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SKILL.md
npx skills add reason-machines/trending-skills --skill 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.
npx skills add reason-machines/trending-skills --skill memory-lancedb-pro-openclaw
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.
Flags:
The script handles fresh installs, upgrades from git-cloned versions, invalid config fields, broken CLI fallback, and provider presets (Jina, DashScope, SiliconFlow, OpenAI, Ollama).
Critical: When installing via npm, you must add the plugin's absolute install path to
plugins.load.pathsinopenclaw.json. This is the most common setup issue.
openclaw.json)Why these defaults:
autoCapture + smartExtraction → agent learns from conversations automatically, no manual calls neededautoRecall → memories injected before each replyextractMinMessages: 2 → triggers in normal two-turn chatssessionMemory.enabled: false → avoids polluting retrieval with session summaries early on| Provider | provider value | Notes |
|---|---|---|
| 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 |
Full Power (Jina + OpenAI):
Budget (SiliconFlow free reranker):
Fully Local (Ollama, zero API cost):
Validate config and restart after any changes:
Expected startup log output:
The plugin exposes MCP tools to the agent. Core tools are always available; management tools require enableManagementTools: true in config.
memory_recallRetrieve relevant memories for a query.
memory_storeManually store a memory.
memory_forgetDelete a specific memory by ID.
memory_updateUpdate an existing memory.
enableManagementTools: true)memory_statsmemory_listself_improvement_logLog an agent learning event for meta-improvement tracking.
self_improvement_extract_skillExtract a reusable pattern from a conversation.
self_improvement_reviewReview and consolidate recent self-improvement logs.
When smartExtraction: true, the LLM automatically classifies memories into:
| Category | What gets stored | Example |
|---|---|---|
profile | User identity, background | "User is a senior TypeScript developer" |
preference | Style, tool, workflow choices | "Prefers functional programming patterns" |
entity | Projects, people, systems | "Project 'Falcon' uses PostgreSQL + Redis" |
event | Decisions made, things that happened | "Chose Vite over webpack on 2026-02-15" |
case | Solutions to specific problems | "Fixed CORS by adding proxy in vite.config.ts" |
pattern | Recurring behaviors, habits | "Always asks for tests before implementation" |
With retrieval.mode: "hybrid", every recall runs:
vectorWeight, default 0.7)bm25Weight, default 0.3)candidatePoolSize candidates reranked by a cross-encoder modelhardMinScore are droppedRetrieval mode options:
"vector" — pure semantic search only"bm25" — pure keyword search only"hybrid" — both fused (recommended)Scopes let you isolate memories by context. Enabling all three gives maximum flexibility:
When recalling, specify scope to narrow results:
Memories naturally fade over time. The decay model prevents stale memories from polluting retrieval.
See CHANGELOG-v1.1.0.md in the repo for behavior changes and upgrade rationale.
Common causes:
plugins.load.paths (must be absolute when using npm install)plugins.slots.memory not set to "memory-lancedb-pro"plugins.entriesautoRecall not injecting memoriesBy default autoRecall is false in some versions — explicitly set it to true:
Also confirm the plugin is bound to the memory slot, not just loaded.
extractMinMessages — must be ≥ number of turns in the conversation (set to 2 for normal chats)extractMaxChars — very long contexts may be truncated; increase to 12000 if neededapiKey and reachable endpointopenclaw logs --follow --plain | grep "extraction"retrieval.mode is "hybrid" not "bm25" alone (BM25 requires indexed content)rerank.hardMinScore temporarily (try 0.4) to see if results exist but are being filteredEnsure env vars are exported in the shell that runs OpenClaw, or use a .env file loaded by your process manager. The ${VAR} syntax in openclaw.json is resolved at startup.
If using OpenClaw's Telegram integration, send this to the bot to auto-configure:
openclaw plugins install memory-lancedb-pro@betanpm i memory-lancedb-pro@beta{
"plugins": {
"load": {
"paths": ["/absolute/path/to/node_modules/memory-lancedb-pro"]
},
"slots": { "memory": "memory-lancedb-pro" },
"entries": {
"memory-lancedb-pro": {
"enabled": true,
"config": {
"embedding": {
"provider": "openai-compatible",
"apiKey": "${OPENAI_API_KEY}",
"model": "text-embedding-3-small"
},
"autoCapture": true,
"autoRecall": true,
"smartExtraction": true,
"extractMinMessages": 2,
"extractMaxChars": 8000,
"sessionMemory": { "enabled": false }
}
}
}
}
}{
"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": "${OPENAI_API_KEY}",
"model": "gpt-4o-mini"
},
"autoCapture": true,
"captureAssistant": false,
"autoRecall": true,
"smartExtraction": true,
"extractMinMessages": 2,
"extractMaxChars": 8000,
"enableManagementTools": true,
"retrieval": {
"mode": "hybrid",
"vectorWeight": 0.7,
"bm25Weight": 0.3,
"topK": 10
},
"rerank": {
"enabled": true,
"type": "cross-encoder",
"candidatePoolSize": 12,
"minScore": 0.6,
"hardMinScore": 0.62
},
"decay": {
"enabled": true,
"model": "weibull",
"halfLifeDays": 30
},
"sessionMemory": { "enabled": false },
"scopes": {
"agent": true,
"user": true,
"project": true
}
}
}
}
}
}{
"embedding": { "provider": "jina", "apiKey": "${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" }
}{
"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" }
}{
"embedding": { "provider": "ollama", "baseURL": "http://localhost:11434", "model": "nomic-embed-text" },
"extraction": { "provider": "ollama", "baseURL": "http://localhost:11434", "model": "llama3" }
}openclaw config validate
openclaw gateway restart
openclaw logs --follow --plain | grep "memory-lancedb-pro"memory-lancedb-pro: smart extraction enabled
memory-lancedb-pro@1.x.x: plugin registered# 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// Agent usage pattern
const results = await memory_recall({
query: "user's preferred code style",
scope: "user", // "agent" | "user" | "project" | "global"
topK: 5
});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"]
});await memory_forget({ id: "mem_abc123" });await memory_update({
id: "mem_abc123",
content: "User now prefers 2-space indentation (changed from tabs on 2026-03-01)",
category: "preference"
});const stats = await memory_stats({ scope: "global" });
// Returns: total count, category breakdown, decay stats, db sizeconst list = await memory_list({ scope: "user", limit: 20, offset: 0 });await self_improvement_log({
event: "user corrected indentation preference",
context: "User asked me to switch from tabs to spaces",
improvement: "Updated coding-style preference memory"
});await self_improvement_extract_skill({
conversation: "...",
domain: "code-review",
skillName: "typescript-strict-mode-setup"
});await self_improvement_review({ days: 7 });"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
}"scopes": {
"agent": true, // Memories specific to this agent instance
"user": true, // Memories tied to a user identity
"project": true // Memories tied to a project/workspace
}// Get only project-level memories
await memory_recall({ query: "database choices", scope: "project" });
// Get user preferences across all agents
await memory_recall({ query: "coding style", scope: "user" });
// Global recall across all scopes
await memory_recall({ query: "error handling patterns", scope: "global" });"decay": {
"enabled": true,
"model": "weibull",
"halfLifeDays": 30
}# 1. Backup first — always
openclaw memory-pro export --scope global --output memories-backup-$(date +%Y%m%d).json
# 2. Preview schema changes
openclaw memory-pro upgrade --dry-run
# 3. Run the upgrade
openclaw memory-pro upgrade
# 4. Verify
openclaw memory-pro stats# Check plugin is recognized
openclaw plugins info memory-lancedb-pro
# Validate config (catches JSON errors, unknown fields)
openclaw config validate
# Check logs for registration
openclaw logs --follow --plain | grep "memory-lancedb-pro""autoRecall": true# Clear jiti transpile cache
rm -rf ~/.openclaw/.cache/jiti
openclaw gateway restartexport OPENAI_API_KEY="sk-..."
export JINA_API_KEY="jina_..."
openclaw gateway restartHelp me connect this memory plugin with the most user-friendly configuration:
https://github.com/CortexReach/memory-lancedb-pro
Requirements:
1. Set it as the only active memory plugin
2. Use Jina for embedding
3. Use Jina for reranker
4. Use gpt-4o-mini for the smart-extraction LLM
5. Enable autoCapture, autoRecall, smartExtraction
6. extractMinMessages=2
7. sessionMemory.enabled=false
8. captureAssistant=false
9. retrieval mode=hybrid, vectorWeight=0.7, bm25Weight=0.3
10. rerank=cross-encoder, candidatePoolSize=12, minScore=0.6, hardMinScore=0.62
11. Generate the final openclaw.json config directly, not just an explanation