This entry duplicates memory-upgrade, which is the one we list in search.

memory-upgrade

Diagnose and fix broken memory search in OpenClaw.

IndexedMIT

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About

Diagnose and fix broken memory search in OpenClaw. Enables local embeddings, hybrid search (BM25+vector), session transcript indexing, MMR diversity, and temporal decay — all running locally with zero API keys. Use when: memory_search returns empty results, agent has poor cross-session recall, user wants to upgrade their memory system, or after a fresh OpenClaw install.

Use cases: backend, agent-building

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What's inside

Skill name: memory-upgrade
Description: Diagnose and fix broken memory search in OpenClaw. Enables local embeddings, hybrid search (BM25+vector), session transcript indexing, MMR diversity, and temporal decay — all running locally with zero API keys. Use when: memory_search returns empty results, agent has poor cross-session recall, user wants to upgrade their memory system, or after a fresh OpenClaw install.
License: MIT
Instructions: 59 lines in SKILL.md · view on GitHub

Before installing

Ships executable scripts

Files (6)

SKILL.md
configure.sh · scripts/
diagnose.sh · scripts/
organize.sh · scripts/
tag.sh · scripts/
verify.sh · scripts/

SKILL.md (first lines)

# Memory Upgrade

Most OpenClaw installs have **broken memory search** — the `memory_search` tool returns empty results because no embedding provider is configured. OpenClaw auto-detects OpenAI → Google → Voyage keys; if none exist, embeddings stay disabled silently.

This skill fixes it with fully local inference. No API keys. No data leaves the machine.

## Quick Start

```bash
# 1. Diagnose
bash scripts/diagnose.sh

# 2. Fix (patches openclaw.json, restart [REDACTED] after)
bash scripts/configure.sh

# 3. Restart [REDACTED]
openclaw [REDACTED] restart

# 4. Verify (waits for indexing, runs test query)
bash scripts/verify.sh
```

## Optional Enhancements

```bash
# Organize memory files into clean directory structure
bash scripts/organize.sh

# Add YAML frontmatter tags to untagged files
bash scripts/tag.sh
```

## What Gets Enabled

| Feature | Details |
|---------|---------|
| **Local embeddings** | embeddinggemma-300m (~328MB GGUF, auto-downloads) |
| **Hybrid search** | BM25 keyword + vector semantic (70/30 weight) |
| **Session transcripts** | Past conversations become searchable |
| **MMR diversity** | Reduces duplicate/overlapping results (λ=0.7) |
| **Temporal decay** | Recent memories rank higher (30-day half-life) |
| **Embedding cache** | 50k entries, avoids re-embedding unchanged text |
| **File watcher** | Auto-reindexes when memory files change |

## How It Works

- Patches `agents.defaults.memorySearch` in `openclaw.json`
- Uses `node-llama-cpp` (ships with OpenClaw) for local embeddings
- Vector search via `sqlite-vec` (ships with OpenClaw)
- No external dependencies required

## Notes

- First search after restart may be slow (model loads into memory)
- Initial indexing takes 30-120s depending on file count
- Embedding model runs on CPU (ARM/x86), ~768-dim vectors
- Compatible with existing memory files — no migration needed

From profbernardoj/travelclaw.org, MIT.

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Stars: 0
Forks: 0
Open issues: 0
Last commit (this folder): May 28, 2026 (5 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License: MIT
Repository: github.com/profbernardoj/travelclaw.org
First seen: Oct 24, 2026
Last checked: Oct 24, 2026
Source: GitHub github-graphql

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Cite this page

memory-upgrade skill. Agent Mart. https://agentmart.dev/skills/profbernardoj-memory-upgrade-d8a3a0 (last updated 2026-10-24)