Best retrieval-augmented generation skills, page 4

以 digoal/德哥 的第一人称口吻重写一篇文章。流程是：先吃透原文（必要时用 mcpMiniMaxwebsearch 拓展资料库），再用德哥的语气重新讲一遍，输出 markdown 到当前项目的 markdown/ 目录（SVG 图存到 markdown/svg/，文中以 …

digoal/blog

Implements document chunking, embedding generation, vector storage, and retrieval pipelines for Retrieval-Augmented Generation systems.

giuseppe-trisciuoglio/developer-kit

Convex is the backend agents get right on the first try: an all-TypeScript reactive platform where the database, server functions, scheduling, file storage, auth, and realtime sync are one type-safe…

openclaw/clawhub

Hunt vector-store / embedding-layer weaknesses in RAG pipelines (OWASP LLM08 Vector and Embedding Weaknesses) — persistent corpus poisoning that survives across sessions and users (distinct from…

elementalsouls/Claude-BugHunter

Black-box security audit of a DEPLOYED AI agent (not the MCP server behind it) — tool-call hijacking, cross-session memory poisoning, confused-deputy via connected tools, agent-to-agent IDOR…

awarexone/Agentic-Bug-Hunter

用 MinerU 将复杂PDF文档转换为LLM友好的Markdown/JSON格式。适用于：(1) PDF转Markdown/JSON，(2) 提取PDF中的文本、表格、公式、图像，(3) 解析学术论文、技术文档、商业报告，(4) 为RAG应用准备文档数据，(5) 批量处理PDF。触发关键词："PDF解析"、"PDF转Markdown"、"提取PDF表格/公式"、"MinerU"、"parse…

staruhub/ClaudeSkills

Vector database expert for embeddings, similarity search, RAG patterns, and indexing strategies

RightNow-AI/openfang

Rerank retrieved passages by whether each one answers the question, drop the near-misses before they reach the prompt, and check every citation in the answer against the passage it points at.

mrmps/classifier-dev

Use Bright Data's Discover API — intent-ranked, AI-relevance-scored web search at scale (not keyword SERP).

brightdata/skills

Design composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by xAI's open-sourced For You algorithm.

affaan-m/ECC

Monitor and evaluate RAG systems with retrieval quality metrics, groundedness checks, hallucination detection, and continuous regression testing.

sickn33/agentic-awesome-skills

Evaluate retrieval and citation behavior for RAG pipelines from deterministic JSONL fixtures.

davepoon/buildwithclaude

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

davila7/claude-code-templates

This skill should be used when a learner wants to navigate or understand the Build-an-Agent workshop as a whole — e.g.

brevdev/workshop-build-an-agent

For any security-related task — threat triage, incident response, MITRE ATT&CK mapping, CVE lookup, exploit analysis, defensive control validation, red/blue/purple team work — always consult the…

lyonzin/knowledge-rag

Train or fine-tune SentenceTransformer, CrossEncoder, and SparseEncoder models for retrieval, similarity, clustering, classification, reranking, and related embedding tasks.

sickn33/agentic-awesome-skills

Semantic + full-text search over documents and the web via basemind's RAG store — PDFs, Office, HTML, email, images (OCR), plus scraped/crawled web pages, with cross-encoder reranking, keyword and…

Goldziher/basemind

Oracle Cloud Infrastructure guidance for designing, operating, and troubleshooting OCI services, including OCI Kubernetes Engine (OKE), OCI Internet of Things Platform, OCI Functions deployment and…

oracle/skills

Optimizing vector embeddings for RAG systems through model selection, chunking strategies, caching, and performance tuning.

ancoleman/ai-design-components

Evaluate LLM systems using automated metrics, LLM-as-judge, and benchmarks.

ancoleman/ai-design-components

AI agent and LLM system engineering reference covering single-agent dev (ReAct, tool calling, plan-execute), multi-agent coordination (swarm, role decomposition, file locking), LLM security (prompt…

telagod/code-abyss

Add an AI agent / RAG backend (@convex-dev/agent) to the Convex app.

openclaw/clawhub

Search the Genie Sim asset library by natural-language keyword via the generator's searchassets MCP tool (RAG over ASSETSINDEX), and look up asset interaction metadata via getinteractions.

AgibotTech/genie_sim

A skill your agent uses when a medical AI paper should be found and cited by AI search engines and RAG tools.

Aperivue/medsci-skills

Only reach for external web search when the local corpus comes back empty or clearly insufficient.

lyonzin/knowledge-rag

A skill your agent uses when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages…

alirezarezvani/claude-skills

A skill your agent uses when managing prompts in production at scale: versioning prompts, running A/B tests on prompts, building prompt registries, preventing prompt regressions, or creating eval…

alirezarezvani/claude-skills

A skill your agent uses for Azure AI: Search, Speech, OpenAI, Document Intelligence.

microsoft/GitHub-Copilot-for-Azure

当系统提示需要设计引用格式、信息溯源机制、来源标注系统时调用。适用于文档问答、搜索增强生成（RAG）、代码引用、浏览器辅助等需要让用户追溯信息来源的场景。不适用于纯创作类输出（如故事、诗歌），不适用于无需溯源的常识问答，也不适用于注入防御（虽然两者都涉及内容可信度）。

kangarooking/system-prompt-skills

Build production-ready LLM applications, advanced RAG systems, and intelligent agents.

curiositech/some_claude_skills

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration.

aiskillstore/marketplace

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying.

aiskillstore/marketplace

Probes Retrieval-Augmented Generation pipelines for indirect prompt injection via poisoned retrieved documents and embedding-space manipulation, using NVIDIA garak, Promptfoo red-team plugins, and…

mukul975/Anthropic-Cybersecurity-Skills

Build RAG (Retrieval Augmented Generation) pipelines with web search and LLMs.

NeverSight/learn-skills.dev

A skill your agent uses when the user wants to build an evaluation system for an LLM/agent application but doesn't know where to start — they have traces, prompts, RAG pipelines, or nothing at all.

agentscope-ai/OpenJudge

Guides Qdrant search strategy selection. An agent skill from github/awesome-copilot.

github/awesome-copilot

Perform finance web searches and local context searches. An agent skill from ninehills/skills.

ninehills/skills

Build a RAG (retrieval-augmented generation) pipeline or a custom search engine on top of Bright Data's Discover API — using intent-ranked web results + parsed page content as the…

brightdata/skills

Retrieval-Augmented Generation patterns including chunking, embeddings, vector stores, and retrieval optimization Use when: rag, retrieval augmented, vector search, embeddings, semantic search.

davila7/claude-code-templates

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models.

microsoft/ai-agents-for-beginners

Build local-first AI agents wey dey run fully for developer workstation wit Microsoft Foundry Local and Qwen function-calling models.

microsoft/ai-agents-for-beginners

Assess and harden LLM applications and agentic systems against prompt injection, tool misuse, excessive agency, memory poisoning, RAG data leakage, and model supply-chain risk, mapped to the OWASP…

trilwu/secskills

使用 ACEHarness 内置 RAG/LanceDB 知识库进行只读检索。

TheAceTeam/AceHarness

Hunt vector-store / embedding-layer weaknesses in RAG pipelines (OWASP LLM08 Vector and Embedding Weaknesses)

sickn33/agentic-awesome-skills

Build and operate Retrieval-Augmented Generation (RAG) infrastructure with vector stores, embedding pipelines, and hybrid search.

sickn33/agentic-awesome-skills

A skill your agent uses when working with OpenSearch vector search edition via the Python SDK (ha3engine) to push documents and run HA/SQL searches.

cinience/alicloud-skills

Build production Firebase Genkit applications including RAG systems, multi-step flows, and tool calling for Node.js/Python/Go.

jeremylongshore/tons-of-skills-marketplace

Choose and wire AI features in the .NET backend — LLM calls, agentic tool-calling/multi-step workflows, RAG/vector search, structured output, streaming.

atherio-danp/cde-dotnetcc