| name | awesome-agentic-reasoning |
| description | A curated collection of research papers and resources on agentic reasoning for Large Language Models, organized by planning, tool use, search, self-evolution, and multi-agent systems. |
| triggers | ["show me agentic reasoning papers","find research on LLM planning and reasoning","what are the latest papers on AI agents","I need resources on multi-agent systems","explain agentic reasoning frameworks","find papers on tool use for LLMs","research on self-evolving AI agents","show me embodied agent benchmarks"] |
Awesome Agentic Reasoning
Skill by ara.so — AI Agent Skills collection.
This skill provides expertise in navigating and utilizing the Awesome Agentic Reasoning repository — a comprehensive, curated collection of research papers and resources on agentic reasoning for Large Language Models (LLMs). The repository is based on the survey paper "Agentic Reasoning for Large Language Models: A Survey" and organizes cutting-edge research into foundational reasoning, self-evolving systems, and multi-agent collaboration.
What This Repository Provides
The Awesome Agentic Reasoning repository offers:
- Categorized Research Papers: Organized by thematic areas including planning, tool use, search, self-evolution, multi-agent systems, and real-world applications
- Benchmarks: Comprehensive lists of evaluation frameworks for agentic reasoning capabilities
- Three-Layer Framework:
- Foundational Reasoning: Core single-agent abilities (planning, tool-use, search)
- Self-Evolving Reasoning: Adaptation through feedback, memory, and learning
- Collective Reasoning: Multi-agent coordination and collaborative intelligence
- Application Domains: Math/coding agents, scientific discovery, embodied agents, healthcare, web exploration
- Survey Materials: Slides and the comprehensive survey paper
Repository Structure
Awesome-Agentic-Reasoning/
├── README.md # Main curated list
├── CONTRIBUTING.md # Contribution guidelines
├── materials/ # Survey slides and materials
│ └── Agentic Reasoning Survey Talk.pdf
└── figs/ # Framework diagrams
├── overview.png
└── planning.png
Navigating the Repository
Main Categories
The repository organizes papers into three primary layers:
1. Foundational Agentic Reasoning
Planning Reasoning:
- In-context Planning (workflow design, tree search)
- Post-training Planning (supervised fine-tuning, reinforcement learning)
Tool-Use Optimization:
- In-context Tool-Use (API orchestration, workflow design)
- Post-training Tool-Use (supervised learning, RL fine-tuning)
Agentic Search:
- In-context Search (web navigation, knowledge retrieval)
- Post-training Search (RL optimization)
2. Self-Evolving Agentic Reasoning
- Agentic Feedback Mechanisms: Self-reflection, critique, and iterative refinement
- Agentic Memory: Short-term and long-term memory systems
- Evolving Foundational Capabilities: Continuous improvement of planning, tool-use, and search
3. Collective Multi-Agent Reasoning
- Role Taxonomy: Debate, collaboration, hierarchical structures
- Collaboration Patterns: Division of labor, coordination strategies
- Multi-Agent Memory and Evolution: Shared knowledge, collective learning
Applications
The repository covers real-world applications:
- 💻 Math Exploration & Coding Agents
- 🔬 Scientific Discovery Agents
- 🤖 Embodied Agents
- 🏥 Healthcare & Medicine Agents
- 🌐 Autonomous Web Exploration & Research Agents
Benchmarks
Organized by:
- Core Mechanisms: Tool Use, Search, Memory & Planning, Multi-Agent Systems
- Application Domains: Embodied, Scientific Discovery, Medical, Web, General Tool-Use
Usage Patterns
Finding Papers on Specific Topics
Example 1: Finding Planning Papers
Navigate to the Planning Reasoning section to find papers on:
- Workflow design approaches (ReAct, ReWOO, Plan-and-Solve)
- Tree search methods (Tree of Thoughts, MCTS-based approaches)
- Post-training planning optimization
Example 2: Multi-Agent System Research
The Collective Multi-Agent Reasoning section includes:
- Role specialization papers
- Collaboration frameworks
- Multi-agent memory systems
Exploring Application Domains
Example: Embodied Agent Research
- Check the Applications > Embodied Agents section
- Cross-reference with Benchmarks > Embodied Agents for evaluation frameworks
- Review foundational papers on planning and tool-use that apply to embodied settings
Finding Benchmarks
Example: Evaluating Tool-Use Capabilities
## Tool Use Benchmarks
Navigate to: Benchmarks > Core Mechanisms > Tool Use
Key benchmarks include:
- API-Bank: API selection and execution
- ToolBench: Multi-tool orchestration
- T-Eval: Tool learning evaluation
Contributing to the Repository
Adding New Papers
Create a pull request with papers organized by category:
| [Paper Title](https://arxiv.org/abs/XXXX.XXXXX) | Conference/Year |
Guidelines:
- Place papers in the appropriate thematic section
- Follow the existing table format
- Include the full arXiv link or conference proceedings URL
- Add the publication year or venue
Suggesting Resources
Open an issue to suggest:
- New paper categories
- Additional benchmarks
- Application domains not yet covered
- Survey materials or tutorials
Contact:
Key Research Paradigms
In-Context Reasoning vs. Post-Training Reasoning
The repository distinguishes between two optimization approaches:
In-Context Reasoning:
- Test-time scaling through structured orchestration
- Adaptive workflows without parameter updates
- Examples: ReAct, Tree of Thoughts, Chain-of-Thought prompting
Post-Training Reasoning:
- Behavior optimization via RL and supervised fine-tuning
- Parameter updates to internalize reasoning strategies
- Examples: RLHF for tool-use, Q-learning for planning
Environmental Dynamics
Papers are organized by the environmental setting:
- Static environments: Fixed tool sets, deterministic outcomes
- Dynamic environments: Feedback loops, adaptation requirements
- Multi-agent environments: Coordination, communication, emergent behavior
Working with Survey Materials
Accessing the Survey Paper
The foundational survey is available at:
Using the Slides
Presentation materials are in materials/Agentic Reasoning Survey Talk.pdf:
- Framework overview
- Key insights from each reasoning layer
- Application case studies
- Future research directions
Common Patterns
Building a Research Bibliography
Pattern: Comprehensive Literature Review
categories = [
"Planning Reasoning",
"Tool-Use Optimization",
"Agentic Search",
"Multi-Agent Systems"
]
papers_by_category = {}
for category in categories:
papers = extract_papers_from_section(category)
papers_by_category[category] = papers
Tracking New Research
Pattern: Monitoring Updates
The repository is actively maintained. To stay current:
- Watch the repository for updates
- Check the News section in README for announcements
- Review recent commits for newly added papers
- Subscribe to GitHub notifications
Cross-Referencing Applications and Benchmarks
Pattern: Application-Specific Research
For a specific application domain:
1. Identify application section (e.g., "Healthcare & Medicine Agents")
2. Review papers in that section
3. Navigate to corresponding benchmark section
4. Check foundational techniques used (planning, tool-use, etc.)
5. Trace back to foundational reasoning sections for core methods
Citation
When using this repository in research or projects:
@article{wei2026agentic,
title={Agentic Reasoning for Large Language Models},
author={Wei, Tianxin and Li, Ting-Wei and Liu, Zhining and Ning, Xuying and Yang, Ze and Zou, Jiaru and Zeng, Zhichen and Qiu, Ruizhong and Lin, Xiao and Fu, Dongqi and others},
journal={arXiv preprint arXiv:2601.12538},
year={2026}
}
Integration with Development Workflows
For Researchers
Literature Review Workflow:
- Clone the repository for offline access
- Use the categorized structure to identify relevant papers
- Cross-reference applications with foundational techniques
- Export citations for reference management tools
For Practitioners
Implementation Workflow:
- Identify your application domain (e.g., web agents, coding)
- Review application-specific papers and benchmarks
- Trace foundational techniques (planning, tool-use)
- Reference implementation papers for code patterns
- Evaluate using suggested benchmarks
For Tool Builders
Benchmark Selection:
- Determine core capability (planning, tool-use, search)
- Navigate to corresponding benchmark section
- Review evaluation frameworks and metrics
- Compare agent performance across standard benchmarks
Best Practices
Exploring New Topics
- Start with the Overview: Read the survey paper introduction and framework diagram
- Navigate by Layer: Begin with foundational reasoning before advanced topics
- Cross-Reference: Link application papers back to foundational techniques
- Check Benchmarks: Understand evaluation standards for each capability
Contributing Quality Additions
- Verify Relevance: Ensure papers fit the agentic reasoning scope
- Check Duplicates: Search existing entries before adding
- Provide Context: Include venue/year information
- Follow Format: Maintain consistent table structure
Staying Current
- Monitor Commits: The repository updates regularly with new papers
- Check News Section: Major updates announced at the top of README
- Watch Discussions: GitHub issues may highlight emerging trends
- Follow Survey Updates: Authors plan continued improvements
Troubleshooting
Finding Specific Papers
Issue: Can't locate a specific paper
Solution:
- Use browser search (Ctrl+F / Cmd+F) on the README
- Check multiple related sections (papers may fit several categories)
- Review the benchmarks section for evaluation-focused papers
- Check recent commits if it's a new publication
Understanding Categories
Issue: Unclear which section contains relevant papers
Solution:
- Refer to the framework overview diagram
- Read the category descriptions in the survey paper
- Cross-reference with similar known papers
- Check application sections if domain-specific
Accessing Papers
Issue: Links not working or papers behind paywalls
Solution:
- Most papers link to arXiv versions (open access)
- For conference papers, search on Google Scholar
- Check author websites for preprints
- Use institutional access for published versions
Related Resources
Quick Reference
| Category | Key Papers | Benchmarks |
|---|
| Planning | Tree of Thoughts, ReAct, Plan-and-Solve | PlanBench, BlocksWorld |
| Tool-Use | Gorilla, ToolLLM, HuggingGPT | API-Bank, ToolBench |
| Search | WebGPT, Agent-E, Mind2Web | WebArena, GAIA |
| Multi-Agent | ChatDev, AgentVerse, MetaGPT | MAgIC, AgentBench |
| Embodied | LM-Nav, PERIA, RT-1 | CALVIN, MetaWorld |
| Scientific | FunSearch, AI Scientist | ScienceBench |
This skill enables AI coding agents to effectively navigate and utilize the Awesome Agentic Reasoning repository, helping developers access cutting-edge research on LLM-based agents, understand agentic reasoning frameworks, and apply state-of-the-art techniques to their projects.
