Session Memory

Your agent forgets everything after compaction? This fixes it. Built by the AI Advantage community — the world's leading AI learning platform (aiadvantage.ai...

This skill appears to do what it claims: convert local session logs to Markdown, build a glossary, and suggest memory-aware cron prompts. Before installing/running: 1) Review the exact paths used by the scripts (session-to-memory.py currently targets ~/.openclaw/agents/main/sessions and writes to ~/.openclaw/workspace/memory); adjust if you store sessions elsewhere or have multiple agents. 2) Recognize privacy risk: session logs and cron payloads frequently contain sensitive data (API keys, personal data, passwords). The scripts will consolidate those into memory/*.md and (per SKILL.md) may be vectorized by memory_search — ensure the vector store and memory files are stored with proper access controls or sanitize secrets first. 3) Test on a copy of your data or a limited agent (use --new or --force cautiously) before enabling cron jobs broadly. 4) If you want to limit scope, run the scripts on a subset of session files or edit the scripts to filter/exclude patterns (e.g., API keys) before indexing. 5) If you need higher assurance, ask the author for explicit documentation of which fields are read and how to opt out of indexing particular sessions.

Type: OpenClaw Skill Name: sessionmemory Version: 1.3.0 The session-memory skill is a legitimate utility designed to create a multi-layer memory system for OpenClaw agents by indexing session transcripts. It includes Python scripts (session-to-memory.py, build-glossary.py, and cron-optimizer.py) that convert local JSONL logs into searchable Markdown and generate a structured glossary of people, projects, and decisions. The code operates entirely locally within standard OpenClaw directories (~/.openclaw/), contains no network calls or data exfiltration logic, and includes safety features like stripping untrusted metadata from logs during processing.