dvcrn Decision Dynamo
Run a weighted matrix analysis to score and rank options objectively.
Workflow
- Gather options — Identify 2–4 named choices to compare.
- Set weights — Ask the user to rate how important each of the 5 criteria is (1–10).
- Score options — For each option, rate it 1–10 on each criterion.
- Run the matrix — Execute
scripts/decision_matrix.py(interactive or JSON mode). - Present results — Share the ranked output and briefly explain the winner.
Running the Script
Interactive mode (guided prompts):
python3 scripts/decision_matrix.py
JSON mode (pre-built input):
python3 scripts/decision_matrix.py input.json
See references/criteria.md for the JSON schema, criteria definitions, scoring scale, and inversion logic for negative criteria.
The Five Criteria
| Criterion | Type |
|---|---|
| Skill/Leverage Gain | Positive |
| Goal Alignment | Positive |
| Mental/Emotional Drag | Negative (inverted) |
| Financial Cost | Negative (inverted) |
| Time and Effort | Negative (inverted) |
Negative criteria use (11 - score) * weight so that less drag = higher score.
Agent Guidance
- If the user hasn't defined weights, suggest defaults (all equal at 5) and ask if they want to adjust.
- If scoring feels subjective, help the user by asking "on a scale of 1–10, how much does this option [criterion]?"
- After presenting results, offer to re-run with adjusted weights to test sensitivity.
- Always show the winner clearly and explain why it scored highest in plain language.