Conversation Memory Sync

Automatically syncs and maintains detailed conversation logs and activity digests across agent sessions for persistent memory and context recall.

Never forget a conversation again. Auto-generates CONVERSATION_LOG.md and ACTIVITY_DIGEST.md from all agent session transcripts.

Use when: you want persistent conversation memory across agent sessions, or when agents keep forgetting past decisions and promises.

What it does

Solves the #1 problem with AI agents: they forget everything between sessions.

This skill includes two Python scripts that run via cron:

1. sync_conversation_logs.py — Extracts the last 300 messages from every agent session and writes them to CONVERSATION_LOG.md in each agent's workspace. Full messages with timestamps.

2. sync_activity_digest.py — Creates a compact 1-line-per-action summary in ACTIVITY_DIGEST.md. Ultra-lightweight (~10-20KB per agent).

Setup

1. Copy the scripts to your workspace
2. Add a cron job: */30 * * * * python3 /path/to/sync_conversation_logs.py && python3 /path/to/sync_activity_digest.py
3. Add to each agent's SOUL.md or AGENTS.md:

   text

   At EVERY session start, read CONVERSATION_LOG.md and ACTIVITY_DIGEST.md before doing anything else.
   

What gets captured

• All user ↔ agent messages (Telegram, Discord, etc.)
• Cron job outputs and results
• Decisions, promises, task assignments
• Timestamps for everything

What gets filtered

• Heartbeat noise (HEARTBEAT_OK)
• Empty messages
• System metadata

File sizes

• CONVERSATION_LOG.md: ~15-20KB per agent (300 messages)
• ACTIVITY_DIGEST.md: ~5-20KB per agent (150 entries, 1 line each)
• Total for 12 agents: ~110KB — zero performance impact

Requirements

• Python 3.8+
• OpenClaw with session transcripts (default location: ~/.openclaw/agents//sessions/.jsonl)

Tags

memory, persistence, conversation, logging, multi-agent, session, context, recall