tao-list-capabilities — Claude Code skill: features and setup

---
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
---

# TAO Skill Bank Capabilities

> **Standalone install?** If this session was not initialized by the TAO skill bank plugin, run the `tao-setup` skill first (host preflight, credentials, cross-skill 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.

## Quick Start

Run `scripts/list_tao_capabilities.py` for general capability questions, or
`scripts/list_tao_models.py` for model/action and AutoML support questions.

## Capability Answers

For a general capabilities answer, run the packaged helper:

```bash
${TAO_SKILL_BANK_PATH:-~/tao-skill-bank}/scripts/list_tao_capabilities.py \
  --skill-bank ${TAO_SKILL_BANK_PATH:-~/tao-skill-bank} --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:

- Every top-level application workflow under `applications/` and what it can do.
- Every top-level data workflow under `data/` and what it can do.
- Supported execution platforms, discovered from the installed platform skills
  (tao-run-on-docker / -slurm / -kubernetes / -brev, plus any external one); on a
  runtime that surfaces only the core router skills, read
  `skills/platform/tao-run-on-*/SKILL.md` frontmatter.
- The fine-tuning/deployment workflow coverage for models under `models/`: train,
  evaluate, inference, export, and TensorRT engine generation when those actions
  are present in the packaged schema manifest.
- AutoML support and the AutoML per-action schema gate.

## Model Lists

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:

```bash
${TAO_SKILL_BANK_PATH:-~/tao-skill-bank}/scripts/list_tao_models.py \
  --skill-bank ${TAO_SKILL_BANK_PATH:-~/tao-skill-bank} --scope all --format text
```

The model list comes from `skills/models/schemas.manifest.json`.

## AutoML Lists

When the user asks what models are capable with AutoML, use the same model-list
script in AutoML mode, or the compatibility wrapper:

```bash
${TAO_SKILL_BANK_PATH:-~/tao-skill-bank}/scripts/list_tao_models.py \
  --skill-bank ${TAO_SKILL_BANK_PATH:-~/tao-skill-bank} --scope automl --format text
```

```bash
${TAO_SKILL_BANK_PATH:-~/tao-skill-bank}/scripts/list_automl_support.py \
  --skill-bank ${TAO_SKILL_BANK_PATH:-~/tao-skill-bank} --format text
```

Use `--action distill`, `--action prune`, or `--action quantize` when the user
asks about a specific compression action.

AutoML support for an action requires
`skills/models/<model_skill>/schemas/<action>.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/action as AutoML-supported.