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π¦ OpenClaw launched Nov 2025, hit 200k GitHub stars in 84 days, and surpassed 330k stars by March 2026. This repo collects papers studying or built upon the OpenClaw ecosystem β covering agent infrastructure, learning, safety, embodiment, social dynamics & domain applications. The questions are universal; OpenClaw is the lens.
NanoClaw is an open-source, lightweight, and containerized personal AI assistant framework
nanobot
GitHub
2026.02
Nanobot is a lightweight system framework for personal AI agents, providing agent execution architecture, cross-platform message integration, and tool invocation mechanisms
AutoResearchClaw:Chat an Idea. Get a Paper. Autonomous, Collaborative & Self-Evolving.
GitHub
2026.03
AutoResearchClaw is an openβsource infrastructure for fully automated and coβpilotβassisted scientific research
Three Provinces and Six Ministries Β· Edict
GitHub
2026.02
Edict is an OpenClawβbased multiβagent coordination and governance infrastructure that defines structured roles, task delegation, and audit mechanisms for orchestrating agent workflows
ClawTeam: Agent Swarm Intelligence
GitHub
2026.03
ClawTeam is a foundational framework for AI agent group collaboration and automated orchestration, providing system-level capabilities such as multi-agent task allocation, team coordination, and real-time monitoring
CyberClaw is a transparent, controllable agent architecture for multi-domain AI systems, enabling decision auditing, safe execution, persistent memory, and monitoring, compatible with OpenClaw/Claude Code
Learning & Evolution
Reinforcement learning, meta-learning, and self-improvement of agents.
Hermes Agent is an autonomous AI agent with a builtβin selfβimproving learning loop, capable of persistent memory, autonomous skill creation and refinement, and adaptive personalized interactions across sessions
SkillClaw: Let Skills Evolve Collectively with Agentic Evolver
arXiv
2026.04
SkillClaw is a framework for evolving and sharing skills across multi-user autonomous agents, enabling continuous capability improvement and knowledge transfer
Safety & Security
Attack benchmarks, defense frameworks, supply-chain security, and runtime protection.
Title
Venue
Date
Paper
Code
Highlights
From Assistant to Double Agent: Formalizing and Benchmarking Attacks on OpenClaw for Personalized Local AI Agent
arXiv
2026.02
End-to-end security eval; only 17% native defense rate
A Trajectory-Based Safety Audit of Clawdbot (OpenClaw)
OpenClaw PRISM: A Zero-Fork, Defense-in-Depth Runtime Security Layer for Tool-Augmented LLM Agents
arXiv
2026.03
Defense-in-depth; zero-fork; anti prompt injection
Uncovering Security Threats and Architecting Defenses in Autonomous Agents: A Case Study of OpenClaw
arXiv
2026.03
Tsinghua & Ant Group; tri-layered risk taxonomy; FASA + ClawGuard; 26% community tools have vulns
Defensible Design for OpenClaw: Securing Autonomous Tool-Invoking Agents
arXiv
2026.03
Security-as-engineering blueprint; risk taxonomy; practical research agenda
Claw-Eval: Toward Trustworthy Evaluation of Autonomous Agents
arXiv
2026.04
ClawβEval is a benchmark suite for autonomous agents with trajectory-aware grading and safety metrics, addressing gaps in existing evaluations for deployable agents
ClawArena: Benchmarking AI Agents in Evolving Information Environments
arXiv
2026.04
ClawArena benchmarks autonomous agents on belief accuracy in dynamic, multi-source environments, highlighting reasoning, belief revision, and personalization challenges
Taming OpenClaw: Security Analysis and Mitigation of Autonomous LLM Agent Threats
arXiv
2026.03
Taming OpenClaw is a security framework analyzing LLM agent vulnerabilities and proposing lifecycle-aware defenses to reduce systemic risks
ClawBench: Can AI Agents Complete Everyday Online Tasks?
arXiv
2026.04
ClawBench benchmarks autonomous agents on completing real-world online tasks, tracking behavior and revealing reliability and safety challenges
Your Agent, Their Asset: A Real-World Safety Analysis of OpenClaw
arXiv
2026.04
Your Agent, Their Asset evaluates OpenClaw using the CIK taxonomy, exposing high vulnerabilities and limited defenses across multiple models
Agent Society
Social behaviors, emergent norms, peer learning, and collective dynamics in agent populations.
Title
Venue
Date
Paper
Code
Highlights
OpenClaw Agents on Moltbook: Risky Instruction Sharing and Norm Enforcement in an Agent-Only Social Network
When AI Agents Teach Each Other: Discourse Patterns Resembling Peer Learning in the Moltbook Community
arXiv
2026.02
2.4M agents' peer learning patterns
OpenClaw AI Agents as Informal Learners at Moltbook: Characterizing an Emergent Learning Community at Scale
arXiv
2026.02
2.8M agents' informal learning behavior
When Openclaw Agents Learn from Each Other: Insights from Emergent AI Agent Communities for Human-AI Partnership in Education
arXiv
2026.03
167k agents; bidirectional scaffolding; emergent peer learning; implications for AIED
MoChat: Reconnecting the World through AI Agents
GitHub
2026.02
MoChat is a native AI agent social platform that builds an interactive ecosystem and collaborative space for AI agents
AgentPanel: The worldβs first research-focused human-AI Agent collaborative discussion community
GitHub
2026.03
AgentPanel is a collaborative discussion platform where humans and AI agents (e.g., OpenClaw) jointly engage in researchβoriented social interactions, enabling multiβagent Q&A, debate, and knowledge sharing
application
Vertical applications, organized into embodied, scientific discovery, medical, and other directions.
Embodied Agents
Robotics, physical embodiment, and ROS integration.
Title
Venue
Date
Paper
Code
Highlights
RoboClaw: An Agentic Framework for Scalable Long-Horizon Robotic Tasks
From Agent-Only Social Networks to Autonomous Scientific Research: Lessons from OpenClaw and Moltbook, and the Architecture of ClawdLab and Beach.Science
arXiv
2026.02
Agent social networks to research platforms; life-science collaboration; workflow orchestration and platform architecture
ScienceClaw
GitHub / Website
2026.03
Self-evolving research colleague for scientists; 285 skills; persistent research memory; life-science automation platform
Medical
Clinical workflows, medical imaging, digital twins, and medical skill ecosystems.
Title
Venue
Date
Paper
Code
Highlights
Autonomous Agent-Orchestrated Digital Twins (AADT): Leveraging the OpenClaw Framework for State Synchronization in Rare Genetic Disorders
arXiv
2026.03
Medical digital twins for rare genetic disorders; heartbeat-based synchronization; longitudinal phenotype tracking
MedOpenClaw: Auditable Medical Imaging Agents Reasoning over Uncurated Full Studies
arXiv
2026.03
Auditable agents for full 3D medical imaging studies; MedFlowBench; spatial grounding and tool use
OpenClaw-Medical-Skills
GitHub
2026.03
Open-source medical skill library; 869 curated skills; clinical, genomics, drug discovery, and bioinformatics
When OpenClaw Meets Hospital: Toward an Agentic Operating System for Dynamic Clinical Workflows
arXiv
2026.03
Restricted execution; document-centric interaction; page-indexed memory; medical skill library
Other
Other application directions such as education, knowledge work, and math learning.
Title
Venue
Date
Paper
Code
Highlights
Scaling Laws for Educational AI Agents
arXiv
2026.03
Agent scaling laws; AgentProfile framework; 330+ profiles and 1,100+ skill modules across K-12
DenchClaw
GitHub
2026.02
OpenClaw framework for business operations and sales outreach; CRM automation, calling, and local workflows
MathClaw
GitHub
2026.03
Multimodal learning assistant for secondary-school mathematics; math education and interactive learning support
π Architecture
flowchart LR
subgraph Channels["π± Channels"]
direction TB
C1[WhatsApp] ~~~ C2[Telegram] ~~~ C3[Discord] ~~~ C4[Slack] ~~~ C5["50+"]
end
subgraph Core["βοΈ Core"]
direction TB
Router[Message Router] --> Kernel[Agent Kernel]
Kernel <--> LLM["LLM Backend\nClaude / GPT / Ollama"]
end
subgraph Memory["π§ Memory"]
direction TB
M1[Session Context] ~~~ M2[Daily Notes] ~~~ M3[Long-term Memory] ~~~ M4[Semantic Search]
end
subgraph Extensions["π Extensions"]
direction TB
E1["Skills (5,700+)"] ~~~ E2["MCP (3,200+)"] ~~~ E3[Plugins]
end
subgraph External["π External"]
direction TB
X1[Moltbook] ~~~ X2[ROSClaw] ~~~ X3[RoboClaw]
end
Channels --> Core
Core <--> Memory
Core <--> Extensions
Extensions --> External