skill-card-generator

द्वारा nvidia

केवल निर्दिष्ट मौजूदा एजेंट कौशल निर्देशिका के लिए शासन कौशल कार्ड उत्पन्न या अद्यतन करने के लिए उपयोग करें। व्याख्या, सूचीकरण, तुलना या… के लिए उपयोग न करें।

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

nvidia की और Skills

compileiq-debug
nvidia
उपयोग करें जब कुछ गलत हो: Search() हैंग हो जाता है, सभी मूल्यांकन INVALID_SCORE लौटाते हैं, स्कोर में सुधार नहीं हो रहा है, हर कॉन्फ़िगरेशन एक ही संख्या लौटाता है, ptxas त्रुटियाँ…
create-github-pr
nvidia
gh CLI का उपयोग करके GitHub पुल रिक्वेस्ट बनाएँ। जब उपयोगकर्ता नया PR बनाना चाहता है, कोड समीक्षा के लिए सबमिट करना चाहता है, या पुल रिक्वेस्ट खोलना चाहता है, तब उपयोग करें। ट्रिगर कीवर्ड -…
nemoclaw-maintainer-cross-issue-sweep
nvidia
अन्य खुले मुद्दों को स्कैन करता है ताकि उन मुद्दों को ढूंढ सके जिन्हें कोई दिया गया PR ठीक कर सकता है या गलती से तोड़ सकता है। आसन्न-सुधार अवसरों और विरोधाभास जोखिमों को file:line… के साथ आउटपुट करता है।
fhir-basics
nvidia
एजेंटों को सिखाता है कि FHIR R4 APIs कैसे काम करते हैं, कौन से संसाधन उपलब्ध हैं, उन्हें खोज मापदंडों के साथ कैसे क्वेरी करें, और सभी प्रतिक्रिया प्रारूपों को सही ढंग से कैसे पार्स करें…
compileiq-validate-result
nvidia
खोज पूरी होने के बाद और किसी स्पीडअप का दावा करने या ACF भेजने से पहले उपयोग करें। dump_results CSV लोड करता है, शीर्ष-K उम्मीदवारों (एकल-उद्देश्य) को निकालता है…
changelog-audit
nvidia
रिलीज़ से पहले Warp CHANGELOG.md का ऑडिट करें: खोई हुई प्रविष्टियाँ पुनर्प्राप्त करें, उपयोगकर्ता प्रभाव के अनुसार क्रमबद्ध करें, प्रविष्टि भाषा को परिष्कृत करें, लाइन-रैप करें, और (रिलीज़-ब्रांच मोड) तुलना बढ़ाएँ…
maintain-dynamic-plugins
nvidia
NeMo Relay डायनामिक प्लगइन लोडर, मैनिफेस्ट, रस्ट नेटिव SDK, gRPC वर्कर प्रोटोकॉल, पायथन वर्कर SDK, दस्तावेज़, परीक्षण और रिलीज़ वर्कफ़्लो कवरेज बनाए रखें
dgx-diagnose
nvidia
सामान्य DGX Station GB300 समस्याओं का निदान करें — CUDA क्रैश, गलत-GPU लक्ष्यीकरण, vLLM/SGLang कंटेनर बग, MIG स्थिति समस्याएं, NVLink/Fabric Manager त्रुटियां,…