[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71Q2H9112GCDJTX6GSQPDKV":3,"skill-same:01M71Q2H9112GCDJTX6GSQPDKV":93},{"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":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":52,"commitSha":53,"skillDirectory":54,"forksCount":14,"repositoryHtmlUrl":55,"repositoryHomepageUrl":56,"ownerHtmlUrl":57,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":58,"install":59,"resources":72},"01M71Q2H9112GCDJTX6GSQPDKV","tao-validate-dataset-format",null,"Run `tao-daft validate` to check NVIDIA TAO DAFT datasets for structure, schema, and cross-reference errors. Do not use for non-DAFT formats. Use when the user asks to validate a DAFT dataset, check DAFT schema, validate a TAO dataset format, or run `tao-daft validate`.","pattanation\u002FNorvik","pattanation","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F235419268?v=4","01M71M5THHYYB15ME8R2E4FCZG","Patta","01M71M5TJM1NDM992M8PDKYR2K",0,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Ftao-validate-dataset-format\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"validate","tao validate dataset format","format","tao","dataset","cross-reference","python","when","nvidia-tao","for","pip","errors","structure","do","schema","use","check","Bash","NVIDIA","package","2026-11-10 13:02:02",false,"---\nname: tao-validate-dataset-format\ndescription: Run `tao-daft validate` to check NVIDIA TAO DAFT datasets for structure, schema, and cross-reference errors. Do\n  not use for non-DAFT formats. Use when the user asks to validate a DAFT dataset, check DAFT schema, validate a TAO dataset\n  format, or run `tao-daft validate`.\nlicense: Apache-2.0\ncompatibility: Requires Python 3.10+ and the nvidia-tao-sdk package (pip install nvidia-tao-daft).\nmetadata:\n  author: NVIDIA Corporation\n  version: \"0.1.0\"\nallowed-tools: Read Bash\ntags:\n- tao-daft\n- dataset\n- validation\n- schema\n---\n\n# Validate a TAO DAFT Dataset\n\n## Quick start\n\n```bash\ntao-daft validate \u003Cformat> --path \u003Cdataset-or-parent-dir>\n```\n\n`\u003Cformat>` is a positional subcommand (e.g. `metropolis-v3.0`, `cosmos-reason-v1.0`);\n`--path` is required. Discover supported formats and per-format flags via\n`tao-daft validate --help` and the leaf `--help` (see \"CLI conventions\" below).\n\n## Preflight\n```bash\npython -c \"import nvidia_tao_daft\" 2>\u002Fdev\u002Fnull || {\n  echo \"MISSING: tao-daft not installed. Run:\"\n  echo \"  pip install nvidia-tao-daft\"\n  exit 1\n}\n```\n\n## Quick Start\n\nDiscover the installed validator formats before choosing a format slug, then\nrun validation with the target passed through `--path`:\n\n```bash\ntao-daft --version\ntao-daft validate --help\ntao-daft validate \u003Cformat> --help\ntao-daft validate \u003Cformat> --path \u002Fpath\u002Fto\u002Fdaft-dataset\n```\n\n## Purpose\n\nDrive `tao-daft validate` against a DAFT dataset (or a tree of them).\nThe CLI is the spec; the skill picks subcommand + flags and explains\nthe result.\n\nTrigger when the user mentions \"TAO DAFT\", \"DAFT format\", validating a\nDAFT dataset, schema\u002Fcross-reference errors, or `tao-daft validate`.\nDo **not** trigger for non-DAFT layouts (COCO, YOLO, Data Factory JSONL),\nor for `tao-daft info` \u002F `tao-daft convert` — those have their own skills.\n\nIf the user's opening is ambiguous, run a few `--help` commands first\nto ground yourself, then come back and confirm the task.\n\n## Prerequisites\n\n- `nvidia-tao-daft` installed (`pip install nvidia-tao-daft`; the wheel\n  is enough, no source repo). Confirm with `tao-daft --version`.\n- A DAFT dataset, or a parent directory of them, on local disk.\n\n## Instructions\n\n### CLI conventions\n\n`tao-daft` is nested argparse subcommands. Names and flags drift across\nversions, so **discover the current surface from `--help`** rather than\ntrusting any list in this doc.\n\n1. **Format is a positional subcommand**, not `--format`:\n   `tao-daft validate \u003Cformat> [flags]`. List current formats via\n   `tao-daft validate --help`; slugs look like `metropolis-v3.0`,\n   `cosmos-reason-v1.0`.\n2. **Target is `--path PATH`**, not positional. It accepts a single\n   dataset\u002Fscene or a parent directory — the validator walks the tree.\n3. **Flags are per-format**; run the leaf help, e.g.\n   `tao-daft validate metropolis-v3.0 --help`, before choosing them.\n   Don't assume a flag from one format exists on another.\n\nSo the loop is: `tao-daft --version` → `tao-daft validate --help` →\npick format (infer if unspecified, see below) →\n`tao-daft validate \u003Cformat> --help` → run → interpret.\n\n### Format inference\n\nUse directory markers, not filenames:\n\n- `meta.json` next to `media\u002F` and `text\u002F` ⇒ `cosmos-reason-v1.0`.\n- A directory (or nested directories) containing `contextual\u002F`,\n  typically alongside `raw\u002F` and `task\u002F` ⇒ `metropolis-v3.0`.\n- Neither marker present ⇒ ask the user; do not guess.\n\n### Reading errors\n\nThe CLI ends every run with a `VALIDATION RESULTS` block, then\n`✅ VALIDATION PASSED` or `❌ VALIDATION FAILED`, and exits non-zero on\nfailure (safe to chain in scripts).\n\nOutput can be large on big trees — capture the full output to a file\nand read it in slices rather than scrolling inline.\n\n## Limitations\n\n- Validates DAFT only. Non-DAFT layouts (COCO, YOLO, Data Factory\n  JSONL, etc.) belong in the upstream converter skills.\n- Supported formats are whatever `tao-daft validate --help` reports\n  for the installed version; older slugs may have been retired.\n- Covers `validate` only. Defer to the dedicated skills for\n  `tao-daft info` and `tao-daft convert`.\n- Don't reimplement validation in Python; the CLI is the spec.\n\n## Troubleshooting\n\n- **`tao-daft: command not found`** — wheel not installed in the active\n  env. `pip install nvidia-tao-daft`; verify `tao-daft --version`.\n- **`error: argument --path is required`** — path passed positionally.\n  Move it behind `--path`.\n- **`invalid choice: '\u003Cformat>'`** — slug isn't wired up in this\n  version. Re-run `tao-daft validate --help` and pick from the list.\n- **Auto-detection (raw type \u002F contextual set) is wrong** — override\n  via the format's scope-restriction flag; discover the name from the\n  leaf `--help`.\n- **CI wants warnings to fail** — add `--strict`.\n","# Validate a TAO DAFT Dataset\n\n## Quick start\n\n```bash\ntao-daft validate \u003Cformat> --path \u003Cdataset-or-parent-dir>\n```\n\n`\u003Cformat>` is a positional subcommand (e.g. `metropolis-v3.0`, `cosmos-reason-v1.0`);\n`--path` is required. Discover supported formats and per-format flags via\n`tao-daft validate --help` and the leaf `--help` (see \"CLI conventions\" below).\n\n## Preflight\n```bash\npython -c \"import nvidia_tao_daft\" 2>\u002Fdev\u002Fnull || {\n  echo \"MISSING: tao-daft not installed. Run:\"\n  echo \"  pip install nvidia-tao-daft\"\n  exit 1\n}\n```\n\n## Quick Start\n\nDiscover the installed validator formats before choosing a format slug, then\nrun validation with the target passed through `--path`:\n\n```bash\ntao-daft --version\ntao-daft validate --help\ntao-daft validate \u003Cformat> --help\ntao-daft validate \u003Cformat> --path \u002Fpath\u002Fto\u002Fdaft-dataset\n```\n\n## Purpose\n\nDrive `tao-daft validate` against a DAFT dataset (or a tree of them).\nThe CLI is the spec; the skill picks subcommand + flags and explains\nthe result.\n\nTrigger when the user mentions \"TAO DAFT\", \"DAFT format\", validating a\nDAFT dataset, schema\u002Fcross-reference errors, or `tao-daft validate`.\nDo **not** trigger for non-DAFT layouts (COCO, YOLO, Data Factory JSONL),\nor for `tao-daft info` \u002F `tao-daft convert` — those have their own skills.\n\nIf the user's opening is ambiguous, run a few `--help` commands first\nto ground yourself, then come back and confirm the task.\n\n## Prerequisites\n\n- `nvidia-tao-daft` installed (`pip install nvidia-tao-daft`; the wheel\n  is enough, no source repo). Confirm with `tao-daft --version`.\n- A DAFT dataset, or a parent directory of them, on local disk.\n\n## Instructions\n\n### CLI conventions\n\n`tao-daft` is nested argparse subcommands. Names and flags drift across\nversions, so **discover the current surface from `--help`** rather than\ntrusting any list in this doc.\n\n1. **Format is a positional subcommand**, not `--format`:\n   `tao-daft validate \u003Cformat> [flags]`. List current formats via\n   `tao-daft validate --help`; slugs look like `metropolis-v3.0`,\n   `cosmos-reason-v1.0`.\n2. **Target is `--path PATH`**, not positional. It accepts a single\n   dataset\u002Fscene or a parent directory — the validator walks the tree.\n3. **Flags are per-format**; run the leaf help, e.g.\n   `tao-daft validate metropolis-v3.0 --help`, before choosing them.\n   Don't assume a flag from one format exists on another.\n\nSo the loop is: `tao-daft --version` → `tao-daft validate --help` →\npick format (infer if unspecified, see below) →\n`tao-daft validate \u003Cformat> --help` → run → interpret.\n\n### Format inference\n\nUse directory markers, not filenames:\n\n- `meta.json` next to `media\u002F` and `text\u002F` ⇒ `cosmos-reason-v1.0`.\n- A directory (or nested directories) containing `contextual\u002F`,\n  typically alongside `raw\u002F` and `task\u002F` ⇒ `metropolis-v3.0`.\n- Neither marker present ⇒ ask the user; do not guess.\n\n### Reading errors\n\nThe CLI ends every run with a `VALIDATION RESULTS` block, then\n`✅ VALIDATION PASSED` or `❌ VALIDATION FAILED`, and exits non-zero on\nfailure (safe to chain in scripts).\n\nOutput can be large on big trees — capture the full output to a file\nand read it in slices rather than scrolling inline.\n\n## Limitations\n\n- Validates DAFT only. Non-DAFT layouts (COCO, YOLO, Data Factory\n  JSONL, etc.) belong in the upstream converter skills.\n- Supported formats are whatever `tao-daft validate --help` reports\n  for the installed version; older slugs may have been retired.\n- Covers `validate` only. Defer to the dedicated skills for\n  `tao-daft info` and `tao-daft convert`.\n- Don't reimplement validation in Python; the CLI is the spec.\n\n## Troubleshooting\n\n- **`tao-daft: command not found`** — wheel not installed in the active\n  env. `pip install nvidia-tao-daft`; verify `tao-daft --version`.\n- **`error: argument --path is required`** — path passed positionally.\n  Move it behind `--path`.\n- **`invalid choice: '\u003Cformat>'`** — slug isn't wired up in this\n  version. Re-run `tao-daft validate --help` and pick from the list.\n- **Auto-detection (raw type \u002F contextual set) is wrong** — override\n  via the format's scope-restriction flag; discover the name from the\n  leaf `--help`.\n- **CI wants warnings to fail** — add `--strict`.\n",{"name":5,"tags":44,"license":15,"metadata":47,"description":7,"allowed-tools":50,"compatibility":51},[45,23,46,33],"tao-daft","validation",{"author":48,"version":49},"NVIDIA Corporation","0.1.0","Read Bash","Requires Python 3.10+ and the nvidia-tao-sdk package (pip install nvidia-tao-daft).","claude\u002Finstall-gsd-build-foQdV","d86cd127f527124b5fd0fd0bc679a4d79b7d01d7",".agents\u002Fskills\u002Ftao-validate-dataset-format","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik","https:\u002F\u002Fnorvik-orpin.vercel.app","https:\u002F\u002Fgithub.com\u002Fpattanation","2026-07-17 11:17:04",{"source":8,"skillName":5,"commands":60,"prompt":70,"zipAvailable":71},[61,64,67],{"tool":62,"command":63},"npx","npx skills add pattanation\u002FNorvik --skill tao-validate-dataset-format",{"tool":65,"command":66},"bunx","bunx skills add pattanation\u002FNorvik --skill tao-validate-dataset-format",{"tool":68,"command":69},"pnpm","pnpm dlx skills add pattanation\u002FNorvik --skill tao-validate-dataset-format","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Ftao-validate-dataset-format\u002FSKILL.md",true,[73,79,83,87],{"path":74,"resourceType":75,"resourceTypeDesc":76,"sizeBytes":77,"sourceHtmlUrl":78},"BENCHMARK.md","REFERENCE","参考文档",3853,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Ftao-validate-dataset-format\u002FBENCHMARK.md",{"path":80,"resourceType":75,"resourceTypeDesc":76,"sizeBytes":81,"sourceHtmlUrl":82},"evals\u002Fevals.json",880,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Ftao-validate-dataset-format\u002Fevals\u002Fevals.json",{"path":84,"resourceType":75,"resourceTypeDesc":76,"sizeBytes":85,"sourceHtmlUrl":86},"skill-card.md",3578,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Ftao-validate-dataset-format\u002Fskill-card.md",{"path":88,"resourceType":89,"resourceTypeDesc":90,"sizeBytes":91,"sourceHtmlUrl":92},"skill.oms.sig","OTHER","其他",4605,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Ftao-validate-dataset-format\u002Fskill.oms.sig",[94,126,151,175,197,212],{"skillNo":95,"name":96,"nameZh":6,"description":97,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":98,"sourceHtmlUrl":99,"categories":100,"keywords":109,"publishedAt":39},"01M71QDV4DM8T19HEHWATEF1K4","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. 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Strongly recommends Composition API with `\u003Cscript setup>` and TypeScript as the standard approach. Covers Vue 3, SSR, Volar, vue-tsc. Load for any Vue, .vue files, Vue Router, Pinia, or Vite with Vue work. ALWAYS use Composition API unless the project explicitly requires Options API.","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fvue-best-practices\u002FLICENSE.md","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fvue-best-practices\u002FSKILL.md",[219],{"categoryNo":107,"categoryName":108,"taxonomyType":104,"taxonomyTypeDesc":105},[221,172,187,222,164,223,224,225,206,226,227,228,229,230,231,28,232,34,233,234],"vue best practices","Composition","files","tasks","api","pinia","work","options","ssr","typescript","as","vite","load","standard"]