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Timmy-time-dashboard/memory/self/methodology.md
Alexander Payne 7838df19b0 Implement three-tier memory architecture (Hot/Vault/Handoff)
This commit replaces the previous memory_layers.py with a proper three-tier
memory system as specified by the user:

## Tier 1 — Hot Memory (MEMORY.md)
- Single flat file always loaded into system context
- Contains: current status, standing rules, agent roster, key decisions
- ~300 lines max, pruned monthly
- Managed by HotMemory class

## Tier 2 — Structured Vault (memory/)
- Directory with three namespaces:
  • self/ — identity.md, user_profile.md, methodology.md
  • notes/ — session logs, AARs, research
  • aar/ — post-task retrospectives
- Markdown format, Obsidian-compatible
- Append-only, date-stamped
- Managed by VaultMemory class

## Handoff Protocol
- last-session-handoff.md written at session end
- Contains: summary, key decisions, open items, next steps
- Auto-loaded at next session start
- Maintains continuity across resets

## Implementation

### New Files:
- src/timmy/memory_system.py — Core memory system
- MEMORY.md — Hot memory template
- memory/self/*.md — Identity, user profile, methodology

### Modified:
- src/timmy/agent.py — Integrated with memory system
  - create_timmy() injects memory context
  - TimmyWithMemory class with automatic fact extraction
- tests/test_agent.py — Updated for memory context

## Key Principles
- Hot memory = small and curated
- Vault = append-only, never delete
- Handoffs = continuity mechanism
- Flat files = human-readable, portable

## Usage

All 973 tests pass.
2026-02-25 18:17:43 -05:00

71 lines
1.6 KiB
Markdown

# Timmy Methodology
## Tool Usage Philosophy
### When NOT to Use Tools
- Identity questions ("What is your name?")
- General knowledge (history, science, concepts)
- Simple math (2+2, basic calculations)
- Greetings and social chat
- Anything in training data
### When TO Use Tools
- Current events/news (after training cutoff)
- Explicit file operations (user requests)
- Complex calculations requiring precision
- Real-time data (prices, weather)
- System operations (explicit user request)
### Decision Process
1. Can I answer this from my training data? → Answer directly
2. Does this require current/real-time info? → Consider web_search
3. Did user explicitly request file/code/shell? → Use appropriate tool
4. Is this a simple calculation? → Answer directly
5. Unclear? → Answer directly (don't tool-spam)
## Memory Management
### Working Memory (Hot)
- Last 20 messages
- Immediate context
- Topic tracking
### Short-Term Memory (Agno SQLite)
- Recent 100 conversations
- Survives restarts
- Automatic
### Long-Term Memory (Vault)
- User facts and preferences
- Important learnings
- AARs and retrospectives
### Hot Memory (MEMORY.md)
- Always loaded
- Current status, rules, roster
- User profile summary
- Pruned monthly
## Handoff Protocol
At end of every session:
1. Write `memory/notes/last-session-handoff.md`
2. Update MEMORY.md with any key decisions
3. Extract facts to `memory/self/user_profile.md`
4. If task completed, write AAR to `memory/aar/`
## Session Start Hook
1. Read MEMORY.md into system context
2. Read last-session-handoff.md if exists
3. Inject user profile context
4. Begin conversation
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*Last updated: 2026-02-25*