deepbot: System-level AI assistant built for both personal productivity and enterprise workflows

by kevinluosl · Codex Skill · ★ 2.3k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 65/100

Flagged: sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-skillsagent-toolsagentic-workflowagentosai-agentsharnessharness-engineeringopenclaw

Quick Facts

Stars2,279
Forks180
LanguageTypeScript
CategoryCodex Skill
LicenseMIT
Quality Score65/100
Open Issues2
Last Updated2026-05-23
Created2026-01-30
Platformscli, node
Est. Tokens~579k

About deepbot

让 AI 深入参与企业日常办公,成为你真正干活的伙伴 English | 简体中文 📖 简介 DeepBot 是一个系统级 AI 助手,会更多探索企业生产提效方向。它能够与企业现有系统深度结合,让 AI 深入参与各部门的日常办公提效,通过多 Agent 协作模式实现复杂业务流程的自动化。无论是文档处理、数据分析、系统监控,还是跨部门协作任务,DeepBot 都能通过 AI Agent 技术帮助企业轻松搞定。它支持多任务并行处理、定时任务、技能扩展等功能,同时通过严格的安全机制保护企业系统安全。 ✨ 核心特性 🎯 多任务并行处理 - 同时处理多个任务,互不干扰 🔧 13 个内置工具 - 文件操作、命令执行、浏览器控制、图片生成、AI 对话、跨会话通信、网页内容获取等 🧠 记忆系统 - 长期记忆用户偏好和重要信息 ⏰ 定时任务 - 自动化执行周期性任务 🎨 技能扩展 - 通过...

Compatible Skills

These tools work well together with deepbot for enhanced workflows:

  • Aurogen — semantic(0.37)+complementary+same_lang+similar_pop+shared_platform (58%)
  • openclaw-a2a-gateway — semantic(0.35)+complementary+same_lang+similar_pop+shared_platform (57%)
  • use-agently — semantic(0.32)+complementary+same_lang+similar_pop+shared_platform (56%)
  • ai-maestro — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (53%)
  • evo-ai — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (53%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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