Quark Env Preflight

What it does

When your agent uses it

• A downstream skill needs confirmed hardware and toolchain facts
• The user mentions their setup
• You need to decide between CUDA/ROCm/CPU install paths
• Any accelerator-related assumption is unconfirmed

Example prompts

• “check my environment”
• “what GPU do I have”
• “is my setup ready for Quark”
• “/quark-env-preflight”

Requirements

• Python 3
• Docker

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

1. 1Intake: Ask what downstream task the user is headed toward (install? PTQ? just checking?). This determines which facts are critical vs…
2. 2Detect: Run the detection commands above. Present what was found in a clear summary table.
3. 3Clarify: If the accelerator is ambiguous or versions are uncertain, ask the user — do not guess. Show them the conflicting evidence.
4. 4Emit: Write the confirmed facts to env_context.json. Hand any unresolved items back to the caller (typically quark-torch-router) so they…

What it can do on your machine

Read from SKILL.md and the folder at commit 313cb0b. It shows what the files ask for, not the result of running them.

• Tool permissions

  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.

• Runs code

  Shell commands in SKILL.md call:

  • python
  • pip

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

• Network

  No URLs in SKILL.md. Its commands use pip, 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 no API keys, tokens, secrets or passwords.

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

Context cost

Quark Env Preflight loads about 1.4k tokens when it runs. Until then it costs about 147 tokens; SKILL.md has 528 words of instructions outside code blocks.

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

~147

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

~1.4k

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

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 amd/Quark at commit 313cb0b, republished under its MIT licence (© amd). 528 words, ~1,413 tokens.

name

quark-env-preflight

description

Collect and normalize environment facts (OS, Python, GPU, CUDA/ROCm, container state) before Quark installation or PTQ planning. Use this skill whenever a downstream skill needs confirmed hardware and toolchain facts, when the user mentions their setup, when you need to decide between CUDA/ROCm/CPU install paths, or when any accelerator-related assumption is unconfirmed. Also trigger when the user says things like "check my environment", "what GPU do I have", "is my setup ready for Quark", or before any install/quantization step where hardware facts are missing.

layer

l0-foundation

primary_artifact

env_context.json

source_knowledge

docs/source/install.rst, pyproject.toml, tools/ci/install_torch.sh

{
  "environment": {
    "os": "linux",
    "python": "3.13",
    "containerized": false
  },
  "hardware": {
    "accelerator": "nvidia-cuda",
    "cuda_version": "12.6",
    "gpu_count": 1,
    "gpu_model": "RTX 4090",
    "memory_gb": 24
  }
}

# OS and Python
python --version
uname -a  # or systeminfo on Windows

# GPU detection (try both, one will fail gracefully)
nvidia-smi --query-gpu=name,memory.total,driver_version --format=csv,noheader 2>/dev/null
rocm-smi --showproductname 2>/dev/null

# Environment variables
echo $CUDA_HOME $CUDA_VISIBLE_DEVICES $ROCM_PATH $HIP_VISIBLE_DEVICES

# Existing packages
pip show amd-quark torch 2>/dev/null
python -c "import torch; print(torch.__version__, torch.version.cuda, torch.version.hip)"

© amd, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills-impl/l0-foundation/shared/quark-env-preflight of amd/Quark.

Open the folder on GitHubat commit 313cb0b