No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by lovstudio · Agent Tool · ★ 358
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Ataru safe to install? View the security audit →
Ataru 在本地，快速找回过去 AI 对话中的答案。 Search the memory of your AI work. macOS · Windows · Linux 为什么是 Ataru · 产品路径 · 快速开始 · Agent Skill · 架构 · 开发 · 附录与 FAQ Why Ataru AI 编程过程中，真正有价值的答案经常已经出现过：一次故障排查、一条关键命令、一个架构取舍，或者一段几周前才讨论过的上下文。但这些内容分散在不同 Agent 的本地会话文件里，靠记忆、目录名和人工翻找很难重新定位。 Ataru 把这些已经发生过的对话变成本地可检索的记忆层： 从 Claude、Codex 等本地会话来源建立统一索引。 用关键词、字段、短语或自然语言描述找回相关上下文。 在 、、 三种粒度之间切换。 从命中片段回到原始会话、消息和行号，而不是只展示一段截断摘要。 默认离线运行；语义检索是可选增强，未配置或超时会清晰降级到关键词检索。 Ataru 的目标不是管理正在运行的 Agent，而是让过去的工作重新变得可用。 What it does 新消息写入后自动追赶索引，不需要每次从头扫描
| Stars | 358 |
| Forks | 38 |
| Language | Rust |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 68.4818011205697/100 |
| Open Issues | 15 |
| Last Updated | 2026-08-24 |
| Created | 2025-12-10 |
| Platforms | claude-code, cli, rust |
| Est. Tokens | ~25k |
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Ataru is High-performance AI memory retrieval for local agent history — a Rust search core (SDK / API / JSON CLI) plus a desktop GUI. Tantivy + Jieba keyword search, optional semantic recall, stable Turn/Run/S. It is categorized as a Agent Tool with 358 GitHub stars.
Ataru is primarily written in Rust. It covers topics such as agent-memory, ai-memory, ai-tools.
You can find installation instructions and usage details in the Ataru GitHub repository at github.com/lovstudio/Ataru. The project has 358 stars and 38 forks, indicating an active community.
Ataru is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to Ataru on Agent Skills Hub include lovcode, Ori-Mnemos, yume. 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: