@Xudong07452910: Open-source Tool Recommendation: Hivemind — Give All AI Coding Agents a Shared Brain, Automatically Extract Skills from Real Trajectories Anyone using several AI Coding Agents has likely experienced this: each tool's learning is locked in its own context, switching tools means…

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open-source ai-agent shared-memory skill-transfer claude-code codex cursor

Summary

Hivemind is an open-source tool that allows multiple AI Coding Agents (e.g., Claude Code, Codex, Cursor) to share a memory layer, automatically mining high-quality patterns from usage trajectories and converting them into reusable skill files, enabling cross-tool and cross-team skill propagation, significantly reducing token consumption and interaction rounds.

Open-source Tool Recommendation: Hivemind — Give All AI Coding Agents a Shared Brain, Automatically Extract Skills from Real Trajectories Anyone using multiple AI Coding Agents has probably encountered this: each tool's learning is locked in its own context, switching to another tool means starting from scratch. For example, a workflow you've perfected in Claude Code is completely unknown to Codex or Cursor. Hivemind solves this: it acts as a shared memory layer for all agents, automatically capturing prompts, tool calls, and response trajectories from sessions, mining recurring high-quality patterns, and converting them into reusable SKILL.md files that propagate across teams and tools. From Activeloop (Y Combinator backed), the same team behind the open-source Deep Lake vector database. Core features: 1. Automatic pattern mining: discovers what's worth saving from your actual usage trajectories without manual organization. 2. Cross-agent skill propagation: SKILL.md format, fully supported by Claude Code, Codex, Cursor, Hermes Agent, and more. 3. Hybrid retrieval (lexical + semantic): dual coverage with exact keyword search and semantic fuzzy matching. 4. SQL virtual file system: structured storage, queryable, versionable, and migratable memory. 5. Session summarization + automatic Wiki generation: condense long conversations into indexed knowledge fragments. 6. Benchmark validation (LoCoMo): 25% cheaper, 1.7x fewer tokens per question, 31% fewer interaction rounds compared to baseline. This project is especially suitable for developers and engineering teams who work with multiple AI Coding Agents simultaneously and want the tools to 'learn' from each other rather than operate in isolation. It has already gained 929 stars and is one of the most complete open-source implementations in the field of cross-agent shared memory and skill propagation. Compared to a single agent's built-in memory system (like Claude Code's CLAUDE.md), Hivemind's core difference is its 'cross-tool' nature: it's not Claude Code's own memory, but a shared skill repository for all tools. Switching tools does not mean starting over; the team's engineering wisdom can propagate across tools. https://github.com/activeloopai/hivemind… #AIAgent #ClaudeCode #VibeCoding #codex #AIEngineering
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Hivemind

One brain for all your agents

Auto-learning, cloud-backed shared brain for Claude Code • OpenClaw • Codex • Cursor • Hermes • pi agents.

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