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0dc5423877 |
@@ -2,9 +2,9 @@
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title: "Awesome AI Agents 2026"
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task: ""
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lineage_type: import
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upstream_source: https://github.com/ARUNAGIRINATHAN-K/awesome-ai-agents-2026/blob/d5e51cbb/README.md
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upstream_sha: d5e51cbb
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imported_at: 2026-07-11
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upstream_source: https://github.com/ARUNAGIRINATHAN-K/awesome-ai-agents-2026/blob/91ecee02/README.md
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upstream_sha: 91ecee02
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imported_at: 2026-07-13
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prompt_class: catalogue
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upstream_changes: accepted
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author: upstream
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@@ -227,6 +227,7 @@ The protocol layer that enables agents to discover tools, communicate with each
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Sandboxes, web scrapers, browser automation, and networking layers that agents depend on.
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- [Agent Bounties](https://github.com/NSPG13/agent-bounties) `π¬` `[Rust]` `[MCP]` - Coordinates verifiable digital bounty workflows designed for agents to post, fund, claim, solve, verify, and earn.
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- [AgentDock](https://github.com/agentdock/agentdock) `π` `[Python]` `[Docker]` - Framework for building and deploying production-ready AI agents with composable node architecture.
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- [Agent Starter](https://github.com/raintree-technology/agent-starter) `π±` `[TypeScript]` `[MCP]` - Project-local config manager that syncs one `agent.json` manifest into Claude Code, Codex, Cursor, and MCP setup while preserving manual edits and detecting drift.
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- [codex-profiles](https://github.com/Ducksss/codex-profiles) `π` `[Python]` `[OpenAI]` - Bash CLI for switching OpenAI Codex CLI and Desktop profiles with isolated CODEX_HOME directories.
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@@ -399,6 +400,7 @@ Curated list of vertical agent solutions for finance, healthcare, legal, manufac
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- [Building Effective Agents](https://www.anthropic.com/engineering/building-effective-agents) `π` `[Python]` `[Anthropic]` - Anthropic's guide on agent design patterns, evaluation strategies, and production best practices.
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- [Hugging Face Agents Course](https://huggingface.co/learn/agents-course/unit0/introduction) `π` `[Python]` `[Multi-Agent]` - Open-source course on building AI agents using Hugging Face tools and models.
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- [Implicit Behavioral Alignment of Language Agents in High-Stakes Crowd Simulations](https://arxiv.org/abs/2509.16457) `π±` `[Python]` `[Benchmark]` - EMNLP 2025 paper introducing PersonaEvolve, an LLM-based optimizer that refines agent personas so crowds of LLM agents behave realistically against expert benchmarks.
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- [Jailbreaking LLMs' Safeguard with Universal Magic Words for Text Embedding Models](https://arxiv.org/abs/2501.18280) `π¬` `[Python]` `[Paper]` - Universal suffix that manipulates text-embedding similarity to bypass safety guardrails across ChatGPT, DeepSeek, and Qwen.
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- [LATS: Language Agent Tree Search](https://github.com/lapisrocks/LanguageAgentTreeSearch) `π±` `[Python]` `[Paper]` - Combines Monte Carlo tree search with LLM reasoning for complex multi-step planning tasks.
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- [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) `π±` `[Python]` `[Multi-Agent]` - Deep breakdown of LLM-powered agent components: planning, memory, and tool use.
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- [Microsoft GenAI for Beginners](https://github.com/microsoft/generative-ai-for-beginners) `π` `[Python]` `[Microsoft]` - A 21-lesson course on generative AI concepts and agent development from Microsoft.
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@@ -611,6 +613,7 @@ AI platforms that conduct autonomous multi-step research, synthesize findings fr
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| Gemini Research | 1M tokens | Google Search + KG |
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| Perplexity Pro | Variable | Real-time cited search |
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- [Agon](https://github.com/AutoResearch-Factory/Agon) `π¬` `[Python]` `[Multi-Agent]` - Omnidisciplinary autonomous research system that replaces one-off prompts with Prompt Economy's reusable loops.
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- [CAJAL](https://github.com/Agnuxo1/CAJAL) `π±` `[Python]` `[Local]` - Local AI agent that generates publication-ready IMRaD scientific papers with verified arXiv citations and AI tribunal scoring.
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- [ChatGPT Deep Research](https://openai.com/index/introducing-deep-research) `π` `[Cloud]` `[OpenAI]` - Conducts extended reasoning with web browsing to produce structured research reports with Canvas output.
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- [Claude Deep Research](https://www.anthropic.com/research) `π` `[Cloud]` `[Anthropic]` - Performs multi-step investigation with verified source citations and 200K token context window.
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