Mental Model
Memory is for information with recurring value across conversations. If you'll need it tomorrow/next week, save it. If it's ephemeral (today's weather, casual greeting), don't.
What to Remember (DO)
Category Examples File
Identity Name, age, location, occupation facts/people.jsonl
Preferences Languages, frameworks, work style facts/preferences.jsonl
Relationships Colleagues, family, team members facts/people.jsonl
Decisions Conclusions from discussions facts/projects.jsonl
Context Project details, work environment facts/projects.jsonl
What NOT to Remember (NEVER)
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Ephemeral greetings ("你好", "hi")
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Temporary states ("今天很忙", "现在在外面")
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One-time questions without context
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Duplicate information already stored
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Credentials (passwords, API keys, tokens - even if user shares)
Action Pattern
When user shares memorable info:
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Immediately call fs_write
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don't acknowledge first, don't batch
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Extract structured fields from casual speech
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Use importance score: 0.9-1.0 (identity), 0.7-0.8 (preferences), 0.5-0.6 (context)
Example:
User: "我叫张三，在深圳做后端开发" → fs_write path=".memory/facts/people.jsonl" content='{"id":"mem_1704628800000","ts":"2026-01-07T12:00:00.000Z","type":"fact","category":"person","content":"张三，深圳，后端开发","tags":["name","location","occupation"],"importance":0.95}'
Storage Map
.memory/ ├── profile.json # Read on session start for context ├── facts/ │ ├── people.jsonl # Identity, relationships │ ├── preferences.jsonl # Tech stack, work style │ └── projects.jsonl # Work context, decisions └── conversations/ └── YYYY-MM-DD.jsonl # Session summaries
Entry Schema
{"id":"mem_{{timestamp}}","ts":"{{ISO8601}}","type":"fact","category":"{{person|preference|project}}","content":"{{concise content in user's language}}","tags":["{{retrieval keywords}}"],"importance":{{0.5-1.0}}
Retrieval
Session start: fs_read profile.json
Search: fs_grep pattern="{{keyword}}" path=".memory/"