Two-layer memory system with grep-based recall.
64
Quality
47%
Does it follow best practices?
Impact
95%
1.30xAverage score across 3 eval scenarios
Optimize this skill with Tessl
npx tessl skill review --optimize ./nanobot/skills/memory/SKILL.mdmemory/MEMORY.md — Long-term facts (preferences, project context, relationships). Always loaded into your context.memory/HISTORY.md — Append-only event log. NOT loaded into context. Search it with grep-style tools or in-memory filters. Each entry starts with [YYYY-MM-DD HH:MM].Choose the search method based on file size:
memory/HISTORY.md: use read_file, then search in-memorymemory/HISTORY.md: use the exec tool for targeted searchExamples:
grep -i "keyword" memory/HISTORY.mdfindstr /i "keyword" memory\HISTORY.mdpython -c "from pathlib import Path; text = Path('memory/HISTORY.md').read_text(encoding='utf-8'); print('\n'.join([l for l in text.splitlines() if 'keyword' in l.lower()][-20:]))"Prefer targeted command-line search for large history files.
Write important facts immediately using edit_file or write_file:
Old conversations are automatically summarized and appended to HISTORY.md when the session grows large. Long-term facts are extracted to MEMORY.md. You don't need to manage this.
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