Review auto-memory entries and propose promotions to OPENSPACE.md, OPENSPACE.local.md, or retained auto-memory topics; detect duplicates, stale facts, conflicts
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-remember-18fe742e9194 ,按照其中的说明把「remember」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
Review the user's memory landscape and produce a clear report of proposed changes, grouped by action type. Do not apply changes until the user approves them.
Read OPENSPACE.md and OPENSPACE.local.md from the project root if they exist. Review auto-memory from the memory section and MEMORY.md; use memory_read for topic files when needed. Note team memory only as unavailable unless this deployment explicitly has a team memory backend.
Success criteria: you have the contents of all available memory layers and can compare them.
For each substantive auto-memory entry, determine the best destination:
| Destination | What belongs there | Examples |
|---|---|---|
OPENSPACE.md | Project conventions and instructions for OpenSpace that all contributors should follow | use uv not raw pip; API routes use kebab-case; test command is pytest; prefer functional style |
OPENSPACE.local.md | Personal instructions specific to this user or machine, not applicable to other contributors | concise responses; explain tradeoffs; do not auto-commit; run tests before committing |
| Auto-memory topic | Durable cross-session user, feedback, project, or reference memory that does not belong in static project instructions | user role, durable feedback, external reference pointers, uncertain but useful context |
| Stay put | Working notes, temporary context, or entries that do not clearly fit elsewhere | session-specific observations, uncertain patterns |
Important distinctions:
OPENSPACE.md and OPENSPACE.local.md contain instructions for the agent, not arbitrary external-tool preferences.Success criteria: each entry has a proposed destination or is flagged as ambiguous.
Scan across all layers for:
OPENSPACE.md or OPENSPACE.local.md.MEMORY.md entries that contain content that belongs in a topic file.Success criteria: all cross-layer issues are identified.
Output a structured report grouped by action type:
If auto-memory is empty, say so and offer to review OPENSPACE.md for cleanup.