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Self Description(Agent Native)

Exuberant Witness edited this page Jun 28, 2026 · 1 revision

A .flux file is self-describing: any tool, agent, or human can understand its contents without a runtime, plugin, or external dependency.

How it works

  1. Magic bytes FLXM in the 64-byte header — flux inspect identifies any file
  2. Schema ID in the header — format version + schema hash
  3. Records carry kind + meta — human-readable key/value pairs; an agent understands the content by reading field names (name, title, type, tags)
  4. .fluxa text form — the whole store in grep-able, diff-able plain text

Why this matters for agents

An AI agent (LLM, VLA) can:

from fluxmeme import Store

with Store("robot.flux") as s, s.read() as txn:
    for r in s.scan(txn):
        print(r.kind, r.meta)
        if r.payload:
            print(r.payload[:200])

Without installing a simulation runtime, a USD plugin, or a ROS stack — the agent opens the .flux, scans records, and understands: "this is a robot with 2 links, a revolute joint, and a cart-pole balancing task."

Compare to USD

USD .flux
Agent reads without runtime? no (needs USD plugin + scene graph) yes
Human-grepable? no (binary USDC; USDA is verbose) yes (.fluxa)
Self-identifying? yes (magic + UsdStage) yes (magic FLXM + schema_id)
Structured metadata per record? yes (prim attributes, but engine-heavy) yes (simple kind + meta KV)

The .fluxa text form

#FLUXMEME 1.0
R 019f0411ac9819354883672df8f5d3ec
L MIND
K concept
M title=Cart-pole balancing task
M tags=rl,control,balance
D 73
# Cart-Pole Balancing
Balance the pole upright...

This is the canonical source (what you commit to Git). Agents and humans read it like any text file. flux conv converts to/from the binary .flux.


自描述(Agent 原生)(中文)

一个 .flux 文件是自描述的:任何工具、agent 或人都能理解其内容,无需运行时、 插件或外部依赖

工作原理

  1. Magic 字节 FLXM(64 字节头)——flux inspect 识别任意文件
  2. Schema ID(头)——格式版本 + schema 哈希
  3. 记录带 kind + meta——人可读的 KV;agent 读字段名即可理解内容
  4. .fluxa 文本形态——整个 store 可 grep、可 diff 的纯文本

为什么这对 agent 重要

AI agent(LLM、VLA)可以:

with Store("robot.flux") as s, s.read() as txn:
    for r in s.scan(txn):
        print(r.kind, r.meta)

无需安装仿真运行时、USD 插件或 ROS——agent 打开 .flux、扫描记录,就理解了: "这是一个有 2 个连杆、1 个旋转关节的机器人,任务是平衡杆。"

对比 USD

USD .flux
Agent 无运行时可读? 否(需 USD 插件 + 场景图)
人可 grep? (.fluxa)
自识别? 是(magic + UsdStage) (magic FLXM)
每条记录有结构化元数据? 是(prim 属性,但引擎重) (简单 kind + meta)

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