qwen-edit

digitalsamba/claude-code-video-toolkit · updated Apr 8, 2026

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

AI-powered image editing using Qwen-Image-Edit-2511 via RunPod serverless.

skill.md

Qwen-Image-Edit Skill

AI-powered image editing using Qwen-Image-Edit-2511 via RunPod serverless.

Status: Evolving - learnings being captured as we experiment

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
python tools/image_edit.py --input photo.jpg --prompt "Add sunglasses"

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

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

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

# Higher quality
python tools/image_edit.py --input photo.jpg --prompt "..." --steps 16 --guidance 3.0

# Multi-image composite (identity-preserving)
python 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

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 RunPod endpoint

Related Docs

  • docs/qwen-edit-patterns.md - Character transformation patterns
  • .ai_dev/qwen-edit-research.md - Research notes
how to use qwen-edit

How to use qwen-edit on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add qwen-edit
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

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

The skills CLI fetches qwen-edit from GitHub repository digitalsamba/claude-code-video-toolkit and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/qwen-edit

Reload or restart Cursor to activate qwen-edit. Access the skill through slash commands (e.g., /qwen-edit) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.648 reviews
  • Liam Sethi· Dec 20, 2024

    Useful defaults in qwen-edit — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Chaitanya Patil· Dec 16, 2024

    qwen-edit reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Chinedu Patel· Dec 16, 2024

    I recommend qwen-edit for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Min Martinez· Dec 8, 2024

    qwen-edit reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Liam Reddy· Nov 27, 2024

    I recommend qwen-edit for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Hana Mensah· Nov 27, 2024

    Keeps context tight: qwen-edit is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Olivia Bansal· Nov 11, 2024

    Registry listing for qwen-edit matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Piyush G· Nov 7, 2024

    I recommend qwen-edit for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Soo Sethi· Nov 7, 2024

    qwen-edit reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Shikha Mishra· Oct 26, 2024

    Useful defaults in qwen-edit — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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