Memory Reflect

basicmachines-co/basic-memory-skills/memory-reflect

作者 basicmachines-co6d2b1d426d0dacf020aef45f029768c9d8c1e5e5無授權條款24 個星標收錄於 2026年10月9日更新於 2026年10月9日儲存庫5 個月前更新

Sleep-time memory reflection: review recent conversations and daily notes, extract insights, and consolidate into long-term memory. Use when triggered by cron, heartbeat, or explicit request to reflect on recent activity. Runs as background processing to improve memory quality over time.

僅含說明
AI 產生的概覽

回顧近期對話與每日筆記,擷取有價值的見解並整合到長期記憶中。

功能
此技能定義了一套背景反思流程:蒐集近期修改的筆記、每日記錄與進行中的任務,並逐項評估其長期價值。它會把決策、經驗教訓、偏好與關係細節整合寫入長期記憶檔案,更新或移除過時條目,並在當天的每日筆記中附加一則簡短的反思記錄。它也會檢查檔案系統問題,例如遞迴巢狀、孤立檔案或內容膨脹。
適用情境
適合做為週期性背景任務執行,例如透過排程或心跳機制,或在被明確要求反思、整合或回顧近期記憶時使用。它也用於上下文視窗壓縮事件之後。
執行需求
不隨附指令碼,僅為說明文件。它需要存取記憶工具,用於尋找近期活動、讀取與搜尋筆記,以及寫入長期記憶檔案與每日筆記檔案。

Memory Reflect

Review recent activity and consolidate valuable insights into long-term memory.

Inspired by sleep-time compute — the idea that memory formation happens best between active sessions, not during them.

When to Run

  • Cron/heartbeat: Schedule as a periodic background task (recommended: 1-2x daily)
  • On demand: User asks to reflect, consolidate, or review recent memory
  • Post-compaction: After context window compaction events

Process

1. Gather Recent Material

Find what changed recently, then read the relevant files:

python
# Find recently modified notes — use json format for the complete list# (text format truncates to ~5 items in the summary)recent_activity(timeframe="2d", output_format="json")
# Read specific daily notesread_note(identifier="memory/2026-02-27")read_note(identifier="memory/2026-02-26")
# Check active taskssearch_notes(note_types=["task"], status="active")

2. Evaluate What Matters

For each piece of information, ask:

  • Is this a decision that affects future work? → Keep
  • Is this a lesson learned or mistake to avoid? → Keep
  • Is this a preference or working style insight? → Keep
  • Is this a relationship detail (who does what, contact info)? → Keep
  • Is this transient (weather checked, heartbeat ran, routine task)? → Skip
  • Is this already captured in MEMORY.md or another long-term file? → Skip

3. Update Long-Term Memory

Write consolidated insights to MEMORY.md following its existing structure:

  • Add new sections or update existing ones
  • Use concise, factual language
  • Include dates for temporal context
  • Remove or update outdated entries that the new information supersedes

4. Log the Reflection

Append a brief entry to today's daily note:

markdown
## Reflection (HH:MM)- Reviewed: [list of files reviewed]- Added to MEMORY.md: [brief summary of what was consolidated]- Removed/updated: [anything cleaned up]

Guidelines

  • Be selective. The goal is distillation, not duplication. MEMORY.md should be curated wisdom, not a copy of daily notes.
  • Preserve voice. If the agent has a personality/soul file, reflections should match that voice.
  • Don't delete daily notes. They're the raw record. Reflection extracts from them; it doesn't replace them.
  • Merge, don't append. If MEMORY.md already has a section about a topic, update it in place rather than adding a duplicate entry.
  • Flag uncertainty. If something seems important but you're not sure, add it with a note like "(needs confirmation)" rather than skipping it entirely.
  • Restructure over time. If MEMORY.md is a chronological dump, restructure it into topical sections during reflection. Curated knowledge > raw logs.
  • Check for filesystem issues. Look for recursive nesting (memory/memory/memory/...), orphaned files, or bloat while gathering material.

來源與署名

來源:basicmachines-co/basic-memory-skills位於memory-reflect提交6d2b1d4

授權條款: 無授權條款

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