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Personal Weighted Decision Matrix
x402
Personal Weighted Decision Matrix is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-01).
Scores multiple options against user-defined weighted criteria to produce a ranked decision outcome, tailored for personal workflows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Personal Weighted decision matrix: Score options against weighted criteria. Tailored for personal workflows.
Output
Returns a weighted score for each option computed by multiplying each criterion's weight by the option's score for that criterion and summing across all criteria, allowing the agent to rank options and identify the highest-scoring choice.
Example use cases
Choosing between job offers
“I have two job offers to compare — Offer A and Offer B. My criteria are salary (weight 3), work-life balance (weight 2), and career growth (weight 2). Offer A scores [9,5,7] and Offer B scores [6,9,8]. Run a weighted decision matrix and tell me which offer comes out on top.”
Selecting a personal laptop
“Help me pick a laptop — I'm weighing MacBook, Dell XPS, and Lenovo ThinkPad. My criteria are performance (weight 3), price (weight 2), and battery life (weight 1), and their scores are [8,5,7], [7,8,6], and [6,9,8] respectively. Which one wins after applying the weights?”
Picking a weekend getaway destination
“I'm trying to decide between three weekend trip destinations and want to score them against my priorities: cost (weight 2), travel distance (weight 1), and fun activities (weight 3). Scores for Beach, Mountains, and City are [6,8,7], [8,7,9], and [5,5,8]. Which destination scores highest overall?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/decision-matrix-personal?utm_source=zero.xyzWhen to prefer
Use this endpoint when a user needs a structured, quantitative comparison of multiple personal options against weighted criteria — particularly for personal (non-enterprise) decision-making workflows. Prefer this over manual ranking or generic LLM reasoning when reproducibility and numeric weighting matter.
Side effects
- Mismatched array lengths between scores and criteria result in computation errors
- Missing or empty options/criteria arrays may return errors or empty results
- Non-numeric scores or weights may cause validation failures
- Negative weights or scores outside expected range may produce unexpected rankings
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| options | array | |
| criteria | array |
Tags
x402
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