Practical guidance for building effective AI applications using techniques from 60 product leaders and practitioners.
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add refoundai/lenny-skills --skill building-with-llmsCompatible with
Supported agents
Covers core prompting patterns: few-shot examples, decomposition for complex tasks, self-criticism, and context placement for cache efficiency
Emphasizes architecture decisions over prompt tuning: context engineering, RAG data preparation, layered model supervision, and specialized models for specific tasks
Provides evaluation frameworks: mandatory evals with binary P
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionbuilding-with-llmsExecute the skills CLI command in your project's root directory to begin installation:
epx add refoundai/lenny-skills --skill building-with-llmsFetches building-with-llms from refoundai/lenny-skills 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/building-with-llms
Restart Cursor to activate building-with-llms. Access via /building-with-llmsin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Useful defaults in building-with-llms — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
building-with-llms has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added building-with-llms from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend building-with-llms for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
building-with-llms is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
building-with-llms reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend building-with-llms for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: building-with-llms is the kind of skill you can hand to a new teammate without a long onboarding doc.
building-with-llms has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend building-with-llms for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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