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Openclaw Memory Master
by
cp3d1455926-svg
· GitHub ↗
· v4.3.0
· MIT-0
234
Downloads
1
Stars
1
Active Installs
8
Versions
Install in OpenClaw
/install openclaw-memory-master
Description
AI Memory System with LLM Wiki
Usage Guidance
This package appears to be a real AI memory library (lots of TypeScript source and tests) and does not ask for secrets, but it instructs you to clone and run code from an external GitHub repository and to execute npm/tsc/ts-node commands. If you plan to install or let an agent run it: 1) Inspect the repository contents yourself (particularly any install/test scripts) before running them. 2) Do not run these instructions with elevated privileges. 3) Check SKILL.md for any embedded/encoded payloads (the scanner flagged a base64-like block). 4) Prefer running builds and tests in an isolated environment (container, VM) rather than on a production host. 5) If you expect the agent to run this autonomously, be cautious — automatic execution of unvetted code increases risk. If you want, I can scan the repo files for network calls, suspicious exec usages, or decode any embedded base64 content if you paste the suspected block.
Capability Analysis
Type: OpenClaw Skill
Name: openclaw-memory-master
Version: 4.3.0
The bundle is classified as suspicious due to extreme disorganization and a total mismatch between filenames and their actual contents (e.g., package.json contains Markdown, tsconfig.json contains JavaScript, and several .ts files contain logic for completely different modules). This structure suggests intentional obfuscation or evasion of automated analysis. However, a thorough review of the code reveals a legitimate implementation of an AI memory management system with features like sensitive data filtering (index.js), token optimization (AutoClassifier.ts), and memory curation (filter.js). No clear evidence of malicious behavior, such as data exfiltration, credential theft, or unauthorized network access, was found.
Capability Tags
Capability Assessment
Purpose & Capability
Name/description (AI memory system) aligns with the included TypeScript modules (curator, classifier, tagger, deduper, scorer, relation discoverer). The registry declares no required env or binaries, which is consistent with a pure library/instruction package. Minor inconsistency: the registry lists the skill as instruction-only (no install spec) but the SKILL.md contains explicit git clone / npm install instructions and many source files — the skill expects the consumer to fetch and run an external repo rather than being pre-installed by the registry.
Instruction Scope
SKILL.md instructs cloning a GitHub repo and running npm install / build / tests and the included files (DEV_PLAN, test runners) execute shell commands (child_process.exec). That means following the instructions will execute code from an external, unverified repository. The runtime instructions do not ask for unrelated secrets, but they do grant broad discretion to run arbitrary commands (install TypeScript, compile, run tests). This is appropriate for development packages but raises execution risks when done automatically by an agent.
Install Mechanism
There is no formal install spec in the registry metadata; instead the SKILL.md tells users to git clone from https://github.com/cp3d1455926-svg/openclaw-memory.git and run npm install / npm run build. Downloading and running code from a third-party GitHub repo is common but higher-risk than using a vetted package. The GitHub host is a known platform (lower risk than random IPs), but the repo appears to be a personal/unknown account rather than an established organization. The instructions and included test scripts will extract/execute code on disk.
Credentials
The skill declares no required environment variables, credentials, or config paths. The content provided likewise does not request cloud credentials or tokens. This is proportionate for a local library/tooling package. However, test/install scripts will run system commands and potentially install packages — those commands do not request secrets but can run arbitrary code.
Persistence & Privilege
Registry flags show always: false and no special privileges. The package does not request to be force-included or modify other skills or system agent settings. Nothing indicates it will persistently alter agent configuration beyond normal file writes that happen when cloning/building a repo.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install openclaw-memory-master - After installation, invoke the skill by name or use
/openclaw-memory-master - Provide required inputs per the skill's parameter spec and get structured output
Version History
v4.3.0
OpenClaw Memory Master v4.3.0 introduces a major upgrade with a modular, smart memory curation system and extensive new features.
- Added 6 core TypeScript modules: SmartMemoryCurator, AutoClassifier, AutoTagger, DeduplicationEngine, ImportanceScorer, RelationDiscoverer.
- New enterprise-level features: real-time performance monitoring, plugin architecture, and enhanced emotion/tagging capabilities.
- Brand new README and developer documentation describing installation, quick start, API usage, configuration, and core module details.
- Significantly reorganized project structure for modularity and clarity.
- File structure shifted from /src to root-level .ts files for all core logic; legacy v4.2 docs and src files removed.
- Performance and feature details now extensively documented, including core algorithms for classification, tagging, deduplication, and scoring.
v4.2.2
- Bumped version to 4.2.2 in SKILL.md and package.json.
- No functional or feature changes included in this update.
v4.2.1
- Major internal refactor: 31 new files added, 39 legacy files removed, and key architecture files updated.
- Introduced LLM Wiki proactive curation and a new 4-layer OS-level architecture.
- Enhanced features: emotion dimensions, dynamic Top-K, and hybrid search.
- Project description and tags streamlined for clarity.
- Legacy documentation and unused scripts removed for a leaner codebase.
v4.2.0
Major update: Introduces iterative compression, lineage tracking, and major performance gains.
- Added iterative compression: combines new content with prior summaries for efficient accumulation.
- Implemented full memory lineage tracking for genealogy chains.
- Integrates LRU cache and incremental detection, achieving 5.6x faster performance and 72% cache hit rate.
- Added parallel processing for batch compression and structured summary extraction.
- Comprehensive documentation, test results, and migration/test scripts added.
v4.1.1
更新版本号为 4.1.1，修复 slug 冲突问题
v3.0.0-dev
v3.0.0-dev: 实现 4 类记忆模型、时间树结构、5 种检索类型
v4.1.0
# OpenClaw Memory Master v4.1.0## Major ChangesRefactored based on 32 industry best practice notes, implementing:### ✨ LLM Wiki Proactive Curation- Extract structured knowledge from daily conversations- Generate indexes for Projects/People/Decisions/Tasks/Insights/Preferences- Cron scheduled automatic curation### 🏗️ OS-Level 4-Layer Architecture- L1: Short-term Working Memory (Token Optimizer)- L2: Episodic Memory (Daily Memory + Skill Evolution)- L3: Semantic Long-term Memory (MEMORY.md + wiki/*.md)- L4: Procedural Muscle Memory (Skill Distillation)### 💖 Emotion Dimensions (NEW in v4.1)- 8 emotion types: positive/negative/neutral/joy/sadness/anger/surprise/fear/disgust- Emotion intensity (1-5 scale)- Emotion-based filtering### 🎯 Dynamic Top-K (NEW in v4.1)- Intelligent K value adjustment- Token savings: +10%- Adaptive to query complexity### 🔍 Hybrid Search (NEW in v4.1)- Vector + Keyword + Structured retrieval- Cross-validation- Relevance improvement: +17%## Performance Improvements- Token Savings: 70% (+5% from v4.0)- Retrieval Response: 75ms- Memory Loading: 180ms- Accuracy: 85% (+10% from v4.0)## Documentation- Curation Feature Usage Examples- 32 Industry Best Practice Notes Summary- Complete API Reference- Research Report (GitHub/Gitee benchmarks)## AcknowledgmentsBased on research of:- Karpathy - AI Knowledge Base Methodology + LLM Wiki- Anthropic - Claude Code and Skill Design- Generative Agents - Three-Dimensional Scoring- Mem0 - Dynamic Top-K Optimization- MemoryBank - Emotion Dimensions- MemPalace - Palace Architecture + AAAK CompressionCo-developed with Jake.
v3.1.0
Memory-Master 3.1.0 introduces a comprehensive memory enhancement system for OpenClaw.
- 自动捕捉、过滤并压缩重要对话，实现跨会话记忆连续性，避免重启“失忆”
- 支持记忆图谱：实体（人、项目、任务、文件）间的自动关联和可视查询
- 定期自动整理、删除过期、合并相似记忆，保证系统简洁高效
- 丰富手动命令：/load-memory, /save-memory, /memory-status, /memory-graph
- 灵活配置重要性阈值、记忆最大保存天数、定期整理计划等参数
- 注重安全和隐私，仅本地存储、自动过滤敏感信息
Metadata
Frequently Asked Questions
What is Openclaw Memory Master?
AI Memory System with LLM Wiki. It is an AI Agent Skill for Claude Code / OpenClaw, with 234 downloads so far.
How do I install Openclaw Memory Master?
Run "/install openclaw-memory-master" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Openclaw Memory Master free?
Yes, Openclaw Memory Master is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Openclaw Memory Master support?
Openclaw Memory Master is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Openclaw Memory Master?
It is built and maintained by cp3d1455926-svg (@cp3d1455926-svg); the current version is v4.3.0.
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