rag-engineer
Architect and optimize production-grade RAG systems. Master embedding models, vector databases, chunking strategies, and retrieval pipelines for high-accuracy LLM applications.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
131 skills found
Architect and optimize production-grade RAG systems. Master embedding models, vector databases, chunking strategies, and retrieval pipelines for high-accuracy LLM applications.
A powerful CLI for converting web content and search results into LLM-friendly formats like Markdown, text, or HTML using the Jina AI Reader API.
Comprehensive citation management: search academic databases, extract metadata from DOIs/PMIDs/arXiv, validate references, and generate perfectly formatted BibTeX for scientific manuscripts.
Automated PR lifecycle management: monitors conflicts, resolves CI failures, handles review feedback, and executes squash-merges for safe code integration.
Social media intelligence gathering for TikTok and Instagram. Discover trending hooks, analyze creator strategies, and perform profile data research using the ScrapeCreators API.
Robot perception system design, configuration, and optimization for cameras, LiDAR, and sensor fusion pipelines. Includes camera calibration, 3D reconstruction, and production deployment best practices.
A testing utility designed to simulate prompt injection attacks and validate security scanners for AI agent skills.
Synthesizes multi-agent research findings into coherent, citation-backed reports, resolving contradictions and identifying consensus.
Perform cohort analysis on user engagement data. Identify retention trends, feature adoption rates, churn patterns, and generate actionable research recommendations through quantitative data analysis.
Tools for deploying, managing, and monitoring DataRobot models, including prediction environment configuration, champion/challenger workflows, and deployment operations.
Evidence-first literature collector for automated research pipelines. Scales paper pools to 1200+ with metadata normalization, provenance tracking, and multi-source ingestion.
Conduct systematic literature reviews across PubMed, arXiv, and Semantic Scholar with AI-driven synthesis, verified citations, and mandatory schematic visualization.