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Neron
作者
Vladikasik
· GitHub ↗
· v1.0.0
· MIT-0
155
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install neron
功能描述
Personal knowledge graph. Record notes, track moods, manage tasks, spot patterns in someone's life.
安全使用建议
This skill is coherent with its purpose (a personal knowledge-graph connector) but it gives any connected agent full read/write access to very sensitive personal data via a third-party endpoint (https://mcp.neron.guru/mcp). Before installing or connecting:
- Verify the service and operator: ask for a homepage, privacy policy, and source code or repository. The registry metadata lists no homepage and the publisher is unknown — that reduces trust.
- Treat the Telegram token/password as high-value secrets: only request tokens you can revoke, and avoid pasting them into shared or cloud-backed config files. Prefer storing them in a secure credential store if possible.
- If possible, use a least-privilege token (read-only) for agents that only need to view data; avoid giving write/delete rights unless necessary.
- Understand that the skill allows raw Cypher queries and 'full' verbosity, which can return complete data dumps — don't grant it access to real sensitive data until you trust the service.
- Check TLS certificate and domain reputation for mcp.neron.guru and validate the Telegram bot identity (@NeronBetaBot) before sending credentials to it.
- Consider testing with throwaway or synthetic data first, and ensure you can revoke the token (/token) and that revocation invalidates prior tokens.
What would raise my confidence: a public homepage/privacy policy, audited source code or GitHub repo, documented token scopes, and a clear operator identity or third‑party audit.
功能分析
Type: OpenClaw Skill
Name: neron
Version: 1.0.0
The Neron skill bundle provides a comprehensive MCP interface for interacting with a personal knowledge graph service hosted at mcp.neron.guru. It includes 12 tools for data management and graph analytics, including raw Cypher queries via Apache AGE. The instructions in SKILL.md and the documentation are well-structured, focusing on helping the agent act as a useful personal assistant while emphasizing privacy and the synthesis of user data. No evidence of malicious intent, unauthorized data exfiltration, or prompt injection attacks was found.
能力评估
Purpose & Capability
The skill is a connector for a personal knowledge graph and all described tools (search, semantic_search, cypher, create/update/delete, node_context, etc.) match that purpose. It does not declare unrelated binaries or environment variables. The MCP endpoint and token-based auth model described are coherent with a remote graph service.
Instruction Scope
SKILL.md and auxiliary docs explicitly instruct the agent to call a remote MCP endpoint and use rich tools (including raw Cypher). The docs also instruct users to obtain tokens/passwords via a Telegram bot and place tokens in agent config files. That behavior is within scope for an agent that should read/write a user's graph, but it grants powerful read/write access to sensitive personal data and instructs storing tokens in local config locations — the scope is broad by design and should be treated as high-sensitivity.
Install Mechanism
There is no install spec or executable code; the skill is instruction-only and does not download or install third-party binaries or archives. This minimizes local code-execution risk.
Credentials
No environment variables are declared in metadata, and the service uses per-user Bearer tokens obtained from a Telegram bot. Requiring a token for full read/write access to the user's graph is proportionate to the stated functionality, but those credentials are highly sensitive. The skill does not ask for unrelated credentials, but it does rely on the user placing tokens into agent config files (clear-text storage by instruction), which has privacy implications.
Persistence & Privilege
The skill is not marked always:true and does not request system-wide modifications. It instructs adding a connector/token to agent config (normal for connectors). It does not request elevated or persistent platform privileges beyond normal agent connectors.
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 neron - 安装完成后，直接呼叫该 Skill 的名称或使用
/neron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
Initial release of Neron — a personal knowledge graph skill.
- Record notes, track moods, manage tasks, and connect life events in a linked graph.
- Supports journaling, mood/activity/health tracking, task/project/person management, and AI-powered insights.
- Uses powerful search (keyword & semantic), advanced graph queries, and data pattern spotting.
- Designed for genuinely useful, context-aware interactions — responds as someone who knows you.
- Full CRUD for core entities; automatic extraction entities from notes; detailed guidance for common use cases.
- Built on Apache AGE graph with Cypher analytics and rich graph structure.
元数据
常见问题
Neron 是什么？
Personal knowledge graph. Record notes, track moods, manage tasks, spot patterns in someone's life. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 155 次。
如何安装 Neron？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install neron」即可一键安装，无需额外配置。
Neron 是免费的吗？
是的，Neron 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Neron 支持哪些平台？
Neron 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 Neron？
由 Vladikasik（@vladikasik）开发并维护，当前版本 v1.0.0。
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