fc123326e5
Add persistent knowledge system that enables Atomizer to learn from every session and improve over time. ## New Files - knowledge_base/lac.py: LAC class with optimization memory, session insights, and skill evolution tracking - knowledge_base/__init__.py: Package initialization - .claude/skills/modules/learning-atomizer-core.md: Full LAC skill documentation - docs/07_DEVELOPMENT/ATOMIZER_CLAUDE_CODE_INSTRUCTIONS.md: Master instructions ## Updated Files - CLAUDE.md: Added LAC section, communication style, AVERVS execution framework, error classification, and "Atomizer Claude" identity - 00_BOOTSTRAP.md: Added session startup/closing checklists with LAC integration - 01_CHEATSHEET.md: Added LAC CLI and Python API quick reference - 02_CONTEXT_LOADER.md: Added LAC query section and anti-pattern ## LAC Features - Query similar past optimizations before starting new ones - Record insights (failures, success patterns, workarounds) - Record optimization outcomes for future reference - Suggest protocol improvements based on discoveries - Simple JSONL storage (no database required) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
18 lines
430 B
Python
18 lines
430 B
Python
"""
|
|
Knowledge Base Package
|
|
======================
|
|
|
|
Provides persistent knowledge storage for Atomizer including:
|
|
- LAC (Learning Atomizer Core): Session insights, optimization memory, skill evolution
|
|
- Research sessions: Detailed research logs
|
|
"""
|
|
|
|
from .lac import LearningAtomizerCore, get_lac, record_insight, query_insights
|
|
|
|
__all__ = [
|
|
"LearningAtomizerCore",
|
|
"get_lac",
|
|
"record_insight",
|
|
"query_insights",
|
|
]
|