Memory Learner
Long-term memory + learning from experience + self-evolution.
Core Principle
Write to files, not mental notes. Every lesson, decision, preference, or event worth remembering goes into structured files immediately — not kept in context.
When This Skill Activates
1. Session Start (every time)
Read these files before anything else:
SOUL.md— who I amUSER.md— who I'm helpingMEMORY.md— curated long-term memorymemory/YYYY-MM-DD.md— recent context (today + yesterday)
2. After Significant Decisions
When I make a decision worth remembering (tool choice, strategy, opinion):
- Write to
memory/YYYY-MM-DD.md - If important, distill to
MEMORY.md
3. On Feedback / Mistakes
When user corrects me, expresses frustration, or I realize I made a mistake:
LEARN: <what happened>
LESSON: <what I should do differently>
CONFIDENCE: high/medium/low
→ Store in memory/learnings/YYYY-MM-DD.md
4. Pre-Task Recall (on request)
Before significant tasks, search memory for related context:
mem_recall "task description"
Returns relevant memories, learnings, and past decisions.
5. Heartbeat Review (periodic)
During heartbeats, do light maintenance:
- Review today's
memory/YYYY-MM-DD.md - Identify learnings worth capturing
- Update
MEMORY.mdif anything significant
6. Evolution Check (weekly or on request)
mem_evolve
Review learnings corpus, identify patterns, update behavioral guidelines in SOUL.md.
Memory Structure
memory/
YYYY-MM-DD.md # Daily raw log
learnings/
YYYY-MM-DD.md # Daily lessons learned
patterns.md # Repeated mistake patterns
MEMORY.md # Curated long-term memory
Daily Log Format
## Session DD
### What happened
[Context, decisions, outcomes]
### Key decisions
- [decision] → [why]
### To remember
- [fact about user/preference/project]
Learnings Format
# Learning: YYYY-MM-DD
## Incident
[What happened]
## Lesson
[What I should do differently]
## Context
[When this applies]
## Tags
#feedback #mistake #ui #tool-choice
MEMORY.md Categories
- Identity: Who I am, my values
- User: Preferences, projects, context
- Learnings: Important lessons (distilled)
- Projects: Active work and status
- Patterns: Recurring situations and how I handle them
Scripts
mem_recall.py— Search memories by querymem_learn.py— Capture a learningmem_evolve.py— Review and evolve behavioral patternsmem_status.py— Show memory health summary
Evolving
Every 5 learnings, do an evolution review:
- Read recent learnings
- Identify patterns (same mistake twice = pattern)
- Update
SOUL.mdorAGENTS.mdwith new behavioral guidelines - Archive learnings to
patterns.md
This is how I get genuinely smarter over time, not just accumulate notes.