, or packages.",{"type":37,"tag":62,"props":262,"children":263},{},[264],{"type":42,"value":265},"Never display credential values.",{"type":37,"tag":45,"props":267,"children":268},{},[269,270,275,277,281,283,287,289,294],{"type":42,"value":80},{"type":37,"tag":82,"props":271,"children":273},{"href":272},"references\u002Fplatform.md",[274],{"type":42,"value":272},{"type":42,"value":276}," when interpreting coherency, container ordering, power, memory placement, or qualification evidence. Read ",{"type":37,"tag":82,"props":278,"children":279},{"href":84},[280],{"type":42,"value":84},{"type":42,"value":282}," before applying version-specific guidance. Read ",{"type":37,"tag":82,"props":284,"children":285},{"href":132},[286],{"type":42,"value":132},{"type":42,"value":288}," when guidance may come from the Development Guide or bring-up guide. Read ",{"type":37,"tag":82,"props":290,"children":292},{"href":291},"references\u002Fcli.md",[293],{"type":42,"value":291},{"type":42,"value":295}," for command and JSON details.",{"items":297,"total":395},[298,318,331,346,361,372,389],{"slug":299,"name":299,"fn":300,"description":301,"org":302,"tags":303,"stars":20,"repoUrl":21,"updatedAt":317},"analysis-methods","write Python analysis code for FHIR data","Teaches the analyst agent how to write correct, robust Python analysis code for FHIR clinical data using pandas, matplotlib, and scipy.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[304,307,310,313,314],{"name":305,"slug":306,"type":15},"Data Analysis","data-analysis",{"name":308,"slug":309,"type":15},"FHIR","fhir",{"name":311,"slug":312,"type":15},"Healthcare","healthcare",{"name":9,"slug":8,"type":15},{"name":315,"slug":316,"type":15},"Python","python","2026-07-14T05:35:59.037962",{"slug":319,"name":319,"fn":320,"description":321,"org":322,"tags":323,"stars":20,"repoUrl":21,"updatedAt":330},"case-summary","summarize clinical patient cases from FHIR","Prepare a complete clinical case summary for a patient from FHIR endpoints. Use when asked to summarize a patient, compile a case, or prepare for tumor board.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[324,325,326,327],{"name":308,"slug":309,"type":15},{"name":311,"slug":312,"type":15},{"name":9,"slug":8,"type":15},{"name":328,"slug":329,"type":15},"Summarization","summarization","2026-07-14T05:35:52.790528",{"slug":332,"name":332,"fn":333,"description":334,"org":335,"tags":336,"stars":20,"repoUrl":21,"updatedAt":345},"clinical-delegation","delegate clinical tasks to specialist agents","How to delegate clinical tasks to specialist agents. Always use sub-agent runtime with explicit agentId — never ACP. Never call FHIR via web_fetch.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[337,340,341,344],{"name":338,"slug":339,"type":15},"Agents","agents",{"name":311,"slug":312,"type":15},{"name":342,"slug":343,"type":15},"Multi-Agent","multi-agent",{"name":9,"slug":8,"type":15},"2026-07-14T05:35:55.294972",{"slug":347,"name":347,"fn":348,"description":349,"org":350,"tags":351,"stars":20,"repoUrl":21,"updatedAt":360},"clinical-knowledge","provide clinical reference and regulatory context","Teaches agents clinical reference ranges, condition codes, quality measure definitions, drug classifications, and regulatory context so they can flag abnormal values and identify care gaps.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[352,355,356,357],{"name":353,"slug":354,"type":15},"Clinical Trials","clinical-trials",{"name":311,"slug":312,"type":15},{"name":9,"slug":8,"type":15},{"name":358,"slug":359,"type":15},"Regulatory Compliance","regulatory-compliance","2026-07-14T05:35:56.550833",{"slug":362,"name":362,"fn":363,"description":364,"org":365,"tags":366,"stars":20,"repoUrl":21,"updatedAt":371},"cohort-compare","analyze patient cohorts from FHIR endpoints","Analyze a cohort of patients from FHIR endpoints to find care gaps and patterns. Use when asked to compare patients, find quality gaps, or analyze a population.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[367,368,369,370],{"name":305,"slug":306,"type":15},{"name":308,"slug":309,"type":15},{"name":311,"slug":312,"type":15},{"name":9,"slug":8,"type":15},"2026-07-14T05:35:51.543095",{"slug":373,"name":373,"fn":374,"description":375,"org":376,"tags":377,"stars":20,"repoUrl":21,"updatedAt":388},"dgx-diagnose","diagnose NVIDIA DGX Station hardware issues","Diagnose common DGX Station GB300 issues — CUDA crashes, wrong-GPU targeting, vLLM\u002FSGLang container bugs, MIG state problems, NVLink\u002FFabric Manager errors, X\u002FVulkan failures, HuggingFace auth, and port conflicts. Use when the user reports a GPU error, inference server crash, MIG problem, or any unexplained DGX Station failure.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[378,381,384,385],{"name":379,"slug":380,"type":15},"AI Infrastructure","ai-infrastructure",{"name":382,"slug":383,"type":15},"Debugging","debugging",{"name":9,"slug":8,"type":15},{"name":386,"slug":387,"type":15},"Observability","observability","2026-07-14T05:31:04.085598",{"slug":4,"name":4,"fn":5,"description":6,"org":390,"tags":391,"stars":20,"repoUrl":21,"updatedAt":22},{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[392,393,394],{"name":17,"slug":18,"type":15},{"name":9,"slug":8,"type":15},{"name":13,"slug":14,"type":15},15,{"items":397,"total":552},[398,416,432,443,455,467,480,494,507,518,532,541],{"slug":399,"name":399,"fn":400,"description":401,"org":402,"tags":403,"stars":413,"repoUrl":414,"updatedAt":415},"nemoclaw-user-guide","retrieve NemoClaw documentation and configuration","Guides human users' AI agents to the NemoClaw docs MCP server and canonical Fern documentation in Markdown form. Use when users ask how to install, configure, operate, troubleshoot, secure, or learn NemoClaw with an AI coding assistant. Trigger keywords - nemoclaw docs, use nemoclaw with ai agent, nemoclaw mcp docs, nemoclaw install help, nemoclaw quickstart, nemoclaw markdown docs, llms.txt, agent skills.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[404,407,410],{"name":405,"slug":406,"type":15},"Documentation","documentation",{"name":408,"slug":409,"type":15},"MCP","mcp",{"name":411,"slug":412,"type":15},"Search","search",21777,"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FNemoClaw","2026-07-20T06:00:01.461044",{"slug":417,"name":417,"fn":418,"description":419,"org":420,"tags":421,"stars":429,"repoUrl":430,"updatedAt":431},"mcore-build-and-dependency","manage Megatron-LM development environments","Container-based dev environment setup and dependency management for Megatron-LM. Covers acquiring and launching the CI container, uv package management, and updating uv.lock.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[422,425,428],{"name":423,"slug":424,"type":15},"Containers","containers",{"name":426,"slug":427,"type":15},"Deployment","deployment",{"name":315,"slug":316,"type":15},17049,"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FMegatron-LM","2026-07-27T06:06:11.249662",{"slug":433,"name":433,"fn":434,"description":435,"org":436,"tags":437,"stars":429,"repoUrl":430,"updatedAt":442},"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},[438,441],{"name":439,"slug":440,"type":15},"CI\u002FCD","ci-cd",{"name":426,"slug":427,"type":15},"2026-07-14T05:25:59.97109",{"slug":444,"name":444,"fn":445,"description":446,"org":447,"tags":448,"stars":429,"repoUrl":430,"updatedAt":454},"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},[449,450,451],{"name":439,"slug":440,"type":15},{"name":426,"slug":427,"type":15},{"name":452,"slug":453,"type":15},"GitHub","github","2026-07-27T06:06:12.278222",{"slug":456,"name":456,"fn":457,"description":458,"org":459,"tags":460,"stars":429,"repoUrl":430,"updatedAt":466},"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},[461,462,463],{"name":382,"slug":383,"type":15},{"name":452,"slug":453,"type":15},{"name":464,"slug":465,"type":15},"Triage","triage","2026-07-14T05:25:57.442089",{"slug":468,"name":468,"fn":469,"description":470,"org":471,"tags":472,"stars":429,"repoUrl":430,"updatedAt":479},"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},[473,476],{"name":474,"slug":475,"type":15},"Best Practices","best-practices",{"name":477,"slug":478,"type":15},"Code Analysis","code-analysis","2026-07-14T05:25:56.18433",{"slug":481,"name":481,"fn":482,"description":483,"org":484,"tags":485,"stars":429,"repoUrl":430,"updatedAt":493},"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},[486,489,492],{"name":487,"slug":488,"type":15},"Machine Learning","machine-learning",{"name":490,"slug":491,"type":15},"Migration","migration",{"name":9,"slug":8,"type":15},"2026-07-17T06:07:11.777011",{"slug":495,"name":495,"fn":496,"description":497,"org":498,"tags":499,"stars":429,"repoUrl":430,"updatedAt":506},"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},[500,503],{"name":501,"slug":502,"type":15},"QA","qa",{"name":504,"slug":505,"type":15},"Testing","testing","2026-07-14T05:25:53.673039",{"slug":508,"name":508,"fn":509,"description":510,"org":511,"tags":512,"stars":429,"repoUrl":430,"updatedAt":517},"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},[513,514],{"name":426,"slug":427,"type":15},{"name":515,"slug":516,"type":15},"Infrastructure","infrastructure","2026-07-14T05:25:49.362534",{"slug":519,"name":519,"fn":520,"description":521,"org":522,"tags":523,"stars":429,"repoUrl":430,"updatedAt":531},"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},[524,527,528],{"name":525,"slug":526,"type":15},"Code Review","code-review",{"name":452,"slug":453,"type":15},{"name":529,"slug":530,"type":15},"Pull Requests","pull-requests","2026-07-14T05:26:01.226578",{"slug":533,"name":533,"fn":534,"description":535,"org":536,"tags":537,"stars":429,"repoUrl":430,"updatedAt":540},"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},[538,539],{"name":501,"slug":502,"type":15},{"name":504,"slug":505,"type":15},"2026-07-14T05:25:54.928983",{"slug":542,"name":542,"fn":543,"description":544,"org":545,"tags":546,"stars":429,"repoUrl":430,"updatedAt":551},"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},[547,550],{"name":548,"slug":549,"type":15},"Automation","automation",{"name":439,"slug":440,"type":15},"2026-07-30T05:29:03.275638",525]