>-
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiontao-list-capabilitiesExecute the skills CLI command in your project's root directory to begin installation:
Fetches tao-list-capabilities from nvidia/skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate tao-list-capabilities. Access via /tao-list-capabilities in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
0
total installs
0
this week
1.7K
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
1.7K
stars
| name | tao-list-capabilities |
| description | >- Answer what the TAO Skill Bank plugin can do by generating the response from packaged application, data, model, AutoML, and platform manifests. Use when the user asks "what can TAO Skill Bank do", "list TAO models", "which TAO workflows are available", or "what supports AutoML". |
| license | Apache-2.0 |
| compatibility | Requires the packaged TAO skill bank helper scripts. |
| metadata | author: NVIDIA Corporation version: "0.1.0" |
| allowed-tools | Read Bash |
| tags | - tao - capabilities - discovery |
Use this skill when the user asks what tao-skill-bank can do, asks for plugin
capabilities, asks which application or data workflows are available, asks which
models are supported, or asks what models are capable with AutoML.
Run scripts/list_tao_capabilities.py for general capability questions, or
scripts/list_tao_models.py for model/action and AutoML support questions.
For a general capabilities answer, run the packaged helper:
${TAO_SKILL_BANK_PATH:-~/tao-skills-external}/scripts/list_tao_capabilities.py \
--skill-bank ${TAO_SKILL_BANK_PATH:-~/tao-skills-external} --format text
Use the helper output as the source of truth for the answer instead of manually enumerating capabilities from this skill or plugin metadata. Include:
applications/ and what it can do.data/ and what it can do.scripts/list_tao_platforms.py.models/: train,
evaluate, inference, export, and TensorRT engine generation when those actions
are present in the packaged schema manifest.When the user asks which TAO models are available or which actions a model can run, use the packaged model-list script instead of manually scanning model folders:
${TAO_SKILL_BANK_PATH:-~/tao-skills-external}/scripts/list_tao_models.py \
--skill-bank ${TAO_SKILL_BANK_PATH:-~/tao-skills-external} --scope all --format text
The model list comes from skills/models/schemas.manifest.json.
When the user asks what models are capable with AutoML, use the same model-list script in AutoML mode, or the compatibility wrapper:
${TAO_SKILL_BANK_PATH:-~/tao-skills-external}/scripts/list_tao_models.py \
--skill-bank ${TAO_SKILL_BANK_PATH:-~/tao-skills-external} --scope automl --format text
${TAO_SKILL_BANK_PATH:-~/tao-skills-external}/scripts/list_automl_support.py \
--skill-bank ${TAO_SKILL_BANK_PATH:-~/tao-skills-external} --format text
AutoML support requires skills/models/<network>/schemas/train.schema.json to be
packaged with the plugin and parse successfully as JSON. If that dataclass schema
is missing or invalid, do not describe the model as AutoML-supported.
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
nvidia/skills
nvidia/skills
nvidia/skills
nvidia/skills
nvidia/skills
nvidia/skills
tao-list-capabilities fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
tao-list-capabilities is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in tao-list-capabilities — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend tao-list-capabilities for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
tao-list-capabilities has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: tao-list-capabilities is focused, and the summary matches what you get after install.
I recommend tao-list-capabilities for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
tao-list-capabilities is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
tao-list-capabilities fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in tao-list-capabilities — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
showing 1-10 of 55