Search memories from earlier OpenCode sessions in this repository. Use it when earlier work may already explain the code, error, decision, or command you need,
复制下面这句话,粘贴给 Claude Code、Codex、Cursor 等 AI 编程工具,它会读取安装说明并在你确认后完成安装。
请阅读 https://ai.atlankj.com/install/asset/gh-mem0-context-loader-a30841fba4ef ,按照其中的说明把「mem0-context-loader」安装到你(当前 AI 工具)中。执行前先告诉我将运行的命令和写入的位置,等我确认。
查看 AI 将读取的安装说明正在读取 GitHub 原文…
内容来自 GitHub 原始文件,由原作者维护。在 GitHub 查看
Pre-fetches relevant memories to prime context before working on a task.
Extract topics from current message/task. Identify: file paths, module names, feature areas, error patterns.
Call search_memories once with a focused question about the task: filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}, top_k=10.
Output compact context block (max 10 memories):
context-loader: loaded <N> memories for "<task summary>"
- [decision] <content> [mem0:<short_id>]
- [convention] <content> [mem0:<short_id>]
- [anti_pattern] <content> [mem0:<short_id>]
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like bold, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.