by Pancakes-Labs · Codex Skill · ★ 395
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简体中文 日本語 <a href="http
| Stars | 395 |
| Forks | 20 |
| Language | Python |
| Category | Codex Skill |
| License | AGPL-3.0 |
| Quality Score | 56.2108550804633/100 |
| Open Issues | 25 |
| Last Updated | 2026-09-06 |
| Created | 2025-10-25 |
| Platforms | browser, codex, python |
| Est. Tokens | ~13k |
These tools work well together with astrbot_plugin_proactive_chat for enhanced workflows:
Looking for a astrbot_plugin_proactive_chat alternative? If you're comparing astrbot_plugin_proactive_chat with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
一个能让 Bot 在私聊和群聊中发起主动消息的插件，拥有上下文感知、持久化数据、动态情绪、免打扰时段和 TTS 集成。还有独立 WebUI，可进行个性化配置。 An AstrBot plugin that enable
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astrbot_plugin_proactive_chat is 一个能让 Bot 在私聊和群聊中发起主动消息的插件，拥有上下文感知、持久化数据、动态情绪、免打扰时段和 TTS 集成。还有独立 WebUI，可进行个性化配置。 An AstrBot plugin that enables Bot to send proactive messages in private and group chats, featuring context awareness, . It is categorized as a Codex Skill with 395 GitHub stars.
astrbot_plugin_proactive_chat is primarily written in Python. It covers topics such as agent, ai, astrbot.
You can find installation instructions and usage details in the astrbot_plugin_proactive_chat GitHub repository at github.com/Pancakes-Labs/astrbot_plugin_proactive_chat. The project has 395 stars and 20 forks, indicating an active community.
astrbot_plugin_proactive_chat is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to astrbot_plugin_proactive_chat on Agent Skills Hub include astrbot_plugin_proactive_chat, cui, context-space. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: