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Borg

Data community

Description

One brain, many hands: shared local memory (mem0 + Graphiti) for Claude/Codex/Grok agents, a grammar-shim data flywheel, LoRA students with honest promotion gates, and a steerable Codex conductor fleet. MIT.

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

The Borg

One brain, many hands. The Borg is a local-first shared memory system for AI agents: every agent session on the machine — Claude Code, Codex, Grok — reads from and writes to the same memory, so anything one agent learns, every agent knows. The collective grows every session.

It is not a framework you adopt. It is the working machinery of a real single-operator estate, extracted, scrubbed, and published: the recall layer, the temporal knowledge graph, the fine-tuned local extraction models, the promotion gates that keep them honest, and the conductor that turns ChatGPT-account Codex seats into a steerable worker fleet.

        ┌────────────┐  ┌────────────┐  ┌────────────┐
        │ Claude Code│  │   Codex    │  │    Grok    │
        └─────┬──────┘  └─────┬──────┘  └─────┬──────┘
              │  MCP + hooks  │  MCP + hooks  │
              ▼               ▼               ▼
        ┌─────────────────────────────────────────────┐
        │              mem0 recall layer              │   ← facts (vector store)
        │        local LLM extraction + filters       │
        └──────────────────────┬──────────────────────┘
                               ▼
        ┌─────────────────────────────────────────────┐
        │        Graphiti temporal knowledge graph    │   ← entities, relations, time
        │   grammar-locked local models via the shim  │
        └──────────────────────┬──────────────────────┘
                               ▼
        ┌─────────────────────────────────────────────┐
        │   LoRA students (this repo's adapters/)     │   ← tiny local models learning
        │   exam → canary → promote, or stay benched  │     the teachers' jobs
        └─────────────────────────────────────────────┘

What is in this repo

Directory What it holds
adapters/ Trained LoRA adapters for local extraction students, with honest model cards — including the one that failed its promotion canary and why
memory/ The mem0