skill-card-generator

par nvidia

Utiliser uniquement pour générer ou mettre à jour une fiche de compétence de gouvernance pour un répertoire de compétences d’agent existant spécifié. Ne pas utiliser pour expliquer, lister, comparer ou…

npx skills add https://github.com/nvidia/skills --skill skill-card-generator

Generate Skill Card

Skill directory to analyze: $ARGUMENTS

Purpose

Create a draft NVIDIA governance skill card for an existing agent skill. The skill gathers source signals, guides the agent to build a grounded JSON context, renders a deterministic markdown card, and checks that human-review markers were removed before submission.

Use this when:

  • A skill directory already exists and needs a new governance card.
  • A changed skill needs its existing card refreshed.
  • A skill owner is preparing legal/safety review material.

Do NOT use for:

  • Explaining, listing, comparing, or discussing skills or skill capabilities.
  • Creating or rewriting the source skill itself.
  • Generating cards for non-skill assets such as models, datasets, containers, or full systems.
  • Signing, publishing, or approving a skill card.
  • Replacing required human legal, safety, or owner review.

Prerequisites

  • Python 3 is available.
  • jinja2 is installed before running render_card.py.
  • The target path is a skill directory containing SKILL.md or skill.md.
  • The agent can write a temporary context JSON file and the rendered card output.
  • Runtime permissions allow reads from target_skill_directory plus this skill's references/ and scripts/, writes only to the target skill directory or /tmp/, and shell execution only for the three scripts listed below.

Instructions

  1. First, read this SKILL.md completely before running any script.
  2. Resolve the target skill directory from $ARGUMENTS; if omitted, use the current working directory.
  3. Stay within the declared permission scope. Do not read .env, credential files, hidden auth folders, or unrelated repo files; do not write outside the target skill directory or /tmp/.
  4. Run scripts/discover_assets.py against the target. Use the structured signal summary first; if output is truncated, read only targeted files or small excerpts.
  5. Build a context JSON file from the structured signal summary first, then from extracted file contents only when needed.
  6. Populate credential_requirements with only two fields: requires_api_key_or_credential and credential_types. Ground the classification in SKILL.md prose documentation — not script inspection alone. For credential_types, use the controlled vocabulary in references/style-guide.md. Never include credential values, assignments, or raw environment variable names.
  7. Follow references/style-guide.md for every context field. Use HUMAN-REQUIRED only when no source supports a truthful value.
  8. Render the card with scripts/render_card.py and fix any schema errors before proceeding.
  9. Review the card manually, remove resolved VERIFY and SELECT markers, then run scripts/validate_submission.py.
  10. Before finishing, confirm the rendered card has no unrendered {{ ... }} or {% ... %} template fragments.

Available Scripts

ScriptPurposeArguments
scripts/discover_assets.pyExtracts skill files, repo signals, style guide, and template into one discovery report.<skill_directory>
scripts/render_card.pyValidates context JSON and renders the skill card from the Jinja template.--context <context.json> --template <skill-card.md.j2> --out <output.md>
scripts/validate_submission.pyFails if the rendered card still contains VERIFY or SELECT review markers.<rendered-card.md>

Examples

Discover signals for a target skill:

run_script("scripts/discover_assets.py", args=["/path/to/target-skill"])

Render a card from the completed context:

run_script(
  "scripts/render_card.py",
  args=[
    "--context", "/tmp/target-skill-context.json",
    "--template", "references/skill-card.md.j2",
    "--out", "/path/to/target-skill/target-skill-card.md"
  ]
)

Validate the reviewed card before submission:

run_script("scripts/validate_submission.py", args=["/path/to/target-skill/target-skill-card.md"])

Limitations

  • The generated card is a draft and must be reviewed by a human owner.
  • Discovery is limited to local files and repo metadata visible from the target path.
  • The renderer validates required context shape, not the legal or safety correctness of field values.
  • Canned limitation and risk catalogs are starting points; remove entries that do not apply.

Troubleshooting

ErrorCauseSolution
directory not foundThe target path is wrong or not mounted in the workspace.Re-run discovery with the absolute path to the skill directory.
jinja2 not installedThe renderer dependency is missing.Install jinja2, then re-run render_card.py.
Context validation failedRequired fields are missing or typed incorrectly.Fix the context JSON using references/style-guide.md.
Unresolved marker failureVERIFY or SELECT markers remain after review.Confirm each marked field, prune catalog entries, then re-run validate_submission.py.

Files in this skill

  • SKILL.md - this file (orchestration)
  • references/style-guide.md - per-context-field guidance
  • references/skill-card.md.j2 - exact card layout
  • references/Skill Card Generator License.txt - license text for this skill package
  • references/catalog/limitations.json - canned technical-limitations catalog
  • references/catalog/risks.json - canned risk-management catalog
  • scripts/discover_assets.py - discovery and signal extraction
  • scripts/render_card.py - Jinja renderer with context validation
  • scripts/validate_submission.py - pre-submission marker validator

Plus de skills de nvidia

compileiq-debug
nvidia
Utilisez quand quelque chose ne va pas : Search() bloque, toutes les évaluations retournent INVALID_SCORE, les scores ne s'améliorent pas, chaque configuration retourne le même nombre, erreurs ptxas…
create-github-pr
nvidia
Créer des pull requests GitHub en utilisant l'interface en ligne de commande gh. Utiliser lorsque l'utilisateur souhaite créer une nouvelle PR, soumettre du code pour révision, ou ouvrir une pull request. Mots-clés de déclenchement -…
nemoclaw-maintainer-cross-issue-sweep
nvidia
Analyse les autres problèmes ouverts pour trouver ceux qu’une PR donnée pourrait également corriger ou casser accidentellement. Génère des opportunités de correctifs adjacents et des risques de contradiction avec fichier:ligne…
fhir-basics
nvidia
Apprend aux agents comment fonctionnent les API FHIR R4, quelles ressources sont disponibles, comment les interroger avec des paramètres de recherche, et comment analyser correctement tous les formats de réponse…
compileiq-validate-result
nvidia
Utiliser APRÈS qu'une recherche soit terminée et AVANT de réclamer un accélérateur ou d'expédier un ACF. Charge le CSV dump_results, extrait les K meilleurs candidats (mono-objectif)…
changelog-audit
nvidia
Auditer le CHANGELOG.md de Warp avant une publication : récupérer les entrées perdues, trier par impact utilisateur, affiner le langage des entrées, ajuster les retours à la ligne et (en mode branche de publication) mettre à jour la comparaison…
maintain-dynamic-plugins
nvidia
Maintenir les chargeurs de plugins dynamiques NeMo Relay, les manifestes, les SDK natifs Rust, le protocole worker gRPC, le SDK worker Python, la documentation, les tests et la couverture du workflow de publication
dgx-diagnose
nvidia
Diagnostiquer les problèmes courants du DGX Station GB300 — plantages CUDA, ciblage incorrect du GPU, bugs de conteneur vLLM/SGLang, problèmes d'état MIG, erreurs NVLink/Fabric Manager,…