| 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".
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| 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
- Creates directory structure and stub files via a bash script (no network calls, no env reads, no dependencies)
- 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
