agent-memory-setup-v2

name	agent-memory-setup-v2
description	Create a 3-tier memory directory structure (HOT/WARM/COLD) for OpenClaw agents and configure the built-in memory-core plugin to use Google Gemini Embeddings 2 (gemini-embedding-2-preview) for semantic memory search. Creates memory/ directories and stub files only — no code execution or external API calls from the setup script. After setup, the agent's memory_search tool uses Gemini's cloud embedding API to index memory files. Requires a free Google Gemini API key. Use when setting up a new agent's memory system or asked about semantic memory search. Triggers on "set up memory", "memory setup", "agent memory", "gemini memory", "semantic search memory", "onboard new agent".
allowed-tools	*

Permission Setup Review

python scripts/_wildcard_placeholder.py is an optional setup helper for the Agent Memory Setup v2 — Gemini Embeddings 2 skill. It may apply broad filesystem permissions for compatibility. Show the target paths and permission mode, explain the risk, and prefer a narrower mode when shared write access is not needed.

Agent Memory Setup v2 — Gemini Embeddings 2

Create a 3-tier memory directory structure for OpenClaw agents and configure semantic search using Google Gemini Embeddings 2.

What This Skill Does

1. Creates directory structure and stub files via a bash script (no network calls, no env reads, no dependencies)
2. Provides configuration instructions for openclaw.json to enable Gemini-based memory search

Privacy Notice

⚠️ After setup, the agent's memory_search tool sends memory file content to Google's Gemini embedding API for vectorization. This is how semantic search works — files must be embedded to be searchable. The setup script itself makes no external calls.

Prerequisite

Google Gemini API key — free at https://aistudio.google.com/apikey

Setup

Step 1: Create directory structure

bash scripts/setup_memory_v2.sh /path/to/agent/workspace

Creates: memory/, memory/hot/, memory/warm/, stub .md files, heartbeat-state.json.

Step 2: Configure openclaw.json

Add under agents.defaults:

"memorySearch": { "provider": "gemini" },
"compaction": { "mode": "safeguard" },
"contextPruning": { "mode": "cache-ttl", "ttl": "1h" },
"heartbeat": { "every": "1h" }

Set API key: export GEMINI_API_KEY=your-key

Enable plugin: "lossless-claw": { "enabled": true }

Step 3: Restart

openclaw gateway restart

Memory Tiers

• 🔥 HOT (memory/hot/HOT_MEMORY.md) — Active session state, pending actions
• 🌡️ WARM (memory/warm/WARM_MEMORY.md) — Stable preferences, references
• ❄️ COLD (MEMORY.md) — Long-term milestones and distilled lessons

Optional Plugin

Lossless Claw (@martian-engineering/lossless-claw) — compacts old context into expandable summaries to prevent amnesia. Install separately: openclaw plugins install @martian-engineering/lossless-claw