Tao Data Io

What it does

When your agent uses it

• Phrases include stage inputs
• Mount the dataset
• Upload TAO results
• Download only referenced files

Example prompts

• “stage inputs”
• “mount the dataset”
• “upload TAO results”
• “/tao-data-io”

Requirements

• Python 3
• Docker
• A credential in AWS_SECRET_ACCESS_KEY
• A credential in ACCESS_KEY
• Compatibility (from SKILL.md): Requires aws CLI or s5cmd on the staging host, plus Python 3.10+ with boto3 and pandas/pyarrow for annotation-selective download. No nvidia-tao-sdk, no fsspec/s3fs. Credentials are read from the process environment, whether exported in the user's shell or sourced from a user-approved env file.
• Pre-approved tools (allowed-tools): Read, Bash

What it can do on your machine

Read from SKILL.md and the folder at commit 67a13c0. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Read
  • Bash

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships script files (Python), which the agent can run.

  Shell commands in SKILL.md call:

  • aws
  • python
  • kubectl
  • huggingface-cli

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md. Its commands use aws and kubectl, which can reach the network depending on how they are called.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names these keys or tokens, usually read from environment variables:

  • AWS_ACCESS_KEY_ID
  • AWS_SECRET_ACCESS_KEY
  • ACCESS_KEY
  • SECRET_KEY
  • HF_TOKEN
  • NGC_KEY

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  Requires aws CLI or s5cmd on the staging host, plus Python 3.10+ with boto3 and pandas/pyarrow for annotation-selective download. No nvidia-tao-sdk, no fsspec/s3fs. Credentials are read from the process environment, whether exported in the user's shell or sourced from a user-approved env file.

  From compatibility in the SKILL.md frontmatter.

Context cost

Tao Data Io loads about 1.5k tokens when it runs, and up to ~5.2k if it reads all its reference files. Until then it costs about 170 tokens; SKILL.md has 590 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~170

When it runs · the whole SKILL.md, loaded when a task matches

~1.5k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~5.2k

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.

Safety

• WarningMentions a credentials file (SSH keys, cloud or package-manager tokens)SKILL.md:39

  and **never** write `~/.aws/credentials`:

• NoteMentions a .env fileSKILL.md:42

  set -a; source /path/to/.env; set +a   # omit if already exported

• NoteMentions a .env fileSKILL.md:98

  set -a; source /path/to/.env; set +a   # omit if already exported

• NotePre-approves every shell command (allowed-tools: Bash)SKILL.md

  allowed-tools: Read, Bash

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.

SKILL.md

The full file from NVIDIA/skills at commit 67a13c0, republished under its Apache-2.0 licence (© NVIDIA). 590 words, ~1,501 tokens.

name

tao-data-io

description

The data-mover for TAO jobs — decides the storage tier (A pre-positioned mount with zero fetch / B volume-from-S3 / C ephemeral in-compute fetch), stages inputs (bulk + annotation-selective + archive extract + HF/NGC PTM), maps credentials to env, routes outputs 3-way with upload-excludes, and runs the compute-frame verify gate. A support skill other platform skills (docker, kubernetes, slurm, brev, virtualenv) call to get data to and from the compute container without the TAO SDK. Trigger phrases include "stage inputs", "mount the dataset", "upload TAO results", "download only referenced files", "resolve results_dir", "verify the container can read the data".

allowed-tools

Read, Bash

compatibility

Requires aws CLI or s5cmd on the staging host, plus Python 3.10+ with boto3 and pandas/pyarrow for annotation-selective download. No nvidia-tao-sdk, no fsspec/s3fs. Credentials are read from the process environment, whether exported in the user's shell or sourced from a user-approved env file.

license

Apache-2.0

metadata.author

NVIDIA Corporation

metadata.version

0.1.0

tags

platform, storage

set -a; source /path/to/.env; set +a   # omit if already exported
aws s3 ls "s3://$S3_BUCKET_NAME/..."   # reads AWS_* from the environment

set -a; source /path/to/.env; set +a   # omit if already exported
python references/selective_download.py \
  --annotation /path/to/annotation.parquet \
  --key video \
  --bucket "$S3_BUCKET_NAME" --src-prefix datasets/clips \
  --dest /data/stage/clips

© 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

Files

SKILL.md and 7 other files (references) in skills/tao-data-io of NVIDIA/skills.

• SKILL.md
• BENCHMARK.md
• config/skillspector-baseline.yaml
• evals/evals.json
• references/selective_download.py
• references/tests/test_selective_download.py
• skill-card.md
• skill.oms.sig

Open the folder on GitHubat commit 67a13c0

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in NVIDIA/skills, which our catalogue first saw on October 7, 2026.

• majiayu000/claude-skill-registryskills/bash/tao-data-io