Memory Reflect

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:

# 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 notes
read_note(identifier="memory/2026-02-27")
read_note(identifier="memory/2026-02-26")

# Check active tasks
search_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• Remove or update outdated entries that the new information supersedes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:

## 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.