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Rewind Memory — Persistent Bio-Inspired Memory for AI Agents

作者 SARAI Defence · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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当前安装
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版本数
在 OpenClaw 中安装
/install rewind-memory
功能描述
Persistent, bio-inspired memory for AI agents. 5-layer architecture (L0-L4) with BM25 keyword search, knowledge graph, vector similarity, and HybridRAG fusio...
安全使用建议
This skill appears to do what it says: it automatically captures edits, tool outputs, and conversation turns and stores them in a local ~/.rewind data directory; it will also search that memory and inject relevant context into prompts. Things to consider before enabling: - Privacy: Hooks may capture command outputs and file contents (including secrets accidentally printed to stdout). Audit what your tools output and avoid storing sensitive data. - Pro / cloud features: The Pro path sends queued text to an external Modal endpoint using an auth token stored in ~/.rewind/config.yaml; only configure this if you trust the remote service and keep the auth token secret. - Local binaries: The hooks call an external 'rewind' CLI and may call 'ollama pull' during setup; ensure you inspect/approve those tools and their network activity before running them. - Config review: Inspect ~/.rewind/config.yaml (or REWIND_DATA_DIR) before use to confirm providers, endpoints, and tokens. - Minimizing risk: If you want memory but not automatic capture, disable or remove the hooks, or decline to enable Pro/cloud features. If you have low tolerance for automated context injection, do not enable the UserPromptSubmit/PostToolUse hooks. Overall the package is internally coherent (benign), but it has meaningful privacy and exfiltration implications if you enable Pro or provide external endpoints — review configs and opt-ins carefully.
功能分析
Type: OpenClaw Skill Name: rewind-memory Version: 1.0.0 The skill implements a persistent memory system that captures user prompts, command outputs, and file edits, storing them locally or exfiltrating them to a remote Modal endpoint in the 'Pro' tier (hooks/post_tool_use.py, hooks/session_end.py). While these actions align with the stated purpose of building a 'knowledge graph,' the implementation contains shell injection vulnerabilities in several command files (e.g., commands/rewind-search.md, commands/rewind-recall.md) where the agent is instructed to pass raw user arguments into shell commands. Furthermore, the automatic capture of all 'bash' and 'execute' tool outputs poses a significant risk of capturing and transmitting sensitive data like credentials or API keys to the saraidefence.com infrastructure.
能力标签
crypto
能力评估
Purpose & Capability
Name/description align with the provided files and hooks. The package implements layered memory (search, KG, vectors), provides CLI integration, and registers hooks to capture and index session data — all consistent with a 'persistent memory' skill.
Instruction Scope
Runtime hooks capture file edits, command outputs, and user prompts and will index or store those as memory. UserPrompt injects prior context into system messages. This scope is consistent with the memory use-case but has high privacy impact (it may capture command outputs and snippets of files automatically). The setup flow can pull local models (ollama) and writes ~/.rewind/config.yaml.
Install Mechanism
No installer spec is embedded in the skill bundle. The SKILL.md instructs users to 'pip install rewind-memory' and to optionally pull models with Ollama; code files do not download arbitrary archives themselves. No suspicious external download URLs or shorteners are embedded in the included files.
Credentials
The skill does not require platform credentials but reads several environment/config values (CLAUDE_PLUGIN_ROOT, REWIND_DATA_DIR, REWIND_API_URL) and the user-writable ~/.rewind/config.yaml. Pro features rely on modal.extract_batch_url and modal.auth_token from that config to POST queued texts to an external Modal endpoint — this is justified by the Pro workflow but is sensitive and should only be enabled with trusted endpoints and tokens.
Persistence & Privilege
The skill registers hooks (PostToolUse, Stop, UserPromptSubmit) that run local Python scripts and write persistent data under ~/.rewind (and a queue directory). always:false (not force-enabled). The behavior is expected for a memory plugin, but it will persistently store session content and can autonomously inject memory into prompts.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install rewind-memory
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /rewind-memory 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release — 5-layer bio-inspired memory with BM25, knowledge graph, vector search, HybridRAG fusion, OpenClaw hooks, and MCP server
元数据
Slug rewind-memory
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Rewind Memory — Persistent Bio-Inspired Memory for AI Agents 是什么?

Persistent, bio-inspired memory for AI agents. 5-layer architecture (L0-L4) with BM25 keyword search, knowledge graph, vector similarity, and HybridRAG fusio... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 68 次。

如何安装 Rewind Memory — Persistent Bio-Inspired Memory for AI Agents?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install rewind-memory」即可一键安装,无需额外配置。

Rewind Memory — Persistent Bio-Inspired Memory for AI Agents 是免费的吗?

是的,Rewind Memory — Persistent Bio-Inspired Memory for AI Agents 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Rewind Memory — Persistent Bio-Inspired Memory for AI Agents 支持哪些平台?

Rewind Memory — Persistent Bio-Inspired Memory for AI Agents 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Rewind Memory — Persistent Bio-Inspired Memory for AI Agents?

由 SARAI Defence(@vnesin-sarai)开发并维护,当前版本 v1.0.0。

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