llama-factory▌
davila7/claude-code-templates · updated Apr 8, 2026
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Comprehensive assistance with llama-factory development, generated from official documentation.
Llama-Factory Skill
Comprehensive assistance with llama-factory development, generated from official documentation.
When to Use This Skill
This skill should be triggered when:
- Working with llama-factory
- Asking about llama-factory features or APIs
- Implementing llama-factory solutions
- Debugging llama-factory code
- Learning llama-factory best practices
Quick Reference
Common Patterns
Quick reference patterns will be added as you use the skill.
Reference Files
This skill includes comprehensive documentation in references/:
- _images.md - Images documentation
- advanced.md - Advanced documentation
- getting_started.md - Getting Started documentation
- other.md - Other documentation
Use view to read specific reference files when detailed information is needed.
Working with This Skill
For Beginners
Start with the getting_started or tutorials reference files for foundational concepts.
For Specific Features
Use the appropriate category reference file (api, guides, etc.) for detailed information.
For Code Examples
The quick reference section above contains common patterns extracted from the official docs.
Resources
references/
Organized documentation extracted from official sources. These files contain:
- Detailed explanations
- Code examples with language annotations
- Links to original documentation
- Table of contents for quick navigation
scripts/
Add helper scripts here for common automation tasks.
assets/
Add templates, boilerplate, or example projects here.
Notes
- This skill was automatically generated from official documentation
- Reference files preserve the structure and examples from source docs
- Code examples include language detection for better syntax highlighting
- Quick reference patterns are extracted from common usage examples in the docs
Updating
To refresh this skill with updated documentation:
- Re-run the scraper with the same configuration
- The skill will be rebuilt with the latest information
How to use llama-factory on Cursor
AI-first code editor with Composer
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 llama-factory
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches llama-factory from GitHub repository davila7/claude-code-templates and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate llama-factory. Access the skill through slash commands (e.g., /llama-factory) 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
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★71 reviews- ★★★★★Arya Huang· Dec 28, 2024
I recommend llama-factory for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Shikha Mishra· Dec 24, 2024
We added llama-factory from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Tariq Diallo· Dec 24, 2024
Solid pick for teams standardizing on skills: llama-factory is focused, and the summary matches what you get after install.
- ★★★★★Neel Ndlovu· Dec 12, 2024
Solid pick for teams standardizing on skills: llama-factory is focused, and the summary matches what you get after install.
- ★★★★★Sakshi Patil· Nov 23, 2024
llama-factory fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Meera Harris· Nov 19, 2024
Useful defaults in llama-factory — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Yash Thakker· Nov 15, 2024
llama-factory reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Amina Rahman· Nov 15, 2024
Registry listing for llama-factory matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Zara Thompson· Nov 3, 2024
Registry listing for llama-factory matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Amelia Menon· Oct 22, 2024
Useful defaults in llama-factory — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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