Text-to-image generation and image transformation with Stable Diffusion models via HuggingFace Diffusers.
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
Make 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
Submit your Claude Code skill and start earning
epx add davila7/claude-code-templates --skill stable-diffusion-image-generationCompatible with
Supported agents
Supports multiple generation modes: text-to-image, image-to-image translation, inpainting, outpainting, and ControlNet spatial conditioning for precise control
Compatible with SD 1.5, SDXL, SD 3.0, and Flux models; includes scheduler swapping (Euler, DPM-Solver, LCM) for quality and speed trade-offs
LoRA adapter support for efficient style fine-tuning and multi-adapter compositio
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionstable-diffusion-image-generationExecute the skills CLI command in your project's root directory to begin installation:
epx add davila7/claude-code-templates --skill stable-diffusion-image-generationFetches stable-diffusion-image-generation from davila7/claude-code-templates 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:
.cursor/skills/stable-diffusion-image-generation
Restart Cursor to activate stable-diffusion-image-generation. Access via /stable-diffusion-image-generationin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Time estimate: 30-60 minutes to see productivity improvements
Prerequisites
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.
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stable-diffusion-image-generation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: stable-diffusion-image-generation is focused, and the summary matches what you get after install.
Keeps context tight: stable-diffusion-image-generation is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for stable-diffusion-image-generation matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in stable-diffusion-image-generation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in stable-diffusion-image-generation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: stable-diffusion-image-generation is focused, and the summary matches what you get after install.
stable-diffusion-image-generation has been reliable in day-to-day use. Documentation quality is above average for community skills.
stable-diffusion-image-generation reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend stable-diffusion-image-generation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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