Compress agent conversations into traceable records across memory files.
npx skills add https://github.com/ZHangZHengEric/Sage --skill memory-organizer
Please help me install this Agent Skill. Skill: memory-organizer Source: https://github.com/ZHangZHengEric/Sage/tree/main/app/skills/memory-organizer Command: npx skills add https://github.com/ZHangZHengEric/Sage --skill memory-organizer
The Memory Organizer helps teams and agents automatically extract, categorize, and consolidate reusable information from dense conversations into a structured memory repository, enabling faster retrieval and knowledge sharing. It ensures that only non-sensitive, prep-for-use insights are moved to long-term memory when explicitly triggered by the user.
对指定 Agent 的对话进行压缩，并在需要时生成记忆落地的输出。
High-intent search queries and answers about installing and using this skill.
You can compress and summarize agent conversations into a knowledge base by triggering this Skill to filter essential messages via API and write traceable records into structured markdown files like MEMORY.md and SOUL.md.
Conversation compression handles privacy sensitivities by validating data before any write operations, ensuring only non-sensitive insights are moved to long-term memory storage when explicitly triggered by the user.
You can route extracted conversation data into specific markdown files by indexing summarized information across USER.md, AGENT.md, MEMORY.md, memory/, IDENTITY.md, and SOUL.md for structured long-term knowledge management.
Yes, the memory organizer requires explicit user triggers to write conversation history, enforcing a safety-first workflow that minimizes unintended data writes and maintains auditability through a detailed memory index under memory/.
Maintaining a memory index for long-term agent knowledge management involves consolidating reusable information into MEMORY.md while storing detailed traceable history under the memory/ directory for auditability.
rohunvoraCompress long-running agent sessions into structured summaries with artifact indexes.
zilliztechStore and retrieve past chatbot conversations across sessions using vector memory.
ghufronbagaskaraIngest raw sources into structured, interlinked Markdown wiki pages with automated cross-referencing.
eddmannStore and retrieve atomic notes with semantic connections in SQLite.
