agentleFS
NVIDIAKnown publisherNVIDIA/Trustworthy-AI/skills/skill-card-generator/SKILL.md

skill-card-generator

Skill70 starsChanged 5 months agoCC0-1.0View on GitHub

Use only to generate or update a governance skill card for a specified existing agent skill directory. Do not use for explaining, listing, comparing, or discussing skill capabilities.

  • Reads credentials

3 other projects use a version of this, 2 of them edited.

Adopted by

Most recently taken up by

  • Other versions3 projects use a version of this.

    Word for word · 1

    1. NVIDIA/skills★ 3.9k100% same

    Wrote their own version · 0

    None found.

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 2 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Create a draft NVIDIA governance skill card for an existing agent skill.

    line 35
  2. Distinctive:

    Do NOT use for:

    line 42
  3. Very specific:

    Run scripts/discover_assets.py against the target.

    line 62
  4. Very specific:

    Follow references/style-guide.md for every context field.

    line 65
  5. Very specific:

    Before finishing, confirm the rendered card has no unrendered {{ ...

    line 68

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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

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Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.