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版本数
在 OpenClaw 中安装
/install neuron
功能描述
分布式AI节点系统,实现跨局域网节点的任务分发、并行处理和结果聚合
安全使用建议
This skill implements LAN discovery and will broadcast tasks and final results to other hosts on your local network. Before installing: 1) Do not use on untrusted or public networks — any host on the LAN can impersonate nodes because there is no authentication. 2) The configured discovery port (83668) is invalid (valid ports are 1–65535); fix the port in config.json/SKILL.md before use. 3) Consider adding authentication/encryption for node announce, task RPC, and result broadcasts to prevent data leakage. 4) Be aware the skill will persist a node_identity.json file in the skill directory and will accept an undocumented OPENCLAW_NODE_ID env var to override the ID. If you plan to use it, only run in tightly controlled networks and audit/modify the code to add authorization, input filtering, and a valid port.
功能分析
Type: OpenClaw Skill
Name: neuron
Version: 1.0.0
The 'neuron' skill is a distributed AI task processing system that enables multiple OpenClaw instances to collaborate on tasks via a local network. It uses UDP broadcasting on port 83668 for node discovery and leverages the platform's RPC capabilities for task distribution and result aggregation. The code logic in 'scripts/neuron_skill.py' is transparent, aligns with the documentation in 'SKILL.md', and lacks any indicators of malicious intent such as data exfiltration, persistence, or unauthorized command execution. It also includes appropriate security warnings regarding its use in untrusted network environments.
能力评估
Purpose & Capability
The name/description (distributed node discovery, task distribution, aggregation) match the code: the package implements UDP-based discovery, RPC-style calls to other nodes, local model invocation, and result aggregation. However the chosen discovery port (83668) is invalid (port numbers must be <= 65535) which breaks the core networking functionality and contradicts the configuration/instructions that ask you to open that port. The skill also attempts to discover the local IP by connecting to 8.8.8.8 — a common technique but it implies an external network connection to determine local IP.
Instruction Scope
SKILL.md and the code instruct the agent to broadcast tasks and final results over the LAN. That means user queries (potentially sensitive) will be sent to other nodes. There is no evidence of authentication or signing of announce/messages in the code (node identity is just a generated ID and optional OPENCLAW_NODE_ID env var), so any host on the LAN can claim to be a node or receive tasks. The SKILL.md correctly warns to only use in trusted networks, but the runtime instructions give the agent broad discretion to send user data across the network and to save node identity to disk. Also the code reads an environment variable OPENCLAW_NODE_ID (used to override the generated node id) but this env var is not declared in the skill metadata or documented in SKILL.md — mismatch between runtime behavior and declared inputs.
Install Mechanism
There is no install spec (no packages downloaded or installed). The skill includes Python code files that will run in the agent environment; not having an install step lowers supply-chain risk but means the provided code executes as-is in the agent process. No external URLs or archives are pulled by an installer.
Credentials
The registry metadata declares no required env vars, but the code will check for OPENCLAW_NODE_ID and honor it if present (undocumented). The skill performs network I/O and will send user queries/aggregated results out over UDP and via context.rpc_call — this is a form of data sharing/exfiltration that should be considered sensitive. No credentials, encryption, or authentication mechanisms are implemented in the provided code, which is disproportionate risk for a skill that broadcasts potentially sensitive prompts/results to arbitrary LAN hosts.
Persistence & Privilege
The skill writes a persistent node_identity.json to the scripts directory to store the generated node ID. It does not request elevated privileges or modify other skills' configs. 'always' is false and the skill is user-invocable, so it does not force inclusion in all agent runs. Writing this identity file is within scope but users should be aware it will persist a local identifier on disk.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install neuron - 安装完成后,直接呼叫该 Skill 的名称或使用
/neuron触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Neuron 1.0.0 – Initial Release
- Introduces a distributed AI node system for cross-LAN task distribution, parallel processing, and result aggregation.
- Features automatic node discovery via UDP broadcast, task distribution to available nodes, and final result aggregation.
- Provides collective learning through knowledge sharing by broadcasting final answers to the network.
- Includes Python API and direct skill invocation methods for flexible integration.
- Offers configuration options for network parameters, node identity, and firewall guidance.
- Details typical usage scenarios, workflows, troubleshooting, and security best practices.
元数据
常见问题
神经元 是什么?
分布式AI节点系统,实现跨局域网节点的任务分发、并行处理和结果聚合. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 251 次。
如何安装 神经元?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install neuron」即可一键安装,无需额外配置。
神经元 是免费的吗?
是的,神经元 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
神经元 支持哪些平台?
神经元 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 神经元?
由 fqch1981(@fqch1981)开发并维护,当前版本 v1.0.0。
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