Plugins
6 plugins@lucassantana-dev
Rag
Rag from LucasSantana-Dev/forgekit.
2 skills · plugin
curated
Research Papers for RAG
Gather and structure scientific papers for RAG ingestion using Semantic Scholar and BGPT.
9 skills · plugin
curated
Google RAG Platform
For developers using Google's Agent Platform to build RAG applications with Gemini and managed corpora.
4 skills · plugin
curated
Build RAG Pipeline with Pinecone
Build a production RAG pipeline and persistent agent memory using Pinecone as the vector database backend.
6 skills · plugin
@dotnet
Dotnet AI
AI and ML skills for .NET: technology selection, LLM integration, agentic workflows, RAG pipelines, MCP, and classic ML with ML.NET.
5 skills · plugin
@alirezarezvani
Engineering
37 advanced engineering skills: agent designer, agent workflow designer, RAG architect, database designer + schema designer + SQL assistant, migration architect, observability designer, dependency auditor, changelog generator (with semantic version bumper and hotfix/rollback procedures), API design reviewer, API test suite builder, CI/CD pipeline builder, MCP server builder, skill security auditor
33 skills · plugin
Results for “rag”
70 skills
nvidia RAG Eval
Evaluates RAG pipelines using a filesystem-based benchmark with corpus/ and train.json, running evaluate_rag.py to tune retrieval and generation flags and interpret RAGAS metrics.
2.2k · bundle
nvidia RAG Blueprint
Deploy, configure, troubleshoot, and manage NVIDIA RAG Blueprint deployments across Docker, Helm, and library setups.
2.2k · bundle
oyi77 RAG Builder
Designs and implements RAG pipelines, covering document chunking, embedding strategies, hybrid search, answer synthesis with source attribution, and evaluation using RAGAS metrics.
10
github Pinecone RAG
Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend.
36.2k
alirezarezvani RAG Architect
Design, tune, and evaluate production RAG pipelines with deterministic tools for chunking, pipeline design, and retrieval evaluation.
20.4k · bundle
mukul975 Testing Prompt Injection In RAG Pipelines
Probe RAG applications for prompt injection via poisoned retrieved context and embedding manipulation.
24.6k · bundle
More results
joshuashepherd Agent RAG
Build or modify a RAG retrieval pipeline with vector store search, corpus routing, citation rendering, and book fidelity enforcement.
1
nvidia RAG Perf
Run config-driven performance benchmarks against a deployed NVIDIA RAG Blueprint server, including profiling and load testing, with a unified report.
2.2k · bundle
joshuashepherd Build RAG
Builds or modifies a RAG pipeline with intent-based routing, vector store search, citation rendering, and book fidelity enforcement.
1
google Agent Platform RAG Engine Management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK.
14.4k
inference-sh AI RAG Pipeline
Build RAG pipelines that combine web search and LLMs for research, fact-checking, and grounded responses using the inference.sh CLI.
584
jeffallan RAG Architect
Designs and implements production-grade RAG systems by chunking documents, generating embeddings, configuring vector stores, building hybrid search pipelines, applying reranking, and evaluating retrieval quality.
10.4k · bundle
agentskillexchange Llamaindex Agent
Builds RAG and agent applications with LlamaIndex, covering installation, LlamaParse, and LlamaAgents.
28
scoheart Tavily Best Practices
Reference for building Tavily-powered search, extraction, crawling, and research into agentic workflows and RAG systems.
2 · bundle
nimoqup046-collab AI Ml
Orchestrates AI/ML development workflows covering LLM applications, RAG systems, AI agents, ML pipelines, and observability.
2
rootcastleco AI Engineer
Build production-ready LLM applications, RAG systems, and intelligent agents with architecture design, model selection, and cost controls.
6
majiayu000 RAG
Builds Retrieval-Augmented Generation systems with document chunking, embedding generation, vector storage, and retrieval pipelines, including evaluation and optimization.
567 · bundle
lingxling AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
253
kbarbel640-del Ouyang
Builds a local RAG memory system that indexes session logs and notes into ChromaDB for semantic recall across agent restarts.
1 · bundle
jorcan AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
0 · bundle
lucaspmarie-a11y AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
5
phoroth AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
3
antigravity AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines with observability and security.
42.4k
antigravity AI Product
Guides building production-grade AI features with LLM integration patterns, RAG architecture, prompt engineering, and cost optimization.
42.4k
comeonoliver Mvp
Builds a Streamlit and FastAPI RAG application that lets users upload documents and query them with natural language through LM Studio.
61
antigravity AI Engineer
Build production-ready LLM applications, advanced RAG systems, and intelligent agents with vector search, multimodal AI, and enterprise integrations.
42.4k
joshuashepherd Book Chunk
Chunks a book into canonical retrieval units with heading-aware structure splitting, recursive token targets, and contextual prefixes for downstream RAG ingestion.
1
orchestra-research Llamaindex
Connects LLMs with user data for RAG applications, document Q&A, and knowledge retrieval using 300+ data connectors and vector indices.
10.4k · bundle
oyi77 Ruvector
Generates and manages vector embeddings for semantic search and RAG retrieval across knowledge bases, with self-learning capabilities.
10
nimoqup046-collab LLM Ops
Guides production AI systems: RAG pipelines, embeddings, vector databases, fine-tuning, prompt engineering, cost estimation, quality evals, and caching.
2
jorcan LLM Ops
Guides production LLM operations: RAG pipelines, embeddings, vector databases, fine-tuning, prompt engineering, cost estimation, quality evals, and AI architectures.
0 · bundle
orchestra-research Pinecone
Provides code examples and best practices for using Pinecone, a managed vector database for production RAG, recommendation, and semantic search applications.
10.4k · bundle
diegosouzapw N8n
Builds and debugs n8n workflows, covering nodes, RAG with vector stores, the REST API, Code node scripts, expressions, and Docker hosting.
54 · bundle
lucaspmarie-a11y LLM Ops
Provides guidance on production AI operations including RAG pipelines, vector databases, embeddings, fine-tuning, prompt engineering, cost estimation, and quality evaluation.
5
k-dense-ai Liteparse
Parse PDFs, Office files, and images locally with layout-preserved text, bounding boxes, OCR, and page screenshots for RAG and multimodal agents.
30.2k · bundle
lord1egypt Chroma
Store and query embeddings with metadata, vector and full-text search, and filtering. Integrates with LangChain and LlamaIndex for RAG and semantic search applications.
2