OpenRLHF is a Ray-based RLHF framework optimized for distributed training with vLLM inference acceleration.
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 davila7/claude-code-templates --skill openrlhf-trainingCompatible with
Supported agents
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionopenrlhf-trainingExecute the skills CLI command in your project's root directory to begin installation:
epx add davila7/claude-code-templates --skill openrlhf-trainingFetches openrlhf-training 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/openrlhf-training
Restart Cursor to activate openrlhf-training. Access via /openrlhf-trainingin 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.
backend-to-frontend-handoff-docs
davila7/claude-code-templates · Frontend · same repo
idor-vulnerability-testing
davila7/claude-code-templates · Testing · same repo
inngest
davila7/claude-code-templates · Productivity · same repo
domain-hunter
resciencelab/opc-skills · AI/ML · same category
bullmq-specialist
sickn33/antigravity-awesome-skills · AI/ML · same category
blockchain-developer
sickn33/antigravity-awesome-skills · AI/ML · same category
Keeps context tight: openrlhf-training is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend openrlhf-training for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
openrlhf-training fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
openrlhf-training is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
I recommend openrlhf-training for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
openrlhf-training fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added openrlhf-training from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: openrlhf-training is focused, and the summary matches what you get after install.
Useful defaults in openrlhf-training — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added openrlhf-training from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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