ReDel: A Toolkit for LLM-Powered Recursive Multi-Agent Systems
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
Recently, there has been increasing interest in using Large Language Models (LLMs) to construct complex multi-agent systems to perform tasks such as compiling literature reviews, drafting consumer reports, and planning vacations. Many tools and libraries exist for helping create such systems, however none support recursive multi-agent systems -- where the models themselves flexibly decide when to delegate tasks and how to organize their delegation structure. In this work, we introduce ReDel: a toolkit for recursive multi-agent systems that supports custom tool-use, delegation schemes, event-based logging, and interactive replay in an easy-to-use web interface. We show that, using ReDel, we are able to easily identify potential areas of improvements through the visualization and debugging tools. Our code, documentation, and PyPI package are open-source and free to use under the MIT license at https://github.com/zhudotexe/redel.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 12 of its 19 references that are in the map. First posted on arXiv 5 Aug 2024.
Builds on
12 of 19 references.
Closest ancestors · 4
Same direction, newest first
- 2024Symbolic Learning Enables Self-Evolving Agents26 Jun
- 2024EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms20 Jun
- 2024TravelPlanner: A Benchmark for Real-World Planning with Language Agents2 Feb
- 2024Investigate-Consolidate-Exploit: A General Strategy for Inter-Task Agent Self-Evolution25 Jan
Other references · 8
- 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
- 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 1,908
- 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,906
- 2022Decomposed Prompting: A Modular Approach for Solving Complex Taskscited by 554
- 2023ADaPT: As-Needed Decomposition and Planning with Language Modelscited by 172
- 2024AutoAct: Automatic Agent Learning from Scratch for QA via Self-Planningcited by 81
- 2023Recursion of Thought: A Divide-and-Conquer Approach to Multi-Context Reasoning with Language Modelscited by 24
- 2023Kani: A Lightweight and Highly Hackable Framework for Building Language Model Applicationscited by 11
Built on by
Citing papers per year: 2025: 3; 2026: 5.
8 papers.
- 2025Recursive Language Modelscited by 94
- 2025Agentic AI Needs a Systems Theorycited by 19
- 2025Adaptive Graph of Thoughts: Test-Time Adaptive Reasoning Unifying Chain, Tree, and Graph Structurescited by 16
- 2026Recursive Agent Optimizationcited by 4
- 2026Rollout Cards: A Reproducibility Standard for Agent Researchcited by 1
- 2026Code Broker: A Multi-Agent System for Automated Code Quality Assessmentcited by 0
- 2026Agent System Operations: Categorization, Challenges, and Future Directionscited by 0
- 2026LLMs are General Asynchronous Agentscited by 0
- 2026LLMs are General Asynchronous Agents28 Sep 2026
- 2026Agent System Operations: Categorization, Challenges, and Future Directions1 Jun 2026
- 2026Rollout Cards: A Reproducibility Standard for Agent Research12 May 2026
- 2026Recursive Agent Optimization7 May 2026
- 2026Code Broker: A Multi-Agent System for Automated Code Quality Assessment25 Apr 2026
- 2025Recursive Language Models31 Dec 2025
- 2025Agentic AI Needs a Systems Theory28 Feb 2025
- 2025Adaptive Graph of Thoughts: Test-Time Adaptive Reasoning Unifying Chain, Tree, and Graph Structures7 Feb 2025
Similar, not cited
Close in wording, no citation either way
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