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Add tasks before starting multi-step work.\n2. Mark exactly one task in progress while working.\n3. Update task status as each step completes.\n4. Keep task text concise and action-oriented.\n\n## How to use\n\nUse the `tasks` tool directly. Do NOT use run_code, execute, or write_file for task management.\n\n### 1. Add tasks at the start\n```\ntasks(operation=\"add_multiple\", content=\"Step one; Step two; Step three\")\n```\nThis clears any previous tasks. Each request starts fresh.\n\n## Examples\n\n```python\ntasks(operation=\"add_multiple\", content=\"Inspect repo; Run tests; Summarize findings\")\ntasks(operation=\"start\", task_id=\"task_1\")\ntasks(operation=\"complete\", task_id=\"task_1\")\n```\n\n### 2. Start a task before working on it\n```\ntasks(operation=\"start\", task_id=\"task_1\")\n```\n\n### 3. Complete a task when done\n```\ntasks(operation=\"complete\", task_id=\"task_1\")\n```\n\n### 4. Check what's next\n```\ntasks(operation=\"next\")\n```\n\n## All operations\n\n| Operation | Args | Description |\n|-----------|------|-------------|\n| `add_multiple` | `content=\"t1; t2; t3\"` | Add tasks (clears previous) |\n| `start` | `task_id=\"task_1\"` | Mark in_progress |\n| `complete` | `task_id=\"task_1\"` | Mark completed |\n| `cancel` | `task_id=\"task_1\"` | Cancel a task |\n| `list` | (none) | Show all tasks |\n| `next` | (none) | Get next pending task |\n\n## Rules\n\n- One task in_progress at a time\n- Start before working, complete when done\n- Do not leave tasks hanging\n",{"data":47,"body":50},{"name":4,"description":6,"metadata":48},{"author":49},"SkillEvaluator Maintainers \u003Cmaintainers@example.com>",{"type":51,"children":52},"root",[53,62,68,75,90,96,120,126,140,147,159,164,170,208,214,222,228,236,242,251,257,435,441,459],{"type":54,"tag":55,"props":56,"children":58},"element","h1",{"id":57},"task-list-skill",[59],{"type":60,"value":61},"text","Task List Skill",{"type":54,"tag":63,"props":64,"children":65},"p",{},[66],{"type":60,"value":67},"Track multi-step tasks to ensure nothing is forgotten.",{"type":54,"tag":69,"props":70,"children":72},"h2",{"id":71},"when-to-use",[73],{"type":60,"value":74},"When to use",{"type":54,"tag":76,"props":77,"children":78},"ul",{},[79,85],{"type":54,"tag":80,"props":81,"children":82},"li",{},[83],{"type":60,"value":84},"The request requires 4 or more distinct steps",{"type":54,"tag":80,"props":86,"children":87},{},[88],{"type":60,"value":89},"You need to perform several operations in sequence",{"type":54,"tag":69,"props":91,"children":93},{"id":92},"instructions",[94],{"type":60,"value":95},"Instructions",{"type":54,"tag":97,"props":98,"children":99},"ol",{},[100,105,110,115],{"type":54,"tag":80,"props":101,"children":102},{},[103],{"type":60,"value":104},"Add tasks before starting multi-step work.",{"type":54,"tag":80,"props":106,"children":107},{},[108],{"type":60,"value":109},"Mark exactly one task in progress while working.",{"type":54,"tag":80,"props":111,"children":112},{},[113],{"type":60,"value":114},"Update task status as each step completes.",{"type":54,"tag":80,"props":116,"children":117},{},[118],{"type":60,"value":119},"Keep task text concise and action-oriented.",{"type":54,"tag":69,"props":121,"children":123},{"id":122},"how-to-use",[124],{"type":60,"value":125},"How to use",{"type":54,"tag":63,"props":127,"children":128},{},[129,131,138],{"type":60,"value":130},"Use the ",{"type":54,"tag":132,"props":133,"children":135},"code",{"className":134},[],[136],{"type":60,"value":137},"tasks",{"type":60,"value":139}," tool directly. 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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},[473,476,479],{"name":474,"slug":475,"type":15},"Documentation","documentation",{"name":477,"slug":478,"type":15},"MCP","mcp",{"name":480,"slug":481,"type":15},"Search","search",21777,"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FNemoClaw","2026-08-25T03:29:57.273192",{"slug":486,"name":486,"fn":487,"description":488,"org":489,"tags":490,"stars":499,"repoUrl":500,"updatedAt":501},"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},[491,494,497],{"name":492,"slug":493,"type":15},"Containers","containers",{"name":495,"slug":496,"type":15},"Deployment","deployment",{"name":498,"slug":174,"type":15},"Python",17049,"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FMegatron-LM","2026-07-27T06:06:11.249662",{"slug":503,"name":503,"fn":504,"description":505,"org":506,"tags":507,"stars":499,"repoUrl":500,"updatedAt":512},"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},[508,511],{"name":509,"slug":510,"type":15},"CI\u002FCD","ci-cd",{"name":495,"slug":496,"type":15},"2026-07-14T05:25:59.97109",{"slug":514,"name":514,"fn":515,"description":516,"org":517,"tags":518,"stars":499,"repoUrl":500,"updatedAt":524},"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},[519,520,521],{"name":509,"slug":510,"type":15},{"name":495,"slug":496,"type":15},{"name":522,"slug":523,"type":15},"GitHub","github","2026-08-28T14:38:16.959248",{"slug":526,"name":526,"fn":527,"description":528,"org":529,"tags":530,"stars":499,"repoUrl":500,"updatedAt":538},"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},[531,534,535],{"name":532,"slug":533,"type":15},"Debugging","debugging",{"name":522,"slug":523,"type":15},{"name":536,"slug":537,"type":15},"Triage","triage","2026-07-14T05:25:57.442089",{"slug":540,"name":540,"fn":541,"description":542,"org":543,"tags":544,"stars":499,"repoUrl":500,"updatedAt":551},"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},[545,548],{"name":546,"slug":547,"type":15},"Best Practices","best-practices",{"name":549,"slug":550,"type":15},"Code Analysis","code-analysis","2026-07-14T05:25:56.18433",{"slug":553,"name":553,"fn":554,"description":555,"org":556,"tags":557,"stars":499,"repoUrl":500,"updatedAt":565},"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, including the mechanical steps for transferring an existing pretrain_gpt.py launch script.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[558,561,564],{"name":559,"slug":560,"type":15},"Machine Learning","machine-learning",{"name":562,"slug":563,"type":15},"Migration","migration",{"name":9,"slug":8,"type":15},"2026-08-21T03:36:57.470256",{"slug":567,"name":567,"fn":568,"description":569,"org":570,"tags":571,"stars":499,"repoUrl":500,"updatedAt":578},"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},[572,575],{"name":573,"slug":574,"type":15},"QA","qa",{"name":576,"slug":577,"type":15},"Testing","testing","2026-07-14T05:25:53.673039",{"slug":580,"name":580,"fn":581,"description":582,"org":583,"tags":584,"stars":499,"repoUrl":500,"updatedAt":589},"mcore-run-on-slurm","launch distributed training jobs on SLURM","How to launch distributed Megatron-LM training jobs on a SLURM cluster. 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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},[610,611],{"name":573,"slug":574,"type":15},{"name":576,"slug":577,"type":15},"2026-07-14T05:25:54.928983",{"slug":614,"name":614,"fn":615,"description":616,"org":617,"tags":618,"stars":499,"repoUrl":500,"updatedAt":623},"nightly-sync","manage nightly main-to-dev sync workflows","Domain knowledge for the nightly main-to-dev sync workflow. 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Works on any plain text input provided inline or from a file path.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[678,681,682],{"name":679,"slug":680,"type":15},"Data Analysis","data-analysis",{"name":9,"slug":8,"type":15},{"name":683,"slug":684,"type":15},"Statistics","statistics","2026-08-31T09:18:44.240822",5]