Enhanced Idealization Platform

This repository now contains a Python MVP for an enhanced idealization platform. It helps users define success, model constraints, generate multiple candidate futures, stress test them across scenarios, and receive ranked recommendations with confidence, tradeoffs, and reasoning traces.

What it does

• captures goals, criteria, constraints, and context in a structured request
• generates multiple candidate strategies from a baseline or explicit blueprints
• adapts scoring based on user profiles and weighted success criteria
• simulates candidate performance under future scenarios
• explains why one recommendation outranks another
• compares the current recommendation against previous runs

Project layout

• /enhanced_idealization/models.py - data models and request parsing
• /enhanced_idealization/engine.py - candidate generation, simulation, scoring
• /enhanced_idealization/reporting.py - plain-text recommendation rendering
• /enhanced_idealization/__main__.py - command-line entry point
• /examples/product_strategy.json - sample input
• /tests/test_engine.py - automated tests

Run the sample

cd /path/to/enhanced-idealization
python -m enhanced_idealization examples/product_strategy.json --profile enterprise_ops

Run the tests

cd /path/to/enhanced-idealization
python -m unittest discover -s tests