matching-engine
AI 关系匹配助手的中心化匹配引擎。作为一个独立的 OpenClaw 实例运行，通过内部群组与所有用户的个人 Agent 通信。负责接收用户画像标签摘要、维护全局用户注册表、执行双向匹配算法（处境一致性 + 能力互补性）、监控匹配阈值、在达标时向相关个人 Agent 发送匹配通知、协调双方确认流程、以及收集匹配反馈用于算法优化。当群组中出现新消息、或到了定时匹配扫描的时间时，本 skill 应被触发。
Why use this skill?
Deploy a powerful AI-driven matching engine to connect users within your OpenClaw network using advanced capability and interest vector analysis.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/freeai-io/social-hub-serverWhat This Skill Does
The Matching Engine is the central intelligence node of the OpenClaw relationship-matching ecosystem. Operating as an independent agent instance, it functions as a persistent background server that orchestrates connections between users. It does not engage in casual conversation; instead, it acts as a high-level facilitator that communicates exclusively with individual user agents via an internal group.
Its core logic revolves around a sophisticated bi-directional matching algorithm that evaluates 'contextual consistency' and 'capability complementarity.' By maintaining a global registry of users and utilizing ChromaDB to store vectorized user profiles across dimensions such as skills, interests, and goals, the engine continuously monitors for potential high-value interpersonal synergies. When the engine identifies a match that exceeds predefined threshold scores, it notifies the relevant individual agents, coordinates a dual-confirmation flow, and collects post-interaction feedback to tune its matching algorithm over time.
Installation
To integrate the Matching Engine into your OpenClaw environment, execute the following command in your terminal:
clawhub install openclaw/skills/skills/freeai-io/social-hub-server
Ensure that the environment has read/write access to the ~/.matchbot-engine/ directory, as the engine requires this path to persist its user registry, match history, and vector databases.
Use Cases
- Professional Networking: Automatically connecting users who possess complementary technical skills (e.g., a frontend developer needing a backend specialist) to foster collaboration.
- Mentorship Matching: Pairing individuals seeking specific goals with mentors who have documented success in those areas.
- Interest Groups: Facilitating introductions between individuals with high contextual consistency in niche hobbies or intellectual pursuits.
Example Prompts
- "Matching Engine, trigger a force scan of all registered users to identify any high-potential collaboration opportunities that were missed in the last 6 hours."
- "Update user_005 profile: Add 'Rust programming' to skills and 'Distributed systems' to goals, then re-run matching algorithms for this user."
- "Summarize the current matching status for user_042 and show me any pending acceptance requests that require immediate user action."
Tips & Limitations
- Vector Sensitivity: Because the engine relies on embeddings, ensure that user tags are descriptive and clear. Ambiguous labels can lead to suboptimal matching results.
- Privacy and Ethics: The engine respects disclosure settings defined by each user. Ensure users are aware that their profile data is being processed by the central hub.
- Performance: For deployments exceeding 1,000+ users, monitor the memory usage of the ChromaDB collections and the latency of the embedding API calls to ensure timely processing during global scan cycles.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-freeai-io-social-hub-server": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: file-write, file-read, external-api