Agent skill · Audited from source
qwen-edit
skill · digitalsamba/claude-code-video-toolkitMIT licenceAudited 28 Oct 2026 · source 172a5100d7ed
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,…
Cite
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
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
| Layer | What we check | Result | Findings |
|---|---|---|---|
L0 Provenance | Repo owner, licence, archive status, activity | PASS | 0 |
L1 Static source | Secrets, path traversal, supply chain, hidden code | NA | 0 |
L2 Instructions | Prompt injection, authority framing, hidden directives | PASS | 0 |
L3 Inventory | The files and declarations match the source | PASS | 0 |
L4 Sandbox | Run in isolation and watch behaviour | SKIPPED why | 0 |
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` - ReExcerpt, 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
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
git clone https://github.com/digitalsamba/claude-code-video-toolkit git -C claude-code-video-toolkit checkout 172a5100d7ed
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
- ✓SAFE B 89 / 100
first audit · source
172a5100d7ed
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Sources
- github.com/digitalsamba/claude-code-video-toolkit/tree/main/.cla — the audited source at commit 172a5100d7ed and every finding aboveObserved · 28 Oct 2026
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