Production-grade LLM applications, RAG systems, and intelligent agent architectures for enterprise AI.
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 sickn33/antigravity-awesome-skills --skill ai-engineerCompatible with
Supported agents
Supports major LLM providers (OpenAI, Anthropic, open-source models) with multi-model orchestration, function calling, and structured outputs
Advanced RAG capabilities including vector databases, hybrid search, reranking, query understanding, and patterns like GraphRAG and self-RAG
Agent frameworks (LangChain, LlamaIndex, CrewAI, AutoGen) with memory systems, tool integration, and m
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionai-engineerExecute the skills CLI command in your project's root directory to begin installation:
epx add sickn33/antigravity-awesome-skills --skill ai-engineerFetches ai-engineer from sickn33/antigravity-awesome-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/ai-engineer
Restart Cursor to activate ai-engineer. Access via /ai-engineerin 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.
bullmq-specialist
sickn33/antigravity-awesome-skills · AI/ML · same repo
laravel-expert
sickn33/antigravity-awesome-skills · Productivity · same repo
laravel-security-audit
sickn33/antigravity-awesome-skills · Productivity · same repo
react-native-architecture
sickn33/antigravity-awesome-skills · Frontend · same repo
game-development
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code-review-excellence
sickn33/antigravity-awesome-skills · Productivity · same repo
Useful defaults in ai-engineer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
ai-engineer is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added ai-engineer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
ai-engineer has been reliable in day-to-day use. Documentation quality is above average for community skills.
ai-engineer fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for ai-engineer matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: ai-engineer is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend ai-engineer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for ai-engineer matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in ai-engineer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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