Cohort of 208 admitted agents tagged capability:rag. Composite below is the cohort's average AgentScore.
| Cmp | Rank | Agent | 24h | Score | Δ24h | Watch |
|---|---|---|---|---|---|---|
| #1 | open-webui mcp-serveropen-webui: User-friendly AI Interface (Supports Ollama, OpenAI API, ...) | 1 | 58.5 | 0.00 | ||
| #3 | dify mcp-serverdify: Production-ready platform for agentic workflow development. | 1 | 55.0 | -1.05 | ||
| #8 | Flowise Flowise: Build AI Agents, Visually. | 1 | 53.7 | 0.00 | ||
| #12 | graphify apache-2.0mcp-servergraphify: Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store. | 1 | 53.0 | +0.01 | ||
| #18 | ruflo mitmcp-serverruflo: 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and man... | 50.9 | -0.09 | |||
| #19 | MinerU MinerU: Transforms complex documents like PDFs and Office docs into LLM-ready markdown/JSON for your Agentic workflows. | 1 | 50.7 | -0.15 | ||
| #29 | ragflow apache-2.0ragflow: RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs. | 3 | 49.2 | +0.00 | ||
| #40 | awesome-llm-apps apache-2.0awesome-llm-apps: 100+ AI Agent & RAG apps you can actually run ??? clone, customize, ship. | 8 | 48.1 | +0.67 | ||
| #47 | ai-agents-for-beginners mitlibraryai-agents-for-beginners: 18 Lessons to Get Started Building AI Agents. | 13 | 47.7 | -1.49 | ||
| #57 | anything-llm mitsaasanything-llm: Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience | 1 | 45.7 | +0.05 | ||
| #69 | WrenAI cliWrenAI: GenBI (Generative BI) for AI agents, an open-source, governed text-to-SQL through an open context layer that turns natural-language questions into trusted dashboards, charts, and SQL across 20+ data sources, such as BigQuery, Snowflake, PostgreSQL, ClickHouse, Amazon Redshift,... | 2 | 44.1 | -0.19 | ||
| #74 | giskard-oss apache-2.0librarygiskard-oss: 🐢 Open-Source Evaluation & Testing library for LLM Agents. | 43.4 | 0.00 | |||
| #78 | GenAI_Agents GenAI_Agents: 50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems. | 42.9 | +0.00 | |||
| #98 | langchain mitlibrarylangchain: The agent engineering platform. | 18 | 41.2 | +1.75 | ||
| #110 | awesome-LLM-resources apache-2.0mcp-serverawesome-LLM-resources: ??????????? ??????????????????LLM?????????????????????????????????Agent??????????????????AI??????????????????????????????????????????????????????o1 ?????????MCP?????????????????????????????????????????? | Summary of the world's best LLM resources. | 291 | 40.5 | +11.49 | ||
| #147 | MiniMax: MiniMax M1 saasMiniMax: MiniMax M1: MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it... | 8 | 40.2 | -0.55 | ||
| #116 | ai-agent-book apache-2.0mcp-serverai-agent-book: 《深入理解 AI Agent：设计原理与工程实践》（李博杰 著）开源主仓库：全书正文、编译版 PDF 与按章配套代码. | 64 | 39.9 | +4.55 | ||
| #127 | langroid mitlibrarylangroid: Harness LLMs with Multi-Agent Programming. | 12 | 38.7 | +1.22 | ||
| #136 | AgentGuide ide-pluginAgentGuide: https://adongwanai.github.io/AgentGuide | AI Agent开发指南 | LangGraph实战 | 高级RAG | 转行大模型 | 大模型面试 | 算法工程师 | 面试题库 | 强化学习｜数据合成 | 3 | 37.8 | +0.01 | ||
| #139 | llm_wiki mitllm_wiki: LLM Wiki is a cross-platform desktop application that turns your documents into an organized, interlinked knowledge base — automatically. Instead of traditional RAG (retrieve-and-answer from scratch every time), the LLM incrementally builds and maintains a persistent wiki from... | 4 | 37.8 | +0.12 | ||
| #163 | LiquidAI: LFM2.5-2.6B saasLiquidAI: LFM2.5-2.6B: LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or... | 7 | 36.8 | +0.88 | ||
| #155 | claude-mem apache-2.0claude-mem: A Claude Code plugin that automatically captures everything Claude does during your coding sessions, compresses it with AI (using Claude's agent-sdk), and injects relevant context back into future sessions. | 5 | 36.8 | -0.05 | ||
| #190 | second-brain-cloudflare mitmcp-serversecond-brain-cloudflare: A personal memory layer for AI tools. Self-hosted MCP server on Cloudflare Workers with semantic search — works with Claude Desktop, Claude Code, and claude.ai. | 15 | 35.1 | -0.40 | ||
| #193 | vibekit vibekit: Run Claude Code, Gemini, Codex — or any coding agent — in a clean, isolated sandbox with sensitive data redaction and observability baked in. | 2 | 34.8 | 0.00 | ||
| #201 | awesome-architecture mitawesome-architecture: 🗺️ Think like a software architect, not just a coder — 21 architecture maps (incl. AI gateway, RAG, agents, inference serving, vector DB) + a language-agnostic system-design tutorial. Every template links to real open-source prototypes. 中英文双语。 | 34.6 | +0.00 | |||
| #209 | Awesome-LLM-Long-Context-Modeling mitAwesome-LLM-Long-Context-Modeling: 📰 Must-read papers and blogs on LLM based Long Context Modeling 🔥. | 3 | 34.4 | 0.00 | ||
| #216 | PageIndex mitPageIndex: 📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG. | 2 | 34.1 | +0.01 | ||
| #237 | files-sdk mitfiles-sdk: A unified storage SDK for object and blob backends. One small, honest API. Web-standards I/O. | 4 | 33.5 | +0.00 | ||
| #247 | mirage apache-2.0mirage: A Unified Virtual Filesystem For AI Agents. | 4 | 33.1 | +0.01 | ||
| #253 | HKUDS/VideoAgent ide-pluginHKUDS/VideoAgent: Video editing has become essential in digital media creation, yet existing automated systems are restricted to short segment processing and domain-specific tasks. They face two critical limitations: i) inability to handle diverse video comprehension and editing operations, and... | 2 | 32.7 | +0.04 | ||
| #348 | jevgrep mitclijevgrep: Jev-powered semantic code search for coding agents — find behavior across repositories via CLI or MCP, with exact source excerpts and line numbers. | 55 | 30.3 | +1.30 | ||
| #357 | InternScience/MLEvolve libraryInternScience/MLEvolve: Large language model (LLM) agents are increasingly applied to long-horizon tasks such as scientific discovery and machine learning engineering (MLE), where sustained self-evolution becomes a key capability. However, existing MLE agents suffer from inter-branch information isol... | 8 | 30.0 | +0.02 | ||
| #381 | ai-system-design apache-2.0ai-system-design: AI System Design - Learn how to design AI systems built on LLMs, RAG, and AI Agents step by step. | 6 | 29.5 | +0.03 | ||
| #403 | ComfyUI-Copilot mitide-pluginComfyUI-Copilot: An AI-powered custom node for ComfyUI designed to enhance workflow automation and provide intelligent assistance. | 6 | 29.0 | 0.00 | ||
| #422 | PocketFlow mitlibraryPocketFlow: Pocket Flow: 100-line LLM framework. Let Agents build Agents! | 6 | 28.8 | +0.00 | ||
| #424 | ai-engineering-course apache-2.0ai-engineering-course: AI Engineering Course - A free and complete AI Engineering Course to learn AI Engineering step by step - from Machine Learning, Neural Networks, and Transformers to LLMs, Fine-Tuning, RAG, AI Agents, LLM Inference, Evaluation, AI Safety, and AI System Design. | 6 | 28.7 | +0.22 | ||
| #429 | Alibaba-NLP/qqr ide-pluginAlibaba-NLP/qqr: Reinforcement learning (RL) has emerged as a key paradigm for improving large language model (LLM) agents, enabling stronger reasoning, planning, and tool-use in interactive environments. However, existing agent RL methods remain fundamentally constrained by an on-policy reaso... | 5 | 28.6 | 0.00 | ||
| #466 | cs329z-chinese ide-plugincs329z-chinese: Stanford CS329Z Engineering AI Agents 中文教程：19 讲与 4 项实践，涵盖 LLM、RAG、工具调用、Agent 记忆、多智能体、评测与安全。完整 Markdown 和在线/离线 HTML。Chinese course notes and hands-on guide. | 29 | 28.0 | -0.35 | ||
| #475 | agent-study mitmcp-serveragent-study: 28章AI Agent全栈课程：从ReAct循环到Claude Code逆向、MCP/A2A协议、RAG、DSPy、生产可观测性——全部为可运行Python文件，面试导向。. | 10 | 27.9 | +0.05 | ||
| #260 | Cohere: Command R7B (12-2024) saasCohere: Command R7B (12-2024): Command R7B (12-2024) is a small, fast update of the Command R+ model, delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning... | 8 | 27.8 | -0.55 | ||
| #271 | Z.ai: GLM 4.5 saasZ.ai: GLM 4.5: GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications. It leverages a Mixture-of-Experts (MoE) architecture and supports a context length of up to 128k tokens. GLM-4.5 delivers significantly... | 1 | 27.1 | -0.01 | ||
| #574 | machine-learning-library librarymachine-learning-library: A hand-curated library of the best machine learning education — 590 docs (78 arXiv papers, 474 course lectures from Stanford/MIT/Karpathy/fast.ai, 38 explainer articles), normalized to Markdown with full provenance. A clean ML corpus/dataset for learning, RAG, and fine-tuning. | 1 | 26.7 | +0.07 | ||
| #628 | electric-dragon-80000v/pi-cowboy electric-dragon-80000v/pi-cowboy: discovered AI agent. | 84 | 26.1 | -0.86 | ||
| #634 | thu-nics/AKV ide-pluginthu-nics/AKV: Large Language Model (LLM) agents can handle increasingly complex tasks, navigating long trajectories of observations and actions. As these trajectories grow, key-value (KV) cache I/O and storage become the dominant cost. Trajectories can also exceed the LLM's maximum context... | 17 | 26.1 | +0.27 | ||
| #652 | AgentR1/Claw-R1 ide-pluginAgentR1/Claw-R1: Agentic reinforcement learning (RL) has become an important post-training paradigm for turning LLMs from static chatbots into interactive agents, giving rise to representative applications such as OpenClaw. Existing work mainly focuses on policy optimization algorithms and tra... | 20 | 26.0 | 0.00 | ||
| #682 | OpenDataBox/MemoryData ide-pluginOpenDataBox/MemoryData: Memory for large language model (LLM) agents has rapidly evolved from simple retrieval-augmented mechanisms into a data management system that supports persistent information storage, retrieval, update, consolidation, and dynamic lifecycle governance throughout agent execution... | 18 | 25.7 | +0.04 | ||
| #689 | opendilab/LightZero ide-pluginopendilab/LightZero: Leveraging the rich world knowledge of Large Language Models (LLMs) to enhance Reinforcement Learning (RL) agents offers a promising path toward general intelligence. However, a fundamental prior-dynamics mismatch hinders existing approaches: static LLM knowledge cannot direct... | 21 | 25.6 | -0.00 | ||
| #690 | graphmemory mitgraphmemory: Bitemporal AI memory system: six-variable decay, time-graded recall, TTL expiry, dedupe, competitive retrieval (Neo4j + PostgreSQL + Redis). | 156 | 25.6 | -1.44 | ||
| #310 | Qwen: Qwen3 Max saasQwen: Qwen3 Max: Qwen3-Max is an updated release built on the Qwen3 series, offering major improvements in reasoning, instruction following, multilingual support, and long-tail knowledge coverage compared to the January 2025 version. It... | 2 | 25.5 | +0.00 | ||
| #727 | generative-ai mitmcp-servergenerative-ai: Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation. | 6 | 25.3 | +0.16 | ||
| #750 | ai-roadmap-2026 ai-roadmap-2026: AI Roadmap 2026: a beginner's path through Foundations, LLM Engineering, Agents, Evaluation, and Production, with verified free resources and a mini-project per layer. | 25 | 25.1 | 0.00 | ||
| #775 | mirage-engine mitmirage-engine: A code-only world engine for AI agents: build whole towns and landscapes in three.js as code (pre-alpha) | 88 | 24.9 | +0.97 | ||
| #813 | best-agent-memory-mcp mcp-serverbest-agent-memory-mcp: Best Agent Memory MCP servers, ranked and compared: long-term memory for Claude Code, Codex, Cursor and any MCP client. Glen, Mem0, Supermemory, Zep, Hindsight, Basic Memory, claude-mem, Graphiti, Cognee, the official memory server and more, with storage, capture model, team s... | 20 | 24.6 | +0.02 | ||
| #831 | PRISM mitide-pluginPRISM: A training-free, retrieval-side memory framework for long-horizon LLM agents — high accuracy at an order-of-magnitude smaller context budget. | 17 | 24.3 | 0.00 | ||
| #866 | awesome-agent-skill mitmcp-serverawesome-agent-skill: Curated skill pack for LLM agents in data science and machine learning (Cursor & Claude ready). | 34 | 24.0 | -0.19 | ||
| #873 | skills-comm apache-2.0skills-comm: Neuroimaging community skills repo - making LLMs leverage neuroimaging tools more effectively. | 9 | 23.9 | 0.00 | ||
| #875 | alem-world/alem-env ide-pluginalem-world/alem-env: As language models are increasingly deployed as autonomous agents, they must coordinate with others over long horizons in open-ended interactive tasks. Yet existing evaluations rarely test these demands together, instead emphasising single-agent tasks, short interactions, or h... | 20 | 23.9 | -0.06 | ||
| #886 | Wang-ML-Lab/OrchRM ide-pluginWang-ML-Lab/OrchRM: Multi-Agent Systems (MAS) built on Large Language Models (LLMs) require effective orchestration to coordinate specialized agents, yet training such orchestrators is hindered by limited supervision and high computational cost. We propose Orchestration Reward Modeling (OrchRM),... | 9 | 23.8 | 0.00 | ||
| #900 | zjunlp/LightMem ide-pluginzjunlp/LightMem: Existing memory-augmented LLM agents often treat memory as a static repository with pre-defined representations and fixed retrieval pipelines, which is brittle in dynamic agentic environments where feedback, task variation, and heterogeneous signals continuously reshape what s... | 12 | 23.7 | +0.00 | ||
| #913 | dsh-superagent-prototype mitdsh-superagent-prototype: Towards a More Autonomous Agent System. | 110 | 23.6 | +1.04 | ||
| #912 | deepseek-ai/dsh-superagent-prototype deepseek-ai/dsh-superagent-prototype: discovered AI agent. | 110 | 23.6 | +1.04 | ||
| #333 | Relace: Relace Search saasRelace: Relace Search: The relace-search model uses 4-12 `view_file` and `grep` tools in parallel to explore a codebase and return relevant files to the user request. In contrast to RAG, relace-search performs agentic... | 3 | 23.5 | +0.40 | ||
| #932 | lbn187/PokerSkill librarylbn187/PokerSkill: Poker is a landmark challenge for artificial intelligence. The dominant approach relies on equilibrium solvers built on counterfactual regret minimization, requiring millions of core-hours of training. Large Language Models (LLMs) possess extensive poker knowledge but perform... | 11 | 23.5 | 0.00 | ||
| #944 | FERNme mcp-serverFERNme: A lightweight memory engine for AI agents using fuzzy graphs, Hebbian updates, and optional LLM gating. | 10 | 23.3 | 0.00 | ||
| #958 | dual-mem apache-2.0mcp-serverdual-mem: Dual-system layered memory SDK for LLM agents — structured write path, hybrid retrieval, evolution chains. | 60 | 23.2 | -0.39 | ||
| #974 | ai-security-labs ai-security-labs: AI security training: hands-on labs, tools and courses for LLM, RAG and agent security. Maintained by Pwned Labs. | 65 | 23.1 | -0.43 | ||
| #979 | aelfrice mitmcp-serveraelfrice: Bayesian memory that learns from feedback for LLM agents. | 74 | 23.1 | -0.50 | ||
| #988 | awesome-agent-rl-environments awesome-agent-rl-environments: A curated list of training & evaluation environments for LLM/VLM agents (SWE-Gym, GEM, RAGEN, AgentGym, WebArena, OSWorld, ToolBench…). Updated weekly. | 12 | 23.0 | 0.00 | ||
| #999 | JetAstra/MacAgentBench cliJetAstra/MacAgentBench: Computer use agents (CUAs) have advanced rapidly in desktop automation, and a growing number of users deploy CUAs such as OpenClaw on Mac Mini for always-on automation. However, existing benchmarks, including those for macOS, evaluate agents without framework augmentation and... | 12 | 22.9 | 0.00 | ||
| #1013 | AIDAChip-Inc/mem-plus-plus libraryAIDAChip-Inc/mem-plus-plus: Large Language Model (LLM) agents now take part in organizational work, where many authors record decisions across documents over months. Because a revised decision arrives as a new document rather than an edit, answering a question requires knowing which version held at a giv... | 12 | 22.7 | 0.00 | ||
| #1045 | agent-memory apache-2.0libraryagent-memory: Verifiable memory for LLM agents — every recalled claim is HMAC-signed back to its originating trajectory span. | 7 | 22.5 | 0.00 | ||
| #1062 | Hello-Agents Hello-Agents: 🤖 Building AI Agent Systems from Scratch — A comprehensive, practical tutorial from fundamentals to production-grade multi-agent applications. | 9 | 22.3 | 0.00 | ||
| #1071 | Szy5/EoG ide-pluginSzy5/EoG: Knowledge graphs (KGs) provide reliable external knowledge for multi-hop factual reasoning with large language models (LLMs), yet most KGs in real-world domains such as finance and industry lack question--answer (QA) annotations. Without such annotations, existing methods stru... | 10 | 22.3 | 0.00 | ||
| #1069 | RuohLiuq/SRO ide-pluginRuohLiuq/SRO: Automated post-training transforms pre-trained large language models (LLMs) into models capable of handling diverse domains by automatically constructing and optimizing a recipe of coupled decisions over data sources, data processing, cross-domain composition, and training con... | 10 | 22.3 | 0.00 | ||
| #1067 | hjj194/sabench-artifact ide-pluginhjj194/sabench-artifact: Tool-using language model agents are usually evaluated by whether they finish the user's task. That metric misses a common failure: an agent can complete the requested work while also taking an unauthorized side-effecting action, such as writing to the wrong object, expanding... | 10 | 22.3 | 0.00 | ||
| #1078 | astra-ai-automation-agent libraryastra-ai-automation-agent: Playwright Python test framework with an AI agent that generates tests from Jira/Excel tickets using RAG + GPT-4o. | 9 | 22.3 | 0.00 | ||
| #1104 | lamda-bbo/agentic-bbo lamda-bbo/agentic-bbo: Black-box optimization (BBO) arises in many scientific and engineering problems where objective evaluations are expensive and limited. Recent large language model (LLM) agents offer a new way to approach BBO by combining task semantics, computation, optimization tools, and fee... | 9 | 22.1 | 0.00 | ||
| #1114 | prmbiy/ShutdownMod prmbiy/ShutdownMod: Theory and experiments suggest that capable AI agents may resist shutdown. Existing shutdown evaluations are informative but limited in coverage and vulnerable to evaluation awareness. We introduce ShutdownMod, a method that turns any agent trajectory into a shutdown evaluatio... | 5 | 22.0 | 0.00 | ||
| #1117 | agent-dispatcher mitmcp-serveragent-dispatcher: Repository retrieval and context engine for Claude Code and Codex: finds relevant code, reuses project knowledge, and pairs each task with specialist skills and verification. | 3 | 22.0 | +0.08 | ||
| #1119 | fujiwaranoM0kou/OptSkills libraryfujiwaranoM0kou/OptSkills: Leveraging Large Language Models (LLMs) to automatically formulate and solve optimization problems from natural language has emerged as an efficient paradigm for automated optimization. However, existing methods still exhibit limited generalization: they are sensitive to super... | 4 | 22.0 | 0.00 | ||
| #1135 | Julius-Woo/STAR-PolyaMath libraryJulius-Woo/STAR-PolyaMath: Frontier AI models and multi-agent systems have led to significant improvements in mathematical reasoning. However, for problems requiring extended, long-horizon reasoning, existing systems continue to suffer from fundamental reliability issues: hallucination accumulation, mem... | 5 | 21.8 | 0.00 | ||
| #1139 | Telivus-AI Telivus-AI: AI-Powered Health Assessment Platform — LangChain Agents · RAG · DSGVO-Ready · Full-Stack TypeScript/Python. | 1 | 21.7 | 0.00 | ||
| #1146 | provenant mcp-serverprovenant: Wiki-based retrieval for AI coding agents. 65× token reduction, +24pp Coverage@5 on SWE-bench Verified. | 2 | 21.7 | 0.00 | ||
| #1151 | agentic-quantum-computing mitsaasagentic-quantum-computing: End-to-end agentic quantum-ML pipeline: PennyLane GPU quantum-kernel anomaly detection + LangGraph multi-agent system + locally-hosted Qwen3-14B, benchmarked across network-intrusion, LHC physics, and fraud. | 19 | 21.6 | -0.21 | ||
| #1152 | benstaf/ipoagent librarybenstaf/ipoagent: Finance Agent v2 (by Vals AI) has emerged as the reference benchmark for evaluating both Anthropic Claude and OpenAI ChatGPT frontier language models on financial tasks. However, it narrowly deals with periodic reporting from publicly traded companies (SEC 10-K and 10-Q filing... | 3 | 21.6 | 0.00 | ||
| #1162 | DEEP-JLU/MemAdapter ide-pluginDEEP-JLU/MemAdapter: Long-term memory enables LLM-based agents to retain and reuse information across tasks and sessions, supporting personalization and long-horizon interactions. However, persistent memories can also induce sycophancy, causing agents to over-align with users' historical beliefs e... | 5 | 21.5 | 0.00 | ||
| #348 | Perplexity: Sonar Deep Research saasPerplexity: Sonar Deep Research: Sonar Deep Research is a research-focused model designed for multi-step retrieval, synthesis, and reasoning across complex topics. It autonomously searches, reads, and evaluates sources, refining its approach as it gathers... | 21.3 | +0.02 | |||
| #1198 | shidingz/EDV ide-pluginshidingz/EDV: Experience-driven self-evolution is critical for large language model (LLM) agents to improve through open-world interaction. However, existing experience learning methods mostly rely on single-agent loops, where the same agent executes tasks, summarizes outcomes, and determin... | 218 | 21.3 | +1.92 | ||
| #1243 | idiap/dialfork ide-pluginidiap/dialfork: Large language models (LLMs) deployed as conversational agents are increasingly expected to follow procedural logic. While factual hallucination has received extensive attention, a different failure mode has been overlooked: procedural hallucination, in which an agent produces... | 318 | 20.9 | -2.50 | ||
| #1246 | AgenticRAG-Survey libraryAgenticRAG-Survey: Agentic-RAG explores advanced Retrieval-Augmented Generation systems enhanced with AI LLM agents. | 7 | 20.8 | +0.00 | ||
| #1249 | hexstrike_augment mithexstrike_augment: We have optimized HexStrike by adding a skill system and RAG capabilities. It now also supports connecting to models via Ollama. | 7 | 20.8 | 0.00 | ||
| #1259 | riskradar-tracemap-ai mitriskradar-tracemap-ai: AI code review quality gates, coverage gap detection, and requirements traceability skills. | 6 | 20.7 | 0.00 | ||
| #1267 | XMUDeepLIT/SAAS ide-pluginXMUDeepLIT/SAAS: Agentic search enables LLMs to solve complex multi-hop questions through iterative reasoning and external search. Despite the effectiveness, these systems often suffer from a critical limitation in practice: agents fail to recognize their own knowledge boundaries, blindly trig... | 242 | 20.6 | -1.93 | ||
| #1285 | spring-ai-demos mcp-serverspring-ai-demos: Spring AI demos: OpenAI & Ollama chat, RAG with pgvector, image generation, text-to-speech, MCP server/client (Java 25, Spring Boot 4, Spring AI 2). | 20.5 | 0.00 | |||
| #1298 | paper_lens paper_lens: Traditional Chinese reading notes on AI papers — LLM, VLM, contrastive learning, RL, agentic AI, RAG. Each article unpacks a seed paper with its key dependencies, organized around core knowledge points. | 4 | 20.4 | 0.00 | ||
| #1306 | JesseZZZZZ/SpatialScout ide-pluginJesseZZZZZ/SpatialScout: Spatial intelligence requires agents to actively acquire visual evidence and integrate observations into a coherent representation of the three-dimensional world. Yet spatial question answering offers limited evidence of whether models can construct accurate metric maps throug... | 48 | 20.3 | +0.47 | ||
| #1323 | Agent_Memory_Techniques apache-2.0Agent_Memory_Techniques: Agent memory for LLMs: 30 runnable Jupyter notebooks covering conversation buffers, vector stores, knowledge graphs, episodic and semantic memory, MemGPT, Mem0, Letta, Zep, Graphiti, LoCoMo benchmarks, and production patterns. | 15 | 20.2 | +0.01 | ||
| #1327 | CuSO4-Chen/AKBE ide-pluginCuSO4-Chen/AKBE: Agentic reinforcement learning (RL) has proven effective for training LLM-based agents with external tool-use capabilities. However, we identify that agentic RL training induces increasing redundant tool calls and blurs the model's intrinsic knowledge boundary, where the model... | 15 | 20.1 | 0.00 | ||
| #1334 | MiniMax-AI/MSA MiniMax-AI/MSA: Ultra-long-context capability is becoming indispensable for frontier LLMs: agentic workflows, repository-scale code reasoning, and persistent memory all require the model to jointly attend over hundreds of thousands to millions of tokens, yet the quadratic cost of softmax atte... | 152 | 20.1 | +1.26 | ||
| #1341 | intellibricks libraryintellibricks: A developer-first, modern Python (3.13+) framework for building intelligent applications. IntelliBricks simplifies LLM interactions with robust tools like structured outputs, agent customization, RAG integration, and seamless API conversion using FastAPI or Litestar. | 19 | 20.0 | 0.00 |
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