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ktpriyatham

Triple Memory

作者 ktpriyatham · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
2451
总下载
5
收藏
7
当前安装
1
版本数
在 OpenClaw 中安装
/install triple-memory-skill
功能描述
Complete memory system combining LanceDB auto-recall, Git-Notes structured memory, and file-based workspace search. Use when setting up comprehensive agent memory, when you need persistent context across sessions, or when managing decisions/preferences/tasks with multiple memory backends working together.
安全使用建议
Before installing, verify the following: (1) Confirm where LanceDB stores data and whether it is local or remote and who can access it; (2) Expect to provide an embeddings API key (OPENAI_API_KEY) — do not hardcode secrets into workspace files; (3) Ensure you have the 'memory-lancedb' plugin and 'git-notes-memory' skill from a trusted source; inspect the git-notes code to see if it pushes to remote repos; (4) Be aware the skill recommends silently persisting conversation data and auto-flushing session summaries — if you need user-visible consent or auditability, disable autoCapture/autoFlush or require explicit prompts; (5) Check that your environment has 'clawdbot' and Python available and review scripts (scripts/file-search.sh writes to /tmp and kills the background search after 8s). If the author/source cannot explain the omitted manifest declarations (required env vars, binaries, plugin dependencies) or you don't trust the upstream git-notes/LanceDB implementations, treat this as potentially risky and avoid deploying for sensitive data.
功能分析
Type: OpenClaw Skill Name: triple-memory-skill Version: 1.0.0 The skill bundle provides a comprehensive memory system for the OpenClaw agent, integrating LanceDB, Git-Notes, and file-based search. The `SKILL.md` and `references/SETUP.md` contain instructions for configuring the agent's memory plugins and behavior, including a prompt to perform memory operations 'silently'. The `scripts/file-search.sh` script executes the `clawdbot memory search` command, which is an internal agent CLI tool, and includes a timeout mechanism. There is no evidence of data exfiltration, malicious execution, persistence, or obfuscation. The 'silent operation' instruction, while potentially usable in a malicious context, is presented here as a UX preference for memory management and is not coupled with any harmful actions, thus not meeting the threshold for malicious intent.
能力评估
⚠ Purpose & Capability
The SKILL.md clearly expects the memory-lancedb plugin, the git-notes-memory skill, and use of an embedding API key (OPENAI_API_KEY) for embeddings, plus runtime tools like 'clawdbot' and Python scripts. The registry metadata/requirements list none of these. That mismatch (manifest claims no env vars or binaries but instructions require them) is incoherent and should be clarified.
⚠ Instruction Scope
Instructions direct the agent to read and write local workspace files (memory/active-context.md, MEMORY.md, YYYY-MM-DD.md), run git-notes sync scripts, invoke clawdbot memory search, and silently store/flush session summaries. These actions are within the skill's stated purpose (memory), but the 'silent operation' guidance and automatic flush behavior increase privacy risk and reduce user visibility.
✓ Install Mechanism
There is no remote installer or download; this is instruction-only plus a small included shell script. No archive downloads or third-party package installs are declared, so install risk is low. The included scripts are small and readable.
⚠ Credentials
Although the manifest declares no required env vars, the config examples embed an OPENAI_API_KEY (and SETUP.md shows an sk-... placeholder). The skill implicitly requires credential(s) for embeddings and likely write access to the workspace and (if git-notes pushes) to a git remote. Required environment and permissions are not declared, which is disproportionate and a transparency problem.
⚠ Persistence & Privilege
The skill enables automatic capture/auto-recall and suggests adding an auto-flush config that writes session summaries to disk before compaction, and instructs silent operation. While not marked 'always:true', the default autonomous invocation combined with silent persistent storage increases the blast radius for privacy/exfiltration if misconfigured or malicious. This is particularly important because the skill's source is 'unknown'.
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 triple-memory-skill
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /triple-memory-skill 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 of the triple-memory skill, combining LanceDB conversation memory, Git-Notes structured memory, and file-based workspace search. - Designed for comprehensive, persistent agent memory across sessions and branches. - Supports auto-recall and auto-capture of conversation context, structured decision logging, and workspace document search. - Includes setup and usage instructions for LanceDB plugin, Git-Notes memory, and file search script. - Enables automatic context preservation before memory compaction. - Operates silently during memory operations—no user notifications.
元数据
Slug triple-memory-skill
版本 1.0.0
许可证 —
累计安装 7
当前安装数 7
历史版本数 1
常见问题

Triple Memory 是什么?

Complete memory system combining LanceDB auto-recall, Git-Notes structured memory, and file-based workspace search. Use when setting up comprehensive agent memory, when you need persistent context across sessions, or when managing decisions/preferences/tasks with multiple memory backends working together. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 2451 次。

如何安装 Triple Memory?

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

Triple Memory 是免费的吗?

是的,Triple Memory 完全免费(开源免费),可自由下载、安装和使用。

Triple Memory 支持哪些平台?

Triple Memory 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 Triple Memory?

由 ktpriyatham(@ktpriyatham)开发并维护,当前版本 v1.0.0。

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