quark-workspace-validate

SkillFiles & storage

Validate workspace shape, model paths, output directories, and repo structure before downstream Quark skills proceed. Use this skill whenever a skill needs confirmed file paths, when the user provides a model path or output directory, when you need to distinguish a local model from a HuggingFace ID, or when any path assumption is unverified. Also trigger for "where should I put outputs", "is my model path right", or before model-intake/export steps.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the quark-workspace-validate skill

What this skill tells your AI

The instructions your AI receives, as published by amd/quark in .claude/skills-impl/l0-foundation/shared/quark-workspace-validate/SKILL.md and read by ahel’s review.

Purpose

Validate that file paths, model references, and output locations actually exist and are accessible before a downstream skill depends on them. This prevents silent failures where a PTQ run starts, spends time loading a model, and then crashes because the output directory does not exist or the model path has a typo.

Inputs

  • Model path and output directory from the user (typically forwarded by quark-torch-router)

Outputs: workspace_context.json

Records validated model paths, output directory, and repo locations.

Schema: workspace_context.schema.json

{
  "model_path": "/models/Qwen3-8B",
  "model_source": "local",
  "trust_remote_code_required": false,
  "output_dir": "./output/qwen3-8b-fp8",
  "output_dir_exists": false,
  "output_dir_parent_writable": true,
  "disk_space_gb_free": 250,
  "quark_script_path": null
}

workspace_context.json is for path facts only. Unresolved questions (e.g., ambiguous local-vs-HuggingFace reference) belong in session_context.json (owned by quark-torch-router).

What to Validate

Model Path

A model reference can be one of three things:

  1. Local directory — contains config.json, *.safetensors or *.bin files (e.g., /models/Llama-2-7b-hf/)
  2. HuggingFace ID — format org/model-name (e.g., Qwen/Qwen3-8B)
  3. Ambiguous — could be either (e.g., ./qwen3-8b might be a local dir or a typo)

For local paths, check:

  • Directory exists
  • config.json is present (minimum requirement for HuggingFace-compatible model)
  • At least one weight file exists (.safetensors, .bin, or .pth)
  • Read permissions are adequate

For HuggingFace IDs, note:

  • Cannot fully validate without network access
  • Check format: should contain / separator
  • Record whether trust_remote_code will be needed (some models like DeepSeek VL v2 require it)

Output Directory

  • Check that the parent directory exists and is writable
  • If the output directory itself does not exist, note that it will be created (not an error)
  • Warn if the directory already contains files (risk of overwriting previous results)

Quark Repository (if applicable)

  • If the user is running from source, check for quantize_quark.py at the expected location: examples/torch/language_modeling/llm_ptq/quantize_quark.py
  • Check that requirements.txt dependencies are likely installed

Validation Commands

# Check model directory
ls -la /path/to/model/config.json 2>/dev/null
ls /path/to/model/*.safetensors 2>/dev/null

# Check output directory parent
test -d /path/to/output/.. && echo "parent exists"
test -w /path/to/output/.. && echo "parent writable"

# Check disk space (rough)
df -h /path/to/output/..

Rules

  • Only validate existence, accessibility, and shape. Do not analyze model internals (that is quark-torch-model-intake) or choose install paths (that is quark-install).
  • Never invent replacement paths. If /data/models/llama does not exist, say so — do not suggest /data/models/llama-2 as an alternative unless the user asks.
  • Preserve ambiguity explicitly. When a reference like meta-llama/Llama-2-7b could be local or remote, say: "This looks like a HuggingFace model ID. If you meant a local directory, the path does not exist at ./meta-llama/Llama-2-7b."
  • Check disk space when the downstream task is PTQ or export — quantized models can be large.

Interaction Flow

  1. Collect: Gather the paths the downstream skill needs — model path, output directory, any referenced config files.
  2. Validate: Run existence and permission checks. Present results as a checklist with pass/fail for each item.
  3. Clarify: For ambiguous references, ask the user. For missing paths, report the exact issue.
  4. Emit: Write confirmed facts to workspace_context.json. Hand any unresolved items back to quark-torch-router so they land in session_context.json's open_questions.

Recovery

  • If a required path is missing, report the exact path tested and what was expected. Suggest the smallest fix: "Directory /data/models/llama does not exist. Did you mean /data/models/Llama-2-7b-hf?"
  • If a model reference is ambiguous between local and HuggingFace, keep it unresolved and ask — do not guess.
  • If disk space is low for the intended output, warn with the estimated size needed.

Signals

GitHub stars
166
Forks
33
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
quark-workspace-validate
Source
github.com/amd/quark