general-agentic-memory
CommunityDual-agent memory for deeper AI agent reasoning.
Authoryuyijiong
Version1.0.0
Installs0
System Documentation
What problem does it solve?
The GAM approach delivers Just-in-Time memory optimization and iterative retrieval for AI agents, enabling structured long-term memory and guided research at query time.
Core Features & Use Cases
- Just-in-Time memory construction: MemoryAgent builds abstracts from documents and stores associated pages for on-demand retrieval.
- Iterative deep research: ResearchAgent performs planning, search, integration, and reflection to answer complex, multi-hop questions.
- Flexible retrieval: supports keyword (BM25), vector (dense), and page-index retrieval to cover diverse information needs.
- Use cases: building agents that require deep research over stored memories, multi-hop QA, or context-rich assistants that reason over context.
Quick Start
Trigger the GAM skill with a query that requires deep research over stored memories to produce an integrated answer.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: general-agentic-memory Download link: https://github.com/yuyijiong/paper-to-skill/archive/main.zip#general-agentic-memory Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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