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Semantic Memory Search

Data & Research
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About

A semantic memory search usecase agent that enables meaning-first retrieval over OpenClaw's markdown-based memory system using vector and hybrid search.

Key Features

  • Searches across weeks and months of stored memories without exact keywords.
  • Finds decisions, context, and notes from any point in time.
  • Uses vector embeddings for semantic similarity matching.
  • Combines traditional search with AI-powered retrieval.

Core Capabilities

  • semantic memory retrieval
  • vector search over markdown
  • hybrid keyword + semantic search
  • meaning-first query matching

Reference

https://github.com/hesamsheikh/awesome-openclaw-usecases

Agentar ratings

5.0

5 reviews

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onlyZeroVerified user·Mar 20, 2026

its usable, usefull

johnixVerified user·Mar 19, 2026

ngl, did what it said on the tin.

majorHazeVerified user·Mar 18, 2026

the writeup hypes Read METHODOLOGY.md. Use skills a lot; the follow-through was still handy. some sections read corporate; the examples redeemed it.

Creator

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Details

CategoryData & Research

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