The Data Density Framework

Data Density is a composite of eight dimensions projected onto Intelligence and Wisdom axes. The framework is designed to be extensible: add features, recalibrate weights, export higher-order tensors.

D1..D8 dimensions Axes Intelligence/Wisdom projections Extensible add oracle-text features later Copy/paste math formulas included

Core objects

CardRecord = (name, qty, role, behavior_tag, mode_tags, tags, notes)
Deck = multiset of CardRecord
Run = (deck, config, scores, tensors, timestamps)

Offline-first scoring uses the fields you provide. Oracle text is optional enrichment (Phase 2+).

Composite score

DD = ( Σ_i w_i · D_i ) / ( Σ_i w_i )
Intel = Σ_i p^I_i · D_i
Wis   = Σ_i p^W_i · D_i

Weights w_i and projections p are configurable.

Deck shape statistics

Entropy(counter) = - Σ p(x) log2 p(x)
Gini(qty) = dispersion of copy counts (singleton ā€œThunderdomeā€ vs redundancy)

Shape stats are important: a deck’s identity is often more about distribution than power.

Overcommit tensor (v0.2-inspired)

A general tensor for ā€œpaying a drain and converting it into advantageā€. This isn’t limited to Mercy effects: it models any planned tempo debt.

Drain(L,r) = (1-r)L
U(mode,L,r) = -Drain(L,r) + α·Gain(mode)
Asset iff U > 0