Subscribe Filter Feishu

订阅-过滤-飞书推送。通过WebSocket订阅数据流，大模型智能过滤，自动推送到飞书。

This package appears to implement the stated WebSocket → LLM → Feishu flow and only requires the Feishu and model credentials that it needs to function — but there are important inconsistencies to check before installing: - SKILL.md references a CLI wrapper (subscribe-filter-feishu start/stop/config) and a script path (scripts/subscribe-filter-feishu) that are not included. The actual runnable file is scripts/receiver.js — you will need to run it directly (e.g., node scripts/receiver.js or npm start) or create your own wrapper/service. - Inspect scripts/receiver.js yourself (it is provided) to confirm you are comfortable with it sending data to the configured model_base_url and Feishu endpoints. The script will persist secrets in ~/.openclaw/subscribe-filter-feishu.json and write logs/stats/PID under ~/clawd/data/subscribe-filter-feishu. - Verify the model_base_url and model_name you configure (default points at an Ark endpoint). Only provide API keys and app secrets you trust to this code and the endpoints you control/trust. - When running npm install, note dependencies will be fetched (lockfile points to a mirror). If you have supply-chain concerns, audit package versions or install in an isolated environment. If you plan to use this skill: (1) fix or add a proper CLI/service wrapper if you need start/stop/status semantics; (2) consider file permissions on the config file to protect secrets; (3) run the code in an environment you control and review network endpoints. The inconsistencies in SKILL.md and packaging are likely oversight but should be resolved before production use.

Type: OpenClaw Skill Name: subscribe-filter-feishu Version: 1.0.3 The skill bundle implements a legitimate news filtering and notification service that connects to a WebSocket stream, processes content via an LLM (Volcengine Ark), and pushes results to Feishu. The code in `scripts/receiver.js` follows standard development practices, including local configuration management for API secrets, PID-based process control, and basic error handling. No evidence of data exfiltration, unauthorized file access, or malicious prompt injection was found; the network and file system activities are strictly aligned with the stated purpose.