auto-memory
Skill2 starsChanged 3 months agoMITView on GitHub
Memory as a learnable skill — store, recall, compress, and consolidate agent memories. Inspired by Stanford AutoMem.
3 other projects use a version of this, 1 of them edited.
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- zedarvates/frugal-skillsedited, first seen Nov 8, 2026
- mikeyobrien/rhotheir own version, first seen Oct 8, 2026
- tractorjuice/arc-kittheir own version, first seen May 10, 2026
Other versions3 projects use a version of this.
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Edited · 1
- zedarvates/frugal-skills★ 144% same
Wrote their own version · 2
- tractorjuice/arc-kit★ 2.3ksame name
- mikeyobrien/rho★ 372same name
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The file
Files
AutoMemory
Memory as a capability, not just storage. Adapts to patterns in agent behavior.
Features
- MemoryBank — persistent key/value store with categories and confidence scores
- TrajectoryRecorder — capture goal→actions→outcomes paths
- Compressor — deduplicate, bottleneck reduction, pattern extraction
- Hook — integrate with context_profiler and control loop
Usage
from skills.auto_memory import init_memory, store_memory, recall_memory
bank = init_memory()
store_memory("user_pref.format", "concise", category="user_pref", confidence=0.95)
prefs = recall_memory("user_pref.format")Integration
Add to control_loop.py:
from skills.auto_memory.hook import init_memory, record_step, consolidate_memory
bank = init_memory("task_123")
record_step("plan", {"steps": ["a", "b"]})
consolidate_memory() # merge similar memoriesDoes it work?
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