memory-lancedb-pro Model Card
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memory-lancedb-pro Model Card
| Field | Value |
|---|---|
| Repository | CortexReach/memory-lancedb-pro |
| Category | OpenClaw Long-Term Memory Plugin |
| Stars / forks snapshot | 4400 / 725 |
| Language | TypeScript |
| License | MIT |
| Raw capture | raw-github/cortexreach_memory-lancedb-pro.md |
| Updated by | hourly public metadata update, 2026-05-27 09:59 +0800 |
1. Role in Self Evolve
memory-lancedb-pro is a production-grade OpenClaw memory plugin that combines long-term storage, hybrid retrieval, and scoped context injection for agent workflows. It matters because self-evolving agents need repeatable harness control, measurable feedback loops, and reusable skill procedures before claiming stable improvement.
2. Working Principle
auto-capture memory -> vector+BM25 retrieval -> rerank/context injection -> scoped memory boundaries -> CLI backup and migration
3. Evidence Path
web-observed GitHub page showed 4.4k stars, 725 forks, 459 commits, MIT license signal, and README notes for OpenClaw memory assistant behavior with hybrid retrieval and plugin lifecycle tooling. Shell GitHub API access remained blocked by DNS and local gh auth was invalid, so this card treats the snapshot as web-observed rather than API-verified.
4. Teaching Use
Use this card to explain OpenClaw Long-Term Memory Plugin: it shows how harness/runtime/benchmark layers convert agent behavior into reproducible and auditable engineering workflows.
5. Limits
The repository was not cloned in this iteration; no benchmark run, plugin install, workflow execution, or agent loop experiment was executed. Counts and claims are visible public-page/search signals unless independently revalidated later.