qwen-edit

Q: How do I install qwen-edit?

Run npx skills add https://github.com/digitalsamba/claude-code-video-toolkit --skill qwen-edit in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/qwen-edit/ (personal) or .claude/skills/qwen-edit/ (project).

by digitalsambaMedia & Creative

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.

Installs: 975
Last 24h: +9
Trending rank: #9366
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/digitalsamba/claude-code-video-toolkit --skill qwen-edit

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads qwen-edit automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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

# 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 - Research notes

FAQ

What does the qwen-edit skill do?

How do I install qwen-edit?

Run npx skills add https://github.com/digitalsamba/claude-code-video-toolkit --skill qwen-edit in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/qwen-edit/ (personal) or .claude/skills/qwen-edit/ (project).

Which AI agents can use qwen-edit?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is qwen-edit safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains qwen-edit?

It is published by digitalsamba in digitalsamba/claude-code-video-toolkit. It has 975 recorded installs.