reason-machines/trending-skills1 file

Memory Lancedb Pro Openclaw

Expert skill for memory-lancedb-pro — a production-grade LanceDB-backed long-term memory plugin for OpenClaw agents with hybrid retrieval, cross-encoder reranking, multi-scope isolation, and smart auto-capture.

Specification
Skill ID
reason-machines/trending-skills/memory-lancedb-pro-openclaw
Publisher
reason-machines
Repository
trending-skills
Installs
0
Files
1
Synced
Sep 23, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

reason-machines/trending-skills/memory-lancedb-pro-openclawInstalls these files
  • SKILL.md

What this skill tells the agent

memory-lancedb-pro OpenClaw Plugin

Skill by ara.so — Daily 2026 Skills collection.

memory-lancedb-pro is a production-grade long-term memory plugin for OpenClaw agents. It stores preferences, decisions, and project context in a local LanceDB vector database and automatically recalls relevant memories before each agent reply. Key features: hybrid retrieval (vector + BM25 full-text), cross-encoder reranking, LLM-powered smart extraction (6 categories), Weibull decay-based forgetting, multi-scope isolation (agent/user/project), and a full management CLI.


Installation

Option A: One-Click Setup Script (Recommended)

curl -fsSL https://raw.githubusercontent.com/CortexReach/toolbox/main/memory-lancedb-pro-setup/setup-memory.sh -o setup-memory.sh
bash setup-memory.sh

Flags:

bash setup-memory.sh --dry-run       # Preview changes only
bash setup-memory.sh --beta          # Include pre-release versions
bash setup-memory.sh --uninstall     # Revert config and remove plugin
bash setup-memory.sh --selfcheck-only  # Health checks, no changes

The script handles fresh installs, upgrades from git-cloned versions, invalid config fields, broken CLI fallback, and provider presets (Jina, DashScope, SiliconFlow, OpenAI, Ollama).

Option B: OpenClaw CLI

openclaw plugins install memory-lancedb-pro@beta

Option C: npm

npm i memory-lancedb-pro@beta
Critical: When installing via npm, you must add the plugin's absolute install path to plugins.load.paths in openclaw.json. This is the most common setup issue.

Minimal Configuration (openclaw.json)

{
  "plugins": {
    "load": {
      "paths": ["/absolute/path/to/node_modules/memory-lancedb-pro"]
    },
    "slots": { "memory": "memory-lancedb-pro" },
    "entries": {
      "memory-lancedb-pro": {
        "enabled": true,
        "config": {
          "embedding": {
            "provider": "openai-compatible",
            "apiKey": "${OPENAI_API_KEY}",
            "model": "text-embedding-3-small"
          },
          "autoCapture": true,
          "autoRecall": true,
          "smartExtraction": true,
          "extractMinMessages": 2,
          "extractMaxChars": 8000,
          "sessionMemory": { "enabled": false }
        }
      }
    }
  }
}

Why these defaults:

  • autoCapture + smartExtraction → agent learns from conversations automatically, no manual calls needed
  • autoRecall → memories injected before each reply
  • extractMinMessages: 2 → triggers in normal two-turn chats
  • sessionMemory.enabled: false → avoids polluting retrieval with session summaries early on

Full Production Configuration

{
  "plugins": {
    "slots": { "memory": "memory-lancedb-pro" },
    "entries": {
      "memory-lancedb-pro": {
        "enabled": true,
        "config": {
          "embedding": {
            "provider": "openai-compatible",
            "apiKey": "${OPENAI_API_KEY}",
            "model": "text-embedding-3-small",
            "baseURL": "https://api.openai.com/v1"
          },
          "reranker": {
            "provider": "jina",
            "apiKey": "${JINA_API_KEY}",
            "model": "jina-reranker-v2-base-multilingual"
          },
          "extraction": {
            "provider": "openai-compatible",
            "apiKey": "${OPENAI_API_KEY}",
            "model": "gpt-4o-mini"
          },
          "autoCapture": true,
          "captureAssistant": false,
          "autoRecall": true,
          "smartExtraction": true,
          "extractMinMessages": 2,
          "extractMaxChars": 8000,
          "enableManagementTools": true,
          "retrieval": {
            "mode": "hybrid",
            "vectorWeight": 0.7,
            "bm25Weight": 0.3,
            "topK": 10
          },
          "rerank": {
            "enabled": true,
            "type": "cross-encoder",
            "candidatePoolSize": 12,
            "minScore": 0.6,
            "hardMinScore": 0.62
          },
          "decay": {
            "enabled": true,
            "model": "weibull",
            "halfLifeDays": 30
          },
          "sessionMemory": { "enabled": false },
          "scopes": {
            "agent": true,
            "user": true,
            "project": true
          }
        }
      }
    }
  }
}

Provider Options for Embedding

Providerprovider valueNotes
OpenAI / compatible"openai-compatible"Requires apiKey, optional baseURL
Jina"jina"Requires apiKey
Gemini"gemini"Requires apiKey
Ollama"ollama"Local, zero API cost, set baseURL
DashScope"dashscope"Requires apiKey
SiliconFlow"siliconflow"Requires apiKey, free reranker tier

Deployment Plans

Full Power (Jina + OpenAI):

{
  "embedding": { "provider": "jina", "apiKey": "${JINA_API_KEY}", "model": "jina-embeddings-v3" },
  "reranker": { "provider": "jina", "apiKey": "${JINA_API_KEY}", "model": "jina-reranker-v2-base-multilingual" },
  "extraction": { "provider": "openai-compatible", "apiKey": "${OPENAI_API_KEY}", "model": "gpt-4o-mini" }
}

Budget (SiliconFlow free reranker):

{
  "embedding": { "provider": "openai-compatible", "apiKey": "${OPENAI_API_KEY}", "model": "text-embedding-3-small" },
  "reranker": { "provider": "siliconflow", "apiKey": "${SILICONFLOW_API_KEY}", "model": "BAAI/bge-reranker-v2-m3" },
  "extraction": { "provider": "openai-compatible", "apiKey": "${OPENAI_API_KEY}", "model": "gpt-4o-mini" }
}

Fully Local (Ollama, zero API cost):

{
  "embedding": { "provider": "ollama", "baseURL": "http://localhost:11434", "model": "nomic-embed-text" },
  "extraction": { "provider": "ollama", "baseURL": "http://localhost:11434", "model": "llama3" }
}

CLI Reference

Validate config and restart after any changes:

openclaw config validate
openclaw gateway restart
openclaw logs --follow --plain | grep "memory-lancedb-pro"

Expected startup log output:

memory-lancedb-pro: smart extraction enabled
memory-lancedb-pro@1.x.x: plugin registered

Memory Management CLI

# Stats overview
openclaw memory-pro stats

# List memories (with optional scope/filter)
openclaw memory-pro list
openclaw memory-pro list --scope user --limit 20
openclaw memory-pro list --filter "typescript"

# Search memories
openclaw memory-pro search "coding preferences"
openclaw memory-pro search "database decisions" --scope project

# Delete a memory by ID
openclaw memory-pro forget <memory-id>

# Export memories (for backup or migration)
openclaw memory-pro export --scope global --output memories-backup.json
openclaw memory-pro export --scope user --output user-memories.json

# Import memories
openclaw memory-pro import --input memories-backup.json

# Upgrade schema (when upgrading plugin versions)
openclaw memory-pro upgrade --dry-run   # Preview first
openclaw memory-pro upgrade             # Run upgrade

# Plugin info
openclaw plugins info memory-lancedb-pro

MCP Tool API

The plugin exposes MCP tools to the agent. Core tools are always available; management tools require enableManagementTools: true in config.

Core Tools (always available)

memory_recall

Retrieve relevant memories for a query.

// Agent usage pattern
const results = await memory_recall({
  query: "user's preferred code style",
  scope: "user",        // "agent" | "user" | "project" | "global"
  topK: 5
});
memory_store

Manually store a memory.

await memory_store({
  content: "User prefers tabs over spaces, always wants error handling",
  category: "preference",   // "profile" | "preference" | "entity" | "event" | "case" | "pattern"
  scope: "user",
  tags: ["coding-style", "typescript"]
});
memory_forget

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