Coding

Learning Optimizer

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Learning optimizer - analyze study patterns, identify inefficiencies, suggest optimizations for better learning outcomes

What it does

Learning optimizer - analyze study patterns, identify inefficiencies, suggest optimizations for better learning outcomes

The skill document

Learning Optimizer

Analyze and optimize learning patterns for better efficiency.

Features

  • Study pattern analysis
  • Efficiency identification
  • Time allocation suggestions
  • Focus improvement tips

Input

  • Study schedule/history
  • Current time allocation
  • Distraction factors
  • Performance data (optional)

Output

  • Efficiency analysis
  • Optimization suggestions
  • Time reallocation plan
  • Focus improvement tips

Constraints

  • ❌ No performance guarantees
  • ❌ No one-size-fits-all solutions
  • ❌ No external data collection

Usage

python3 scripts/main.py analyze --schedule "每天2小时" --subjects "数学,英语"
python3 scripts/main.py optimize --problem "容易分心" --current "长时间连续学习"
python3 scripts/main.py allocate --total 120 --priorities "数学高,英语中"
python3 scripts/main.py data

Storage

Logs are local-first and stored under ~/.learning-optimizer/ by default. Set LEARNING_OPTIMIZER_HOME for tests, demos, or shared machines:

LEARNING_OPTIMIZER_HOME=/tmp/learning-demo python3 scripts/main.py analyze --schedule "每天2小时" --subjects "数学,英语"

The skill writes JSONL logs:

  • analysis_log.jsonl
  • optimization_log.jsonl
  • allocation_log.jsonl

Verification

python3 -m py_compile scripts/main.py scripts/verify.py
python3 scripts/verify.py

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