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Validators should report failures against the exact requirement code documented in the capability.\n\nIf the rule already exists but is wrong or incomplete, use `simready-foundation-update-validator`.\n\n## Prerequisites\nBefore editing, read:\n\n- `AGENTS.md`\n- `nv_core\u002Fsr_specs\u002Fdocs\u002Fguides\u002Ffeatures\u002Ffeatures.md`\n- `nv_core\u002Fsr_specs\u002Fdocs\u002Fguides\u002Ffeatures_expansion_workflow.md`\n- `nv_core\u002Fsr_specs\u002Fdocs\u002Fguides\u002Fnaming_conventions.md`\n- target requirement markdown\n- target capability `validation.py`\n- nearby checker classes in the same capability\n- feature manifests that include the requirement\n\n## Inputs\n\nCollect or infer:\n\n| Input | Requirement |\n|---|---|\n| `requirement_codes` | Requirement IDs this validator enforces. |\n| `validation_module` | Target capability `validation.py`. |\n| `rule_name` | Clear checker class\u002Ffunction name. |\n| `asset_scope` | Stage, prim, property, relationship, material, physics, or runtime evidence. |\n| `failure_message` | Actionable message that names the failed condition. |\n| `test_assets` | Existing or minimal pass\u002Ffail assets, if available. |\n\n## Instructions\n\nUse this checklist when changing the repository:\n\n1. Confirm requirement docs exist and the intended check is objective.\n2. Inspect existing validators in the capability and reuse local helper patterns.\n3. Add a checker class or function in `validation.py` with the correct registration decorators\u002Fimports used by the capability.\n4. Register every requirement ID the checker enforces and pass the matching requirement when reporting each failure.\n5. Keep failure messages specific, deterministic, and actionable.\n6. Handle missing default prims, invalid paths, unloaded\u002Fabstract prims, variants, and composed stages consistently with neighboring validators.\n7. Add focused pass\u002Ffail tests or sample validation instructions where the repo has a test pattern.\n8. Update requirement docs only if implementation clarifies edge cases.\n9. Validate consistency:\n   - validator imports successfully where possible\n   - requirement IDs match documented codes\n   - failure messages match docs\n   - feature manifests include only registered requirements when executable validation is expected\n\n## Examples\n\nExample request:\n\n```text\nAdd a validator for a SimReady factory connection point requirement.\n```\n\nExpected result summary:\n\n```text\nchanged_files: new docs, manifests, indexes, or validation scaffolding\nvalidation: focused static checks and any relevant docs\u002Fbuild checks\nremaining_gaps: requirement, validator, adapter, profile, or runtime-test follow-up\n```\n\n## Policies\n\n- Do not validate subjective guidance as a hard failure unless the requirement defines objective criteria.\n- Prefer one clear checker per rule family over tangled mega-checkers.\n- Avoid changing unrelated validators while adding a new one.\n- Use warnings only when the validation framework supports them and the requirement is advisory.\n- If local Omniverse\u002FOAV packages are unavailable, document the narrowed validation you could run.\n\n## Limitations\n\n- Do not mutate published feature or profile versions in place.\n- Do not invent requirement IDs or validator behavior when the contract is ambiguous; record the question.\n- Do not skip index, manifest, validation, or downstream follow-up notes.\n\n## Troubleshooting\n\n- Error: the new concept overlaps an existing artifact. 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examples, indexes, and validator follow-up.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[735,736,737,738],{"name":692,"slug":693,"type":15},{"name":9,"slug":8,"type":15},{"name":18,"slug":19,"type":15},{"name":13,"slug":14,"type":15},"2026-07-14T05:34:11.881936",{"slug":741,"name":741,"fn":742,"description":743,"org":744,"tags":745,"stars":23,"repoUrl":24,"updatedAt":752},"simready-foundation-add-runtime-test","add SimReady runtime tests","Use for adding SimReady runtime tests, runner expectations, batch\u002Fjob\u002Freport notes, and validation evidence.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[746,747,748,751],{"name":9,"slug":8,"type":15},{"name":18,"slug":19,"type":15},{"name":749,"slug":750,"type":15},"Testing","testing",{"name":13,"slug":14,"type":15},"2026-07-14T05:34:09.295859",{"slug":4,"name":4,"fn":5,"description":6,"org":754,"tags":755,"stars":23,"repoUrl":24,"updatedAt":25},{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[756,757,758,759],{"name":21,"slug":22,"type":15},{"name":9,"slug":8,"type":15},{"name":18,"slug":19,"type":15},{"name":13,"slug":14,"type":15},26,{"items":762,"total":917},[763,779,797,808,820,834,847,861,872,883,897,906],{"slug":764,"name":764,"fn":765,"description":766,"org":767,"tags":768,"stars":776,"repoUrl":777,"updatedAt":778},"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},[769,770,773],{"name":692,"slug":693,"type":15},{"name":771,"slug":772,"type":15},"MCP","mcp",{"name":774,"slug":775,"type":15},"Search","search",21777,"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FNemoClaw","2026-07-20T06:00:01.461044",{"slug":780,"name":780,"fn":781,"description":782,"org":783,"tags":784,"stars":794,"repoUrl":795,"updatedAt":796},"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},[785,788,791],{"name":786,"slug":787,"type":15},"Containers","containers",{"name":789,"slug":790,"type":15},"Deployment","deployment",{"name":792,"slug":793,"type":15},"Python","python",17049,"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FMegatron-LM","2026-07-27T06:06:11.249662",{"slug":798,"name":798,"fn":799,"description":800,"org":801,"tags":802,"stars":794,"repoUrl":795,"updatedAt":807},"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},[803,806],{"name":804,"slug":805,"type":15},"CI\u002FCD","ci-cd",{"name":789,"slug":790,"type":15},"2026-07-14T05:25:59.97109",{"slug":809,"name":809,"fn":810,"description":811,"org":812,"tags":813,"stars":794,"repoUrl":795,"updatedAt":819},"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},[814,815,816],{"name":804,"slug":805,"type":15},{"name":789,"slug":790,"type":15},{"name":817,"slug":818,"type":15},"GitHub","github","2026-07-27T06:06:12.278222",{"slug":821,"name":821,"fn":822,"description":823,"org":824,"tags":825,"stars":794,"repoUrl":795,"updatedAt":833},"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},[826,829,830],{"name":827,"slug":828,"type":15},"Debugging","debugging",{"name":817,"slug":818,"type":15},{"name":831,"slug":832,"type":15},"Triage","triage","2026-07-14T05:25:57.442089",{"slug":835,"name":835,"fn":836,"description":837,"org":838,"tags":839,"stars":794,"repoUrl":795,"updatedAt":846},"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},[840,843],{"name":841,"slug":842,"type":15},"Best Practices","best-practices",{"name":844,"slug":845,"type":15},"Code Analysis","code-analysis","2026-07-14T05:25:56.18433",{"slug":848,"name":848,"fn":849,"description":850,"org":851,"tags":852,"stars":794,"repoUrl":795,"updatedAt":860},"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},[853,856,859],{"name":854,"slug":855,"type":15},"Machine Learning","machine-learning",{"name":857,"slug":858,"type":15},"Migration","migration",{"name":9,"slug":8,"type":15},"2026-07-17T06:07:11.777011",{"slug":862,"name":862,"fn":863,"description":864,"org":865,"tags":866,"stars":794,"repoUrl":795,"updatedAt":871},"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},[867,870],{"name":868,"slug":869,"type":15},"QA","qa",{"name":749,"slug":750,"type":15},"2026-07-14T05:25:53.673039",{"slug":873,"name":873,"fn":874,"description":875,"org":876,"tags":877,"stars":794,"repoUrl":795,"updatedAt":882},"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},[878,879],{"name":789,"slug":790,"type":15},{"name":880,"slug":881,"type":15},"Infrastructure","infrastructure","2026-07-14T05:25:49.362534",{"slug":884,"name":884,"fn":885,"description":886,"org":887,"tags":888,"stars":794,"repoUrl":795,"updatedAt":896},"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},[889,892,893],{"name":890,"slug":891,"type":15},"Code Review","code-review",{"name":817,"slug":818,"type":15},{"name":894,"slug":895,"type":15},"Pull Requests","pull-requests","2026-07-14T05:26:01.226578",{"slug":898,"name":898,"fn":899,"description":900,"org":901,"tags":902,"stars":794,"repoUrl":795,"updatedAt":905},"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},[903,904],{"name":868,"slug":869,"type":15},{"name":749,"slug":750,"type":15},"2026-07-14T05:25:54.928983",{"slug":907,"name":907,"fn":908,"description":909,"org":910,"tags":911,"stars":794,"repoUrl":795,"updatedAt":916},"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},[912,915],{"name":913,"slug":914,"type":15},"Automation","automation",{"name":804,"slug":805,"type":15},"2026-07-30T05:29:03.275638",496]