Skill Inspector
NVIDIA/SkillSpector
Decides whether an agent skill is safe to install by combining a SkillSpector static scan with the agent's own source review, ending in APPROVE, CAUTION or REJECT.
Model and publish semantic definitions in Auto Ontology. An agent skill from NVIDIA/skills.
$ npx skills add NVIDIA/skills --skill nvidia-ontology-management -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/skills nvidia-ontology-management --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/nvidia-ontology-management .claude/skills/nvidia-ontology-management && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "nvidia-ontology-management" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nvidia-ontology-management into .claude/skills/nvidia-ontology-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nvidia-ontology-management", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/NVIDIA/skills/tree/main/skills/nvidia-ontology-managementType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add NVIDIA/skills --skill nvidia-ontology-management -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/skills nvidia-ontology-management --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/nvidia-ontology-management .agents/skills/nvidia-ontology-management && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "nvidia-ontology-management" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nvidia-ontology-management into .agents/skills/nvidia-ontology-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nvidia-ontology-management", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/skills --skill nvidia-ontology-management -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/skills nvidia-ontology-management --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/nvidia-ontology-management .cursor/skills/nvidia-ontology-management && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "nvidia-ontology-management" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nvidia-ontology-management into .cursor/skills/nvidia-ontology-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nvidia-ontology-management", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/NVIDIA/skills.git --path skills/nvidia-ontology-management--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NVIDIA/skills --skill nvidia-ontology-management -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/skills nvidia-ontology-management --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/nvidia-ontology-management .gemini/skills/nvidia-ontology-management && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "nvidia-ontology-management" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nvidia-ontology-management into .gemini/skills/nvidia-ontology-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nvidia-ontology-management", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install NVIDIA/skills nvidia-ontology-managementInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add NVIDIA/skills --skill nvidia-ontology-management -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/nvidia-ontology-management .github/skills/nvidia-ontology-management && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "nvidia-ontology-management" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nvidia-ontology-management into .github/skills/nvidia-ontology-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nvidia-ontology-management", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/skills --skill nvidia-ontology-management -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NVIDIA/skills nvidia-ontology-management --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/nvidia-ontology-management .opencode/skills/nvidia-ontology-management && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "nvidia-ontology-management" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nvidia-ontology-management into .opencode/skills/nvidia-ontology-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nvidia-ontology-management", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
nvidia-ontology-managementModel and publish semantic definitions in Auto Ontology. An agent skill from NVIDIA/skills.
Nvidia Ontology Management is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Model and publish semantic definitions in Auto Ontology. Use for terms, relationships, measures, imports, and governed results—not deployment or querying.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including reference files and assets (for example `BENCHMARK.md`, `assets/runtime-contract.yaml` and `evals/evals.json`).
It sits in DevOps & Cloud. It works with NVIDIA AI Platform and Model Context Protocol. The repository describes itself as: Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end. The licence is Apache-2.0.
7 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 14a98ae. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Nvidia Ontology Management loads about 1.6k tokens when it runs, and up to ~5.1k if it reads all its reference files. Until then it costs about 45 tokens; SKILL.md has 644 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from NVIDIA/skills at commit 14a98ae, republished under its Apache-2.0 licence (© NVIDIA). 644 words, ~1,571 tokens.
.claude/skills/nvidia-ontology-management/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.<!--
SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES.
All rights reserved.
SPDX-License-Identifier: Apache-2.0
-->
Inspect and change Auto Ontology's semantic layer without confusing a successful API call with correct business meaning or durable publication. The machine-readable inputs, outputs, statuses, gates, and handoffs are in runtime-contract.yaml.
Choose the focused workflow before acting:
MCP tools only read. Create, patch, import, and compile-reset go through
the Next.js /api/... gateway. Governed result rows require an approved source
writer; Auto Ontology has no generic result-row writeback endpoint. Request bodies and
field types live in docs/openapi/auto-ontology-api.json; this skill names operations and
permissions only.
Use a running, authenticated Auto Ontology deployment. Use nvidia-ontology-setup when
the deployment or semantic layer is not ready.
MCP is read-only, Auto Ontology has no generic result-row writeback endpoint, and current model import and certification APIs do not prove atomic promotion. Follow the publication gates below and fail closed when exact readback is unavailable.
Scripts use an API token (x-api-key or Authorization: Bearer). Mint it in
the UI (user menu → API Tokens). A token acts as its owner — a viewer's
token cannot do admin things. Creating and revoking tokens requires a signed-in
session; a token cannot mint another token.
Writes below need catalog:edit unless noted. 403 means the owner's role
lacks that permission, not that the path is wrong.
search_terms, get_term,
get_term_columns, get_term_sql_attributes, describe_table) or REST
if MCP is absent (GET /api/terms, GET /api/terms/{term_id},
GET /api/exploration/tables/{table_id}/details).POST /api/sql-attributes/validate.
A parse failure is HTTP 422, not valid: false.GET /api/semantic-compilation/status. Do not call
POST /api/semantic-compilation/reset as cleanup — it is an asynchronous,
destructive rebuild of every database's compiled layer, returns 202, and
requires semanticCompilation:manage.check_answerable / ask_question (or REST
POST /api/question-entity-coverage and POST /api/chat/completions) for
positive and negative behavior checks.Stay on the semantic layer. Do not browse raw schemas to answer meaning.
get_term_columns or
GET /api/terms/{term_id}/column-attributesget_term_sql_attributesdescribe_table or
GET /api/exploration/tables/{table_id}/detailsGET /api/exploration/terms/{term_id}/path/{other_term_id}GET /api/exploration/graph,
GET /api/exploration/semantic-graphThese are semantic relationship paths, not generation provenance, source revision, certification history, or version lineage.
POST /api/model/export — YAML of catalog + semantic layer.
Permission modelInterchange:export. Body may set catalog database IDs
in databases (empty = all) and format (auto_ontology or ossie).POST /api/model/import — multipart YAML; native Auto Ontology
(data_layer / semantic_layer) or Apache Ossie (version, name,
datasets at the root).
Query replace (default true) and embed (default true). Permission
modelInterchange:import. Can replace existing data — confirm with the
user before replace=true, apply first in isolation, and use the exact
readback workflow in publication.md.For write failures, verify the authenticated owner's permission, distinguish HTTP 422 parse failures from validation results, and inspect compilation status before changing the model or resetting compilation.
nvidia-ontology-query — how to call Auto Ontology and validate query resultsnvidia-ontology-setup — deployment not readymcp/auto_ontology_mcp/tools.py — live read-tool allow-list© NVIDIA, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 8 other files (references, assets) in skills/nvidia-ontology-management of NVIDIA/skills.
Open the folder on GitHubat commit 14a98ae
Nvidia Ontology Management next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Nvidia Ontology Management this skillNVIDIA/skills | 3.6k | — | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Skill InspectorNVIDIA/SkillSpector | 20k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| AWS Cdk Developmentzxkane/aws-skills | 367 | 2 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Terravision Cloud Diagramspatrickchugh/terravision | 1.6k | — | ~5.6k | Automated safety check: Notes | AGPL-3.0-only | |
| Rocketmq Rust Local Clustermxsm/rocketmq-rust | 1.5k | — | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Trigger.dev Cost Savings Auditpapermark/papermark | 9.2k | — | ~1.3k | Automated safety check: Pass | Custom licence |
NVIDIA/SkillSpector
Decides whether an agent skill is safe to install by combining a SkillSpector static scan with the agent's own source review, ending in APPROVE, CAUTION or REJECT.
zxkane/aws-skills
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Works with
Categories
Model and publish semantic definitions in Auto Ontology. An agent skill from NVIDIA/skills. Nvidia Ontology Management is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Model and publish semantic definitions in Auto Ontology.
Nvidia Ontology Management fits situations like: governed results—not deployment.
Run `npx skills add NVIDIA/skills --skill nvidia-ontology-management -a claude-code`. Or copy the skill folder (skills/nvidia-ontology-management in NVIDIA/skills) into .claude/skills/nvidia-ontology-management in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA/skills --skill nvidia-ontology-management -a codex`. Or copy the skill folder (skills/nvidia-ontology-management in NVIDIA/skills) into .agents/skills/nvidia-ontology-management in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/skills --skill nvidia-ontology-management -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nvidia-ontology-management, .gemini/skills/nvidia-ontology-management, .github/skills/nvidia-ontology-management and .opencode/skills/nvidia-ontology-management in your project.
SKILL.md names no scripts, command-line tools or credentials: Nvidia Ontology Management is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Nvidia Ontology Management is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.6k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Nvidia Ontology Management: Skill Inspector (NVIDIA/SkillSpector, 20k stars), AWS Cdk Development (zxkane/aws-skills, 367 stars), Terravision Cloud Diagrams (patrickchugh/terravision, 1.6k stars) and Rocketmq Rust Local Cluster (mxsm/rocketmq-rust, 1.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,555 GitHub stars. The repository holds 390 skills in this directory. The repository was last updated on October 9, 2026.
Source: NVIDIA/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.