feat: add FTS5 full-text search for memory retrieval#2
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sergi-rz wants to merge 1 commit intocodejunkie99:masterfrom
Open
feat: add FTS5 full-text search for memory retrieval#2sergi-rz wants to merge 1 commit intocodejunkie99:masterfrom
sergi-rz wants to merge 1 commit intocodejunkie99:masterfrom
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Currently the memory system can only surface top-k entries by salience score, but cannot search by topic or keyword. This adds a lightweight SQLite FTS5 search tool that indexes all .md and .jsonl files under .agent/memory/ and returns ranked results with context snippets. - memory_search.py: FTS5 index with auto-rebuild and grep fallback - .gitignore: exclude derived .index/ directory - memory-manager SKILL.md: document the search command Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Problem
The memory system can surface the top-k entries by salience score (
context_budget.py), but there's no way to search by topic or keyword. If an agent needs to recall what it learned about deploys, or a specific past failure, it has no retrieval path — it only sees whatever happens to score highest globally.Solution
A lightweight
memory_search.pythat builds a SQLite FTS5 index over all.mdand.jsonlfiles in.agent/memory/. It:Usage
python3 .agent/memory/memory_search.py "deploy failure" python3 .agent/memory/memory_search.py --status python3 .agent/memory/memory_search.py --rebuildWhat's changed
.agent/memory/memory_search.py— the search tool (~170 lines, zero dependencies beyond stdlib).gitignore— excludes.agent/memory/.index/(derived, auto-rebuilt)memory-manager/SKILL.md— documents the search command so the agent knows it existsNo existing code is modified. This is purely additive.
Context
I'm building Claudia OS, a personal AI assistant on top of Claude Code. I adopted your episodic memory architecture, dream cycle, and salience scoring (credited in my ATTRIBUTION.md). While adapting it, I needed keyword search over memory — the salience-only retrieval wasn't enough when the agent needed to recall something specific. This FTS5 approach solved it cleanly without adding infrastructure.
🤖 Generated with Claude Code