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Triple Memory
by
ktpriyatham
· GitHub ↗
· v1.0.0
2451
Downloads
5
Stars
7
Active Installs
1
Versions
Install in OpenClaw
/install triple-memory-skill
Description
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.
Usage Guidance
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.
Capability Analysis
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.
Capability Assessment
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'.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install triple-memory-skill - After installation, invoke the skill by name or use
/triple-memory-skill - Provide required inputs per the skill's parameter spec and get structured output
Version History
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.
Metadata
Frequently Asked Questions
What is Triple Memory?
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. It is an AI Agent Skill for Claude Code / OpenClaw, with 2451 downloads so far.
How do I install Triple Memory?
Run "/install triple-memory-skill" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Triple Memory free?
Yes, Triple Memory is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Triple Memory support?
Triple Memory is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Triple Memory?
It is built and maintained by ktpriyatham (@ktpriyatham); the current version is v1.0.0.
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