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phernandez

Memory Reflect

by Paul Hernandez · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install memory-reflect
Description
Sleep-time memory reflection: review recent conversations and daily notes, extract insights, and consolidate into long-term memory. Use when triggered by cro...
README (SKILL.md)

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  • Remove or update outdated entries that the new information supersedes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.
Usage Guidance
This skill appears coherent and does what it says: read recent notes, distill insights, and update MEMORY.md and today's daily note. Before installing, decide and confirm: (1) Where are the notes/MEMORY.md/personality files stored in your environment and that the agent should legitimately have read/write access there? (2) Do you want automatic writes, or should the agent produce proposed edits for your review before committing? (3) Ensure notes do not contain secrets or sensitive credentials the agent would read; if they do, restrict access or sanitize content. (4) Back up MEMORY.md/daily notes before enabling automated edits. (5) If you are concerned about autonomous changes, consider disabling autonomous invocation or requiring an explicit user approval step in your agent’s runtime policy. If you want a deeper check, provide the platform mapping for functions like recent_activity/read_note/search_notes so I can confirm they only touch the intended storage locations.
Capability Analysis
Type: OpenClaw Skill Name: memory-reflect Version: 0.1.0 The memory-reflect skill bundle is a standard utility designed for an AI agent to consolidate daily notes and recent activity into a long-term memory file (MEMORY.md). It uses internal functions like recent_activity and read_note to process local files and follows logical guidelines for data distillation without any evidence of data exfiltration, malicious execution, or unauthorized access.
Capability Assessment
Purpose & Capability
The name/description (sleep-time memory reflection) matches the instructions: gather recent notes, evaluate, and update MEMORY.md and daily notes. It does not ask for unrelated credentials, binaries, or system-wide access.
Instruction Scope
Instructions explicitly tell the agent to read recent notes, specific daily notes (e.g., memory/2026-02-27), search task notes, update MEMORY.md, and append today's daily note. This is expected for the feature, but it does mean the agent will read and write user note files and any referenced 'personality/soul' file. Confirm where those files live and whether you want automated writes vs. draft-for-user-review.
Install Mechanism
Instruction-only skill with no install spec and no code files; nothing is written to disk by an installer. Low install risk.
Credentials
The skill requires no environment variables, credentials, or config paths. The file reads/writes it requests are proportional to its purpose (note review and MEMORY.md updates).
Persistence & Privilege
always is false and autonomous invocation is allowed by default (normal). The skill does instruct writing to user-owned files (MEMORY.md and daily notes), which is expected for this function but should be governed by the agent's file-permission and review policy.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install memory-reflect
  3. After installation, invoke the skill by name or use /memory-reflect
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Initial release of memory-reflect skill. - Enables periodic or on-demand review of recent conversations and daily notes to extract and consolidate valuable insights into long-term memory. - Inspired by sleep-time memory processes; runs as a background task without interrupting active sessions. - Outlines a step-by-step workflow to gather recent activity, evaluate information, update MEMORY.md, and log the reflection. - Emphasizes selective curation, maintaining agent voice, and restructuring knowledge over time for better memory quality. - Includes guidelines to prevent duplication, handle uncertainty, and manage filesystem hygiene during reflection.
Metadata
Slug memory-reflect
Version 0.1.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Memory Reflect?

Sleep-time memory reflection: review recent conversations and daily notes, extract insights, and consolidate into long-term memory. Use when triggered by cro... It is an AI Agent Skill for Claude Code / OpenClaw, with 324 downloads so far.

How do I install Memory Reflect?

Run "/install memory-reflect" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Memory Reflect free?

Yes, Memory Reflect is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Memory Reflect support?

Memory Reflect is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Memory Reflect?

It is built and maintained by Paul Hernandez (@phernandez); the current version is v0.1.0.

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