Agent skill · Audited from source

qwen-edit

skill · digitalsamba/claude-code-video-toolkitMIT licenceAudited 28 Oct 2026 · source 172a5100d7ed

★ 2,364pushed today
✓SAFEGrade B · 89/100 · 28 Oct 2026 · 172a510
2,364repo stars · whole digitalsamba/claude-code-video-toolkit

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 172a5100d7ed and found no filesystem, network or shell access and no hard-coded secrets. What it does: AI image editing prompting patterns for Qwen-Image (Qwen-Image-Edit-2511 by default, Qwen-Image-2.1 as a non-commercial Modal opt-in). Use when editing photos while preserving identity, reframing cropped images,…

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Cite this page

ModelsAtlas. “qwen-edit (digitalsamba/claude-code-video-toolkit)”. Retrieved 28 Oct 2026. https://modelsatlas.com/skills/digitalsamba/qwen-edit

Trust audit

Audit 0.4.1 · source read 28 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 13,985 of 14,816 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 172a5100d7ed · 28 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publisherdigitalsamba GitHub organizationOwner of the repository this skill is read from
  • Source folderdigitalsamba/claude-code-video-toolkit/.claude/skills/qwen-editThe exact folder we audited
  • LicenceMITAs the repository states it
  • Commit pinned for this verdict172a5100d7edA new audit runs when the source changes
  • Repository statusNot archivedPushed today
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: AI image editing prompting patterns for Qwen-Image (Qwen-Image-Edit-2511 by default, Qwen-Image-2.1 as a non-commercial Modal opt-in). Use when editing photos while preserving identity, reframing cropped images,…

---
name: qwen-edit
description: AI image editing prompting patterns for Qwen-Image (Qwen-Image-Edit-2511 by default, Qwen-Image-2.1 as a non-commercial Modal opt-in). Use when editing photos while preserving identity, reframing cropped images, changing clothing or accessories, adjusting poses, applying style transfers, or character transformations. Provides prompt patterns, parameter tuning, and examples.
---

# Qwen-Image-Edit Skill

AI-powered image editing via `tools/image_edit.py`. The model depends on the deployment:

| Deployment | Model | License | Defaults | Max inputs |
|-----------|-------|---------|----------|------------|
| `--cloud modal` (default) | Qwen-Image-Edit-2511 | Apache-2.0, commercial OK | 8 steps, guidance 1.0 | 3 images |
| `--cloud modal`, app deployed with `IMAGE_EDIT_MODEL=qwen-image-2.1` | **Qwen-Image-2.1** (2026-09, unified gen+edit, 7B DiT, RGBA) | Qwen Research License -- **non-commercial** ("research or evaluation purposes only") | 40 steps, guidance 1.0 (no CFG) | 10 images |
| `--cloud runpod` | Qwen-Image-Edit-2511 + Lightning LoRA | Apache-2.0, commercial OK | 8 steps, guidance 1.0 | 3 images |

The tool prints `Model:` and `Steps:` after each edit, so you can tell which model the Modal app
runs and how many steps it took. Without `--steps`, each model runs its own default above.
Opt in with `IMAGE_EDIT_MODEL=qwen-image-2.1 uv run modal deploy docker/modal-image-edit/app.py`;
deploy again without it to switch back.

**Status:** Evolving - learnings being captured as we experiment. The prompt
patterns and parameter findings in `examples.md` / `parameters.md` were measured
on 2511; re-check them on 2.1 before relying on the exact numbers.

### Qwen-Image-2.1 specifics (Modal opt-in)

- **Not step-distilled** -- 40 steps is the model card default. The old 8-step
  default was tuned for 2511's Lightning LoRA, which 2.1 doesn't have here, so expect
  low step counts to cost quality (untested).
- **Sampled without guidance.** `--guidance 1.0` (default) is how the model is meant
  to run. `>1` switches on true CFG (blank negative prompt if you pass none) and
  doubles the cost of every step.
- **Multi-image:** the first `--input` is the image being edited ("image 1"); the
  rest are references in order ("image 2", ...). Up to 10. Output size follows the
  first image's aspect ratio at ~1MP.
- **Local edits:** draw a circle or paint an annotation on the image, or pass a
  separate mask as an extra `--input`, and say what to change there
  (e.g. "Remove the watch inside the red circle").
- **RGBA:** transparent PNG inputs keep their alpha. For a cut-out, prompt
  `"This is an RGBA image with transparency. <subject>. The image has alpha channel
  and the background is transparent."` -- the result comes back as an RGBA PNG only
  when the model actually produced transparency.

## When to Use This Skill

Use when the user wants to:
- Edit/transform photos while preserving identity
- Reframe cropped images (fix cut-off heads, etc.)
- Change clothing, add accessories
- Change pose (arm positions, hand placement)
- Apply style transfers (cyberpunk, anime, oil painting)
- Adjust lighting/color grading
- Add/remove objects
- Character transformations (Bond, Neo, etc.)

## When NOT to Use

- **Background replacement (single image)** - creates cut-out artifacts, halos
- **Face swapping** - cannot preserve identity from reference
- **Outpainting** - can't extend canvas reliably

## Use With Care

- **Multi-image compositing** - CAN work with explicit identity anchors (see examples.md for prompt patterns). Requires describing distinctive features (hair texture/color, ethnicity, outfit) and using guidance ~2.0
- **Camera angle changes** - Inconsistent results. Vertical angles (low/high) work better than rotational (three-quarter view)

## Quick Reference

```bash
# Basic edit
uv run tools/image_edit.py --input photo.jpg --prompt "Add sunglasses"

# With negative prompt (recommended)
uv run tools/image_edit.py --input photo.jpg \
  --prompt "Reframe as portrait with full head visible" \
  --negative "blur, distortion, artifacts"

# Style transfer
uv run tools/image_edit.py --input photo.jpg --style cyberpunk

# Background (use cautiously - often fails)
uv run tools/image_edit.py --input photo.jpg --background office

# Higher quality (RunPod / 2511 -- on Modal / 2.1 the 40-step default already is)
uv run tools/image_edit.py --input photo.jpg --prompt "..." --steps 16 --guidance 3.0 --cloud runpod

# Extract the subject onto a transparent background (Modal / 2.1)
uv run tools/image_edit.py --input product.jpg   --prompt "This is an RGBA image with transparency. The product from the photo. The image has alpha channel and the background is transparent."   --output product_cutout.png

# Multi-image composite (identity-preserving) -- settings tuned on RunPod / 2511
uv run tools/image_edit.py --input person.jpg background.jpg \
  --prompt "The [ethnicity] [gender] with [hair description] from first image is now in [scene] from second image. Same [features], [outfit]." \
  --negative "different ethnicity, different hair color, different face shape, generic stock photo" \
  --steps 16 --guidance 2.0 --cloud runpod

# Multi-image composite on Modal / 2.1 -- up to 10 references, defaults usually suffice
uv run tools/image_edit.py --input person.jpg outfit.jpg shoes.jpg background.jpg \
  --prompt "The person from image 1 wearing the outfit from image 2 and the shoes from image 3, standing in the scene from image 4. Same face and hair."
```

## Key Files

- `prompting.md` - Prompt patterns and structure
- `examples.md` - Good/bad examples from experiments
- `parameters.md` - Tuning steps, guidance, negative prompts

## Tool Location

`tools/image_edit.py` - CLI wrapper for the Modal (`docker/modal-image-edit/`) and RunPod
(`docker/runpod-qwen-edit/`) endpoints

## Related Docs

- `docs/qwen-edit-patterns.md` - Character transformation patterns
- `.ai_dev/qwen-edit-research.md` - Re

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 172a510

Download folder ↗
uv run tools/image_edit.py --input photo.jpg --prompt "Add sunglasses"
uv run tools/image_edit.py --input photo.jpg \
uv run tools/image_edit.py --input photo.jpg --style cyberpunk
uv run tools/image_edit.py --input photo.jpg --background office
uv run tools/image_edit.py --input photo.jpg --prompt "..." --steps 16 --guidance 3.0 --cloud runpod
uv run tools/image_edit.py --input product.jpg   --prompt "This is an RGBA image with transparency. The product from the ph

Commands as the repository documents them: shown, never run by us. Our verdict covers commit 172a5100d7ed only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 172a5100d7ed

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Questions about qwen-edit

What does the qwen-edit skill do?
AI-native video production toolkit for Claude Code
Is qwen-edit safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can qwen-edit access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (172a5100d7ed), read on 2026-10-28. The repository is watched, and a new audit runs when it changes — this is the first audit.

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