AI-powered image editing using Qwen-Image-Edit-2511 via RunPod serverless.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionqwen-editExecute the skills CLI command in your project's root directory to begin installation:
Fetches qwen-edit from digitalsamba/claude-code-video-toolkit and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate qwen-edit. Access via /qwen-edit in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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AI-powered image editing using Qwen-Image-Edit-2511 via RunPod serverless.
Status: Evolving - learnings being captured as we experiment
Use when the user wants to:
# 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
prompting.md - Prompt patterns and structureexamples.md - Good/bad examples from experimentsparameters.md - Tuning steps, guidance, negative promptstools/image_edit.py - CLI wrapper for RunPod endpoint
docs/qwen-edit-patterns.md - Character transformation patterns.ai_dev/qwen-edit-research.md - Research notesMake data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
Useful defaults in qwen-edit — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
qwen-edit reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend qwen-edit for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
qwen-edit reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend qwen-edit for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: qwen-edit is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for qwen-edit matched our evaluation — installs cleanly and behaves as described in the markdown.
I recommend qwen-edit for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
qwen-edit reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in qwen-edit — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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