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gogobee/gogobee_class_balance.md
prosolis 0799b6a57b D&D: class-balance pass plan doc (gogobee_class_balance.md)
Phased plan for the class-balance pass. Unlike the race pass, classes
are *measured* not modeled: combat is one-shot auto-resolved through a
seedable simulateCombatWithRNG, so the harness runs Monte Carlo over the
real engine and reads win rates directly.

Scopes the full matrix (10 classes × 30 subclasses × level checkpoints ×
monster tiers), the two hard policies to de-risk in Phase 0 (equipment
loadout, spell selection), the per-tier win-rate parity rule, and the
tuning levers. Phase 0 spike in progress.
2026-05-14 19:47:10 -07:00

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GogoBee — D&D Class Balance Pass

Companion to: gogobee_dnd_design_doc_v1.1.md, gogobee_spell_system.md, gogobee_subclass_system.md Version: 0.1 (planning draft) Status: Pre-implementation — Phase 0 spike in progress Sibling work: the race-balance pass (internal/plugin/dnd_race_balance.go, TestRaceBalance) — same spirit, different method (see §1).


0. Why this doc exists

The race-balance pass tuned the seven races to equal effective power via a hand-weighted scoring model. That model is a proxy — races don't fight, so there is nothing to measure directly.

Classes are different: combat is one-shot auto-resolved through a single simulateCombatWithRNG call (combat_engine.go:338), and the RNG is seedable. So class balance does not need a proxy model — we can run thousands of real, reproducible fights and read the win rates directly.

This doc plans that work. Endgame: a TestClassBalance regression fixture that holds per-tier win-rate parity across all 10 classes × 30 subclasses, plus the tuning pass that gets us there.

Non-goals. Not a combat-engine redesign. Not adding classes/subclasses. "Balanced" means balanced in gogobee's one-shot engine — the model collapses tabletop action economy, and that is accepted.


1. Method — measure, don't model

Race pass Class pass
Power source ability mods only full combat: HP/AC, weapons, spells, passives, subclass tiers
Approach hand-weighted scoring proxy Monte Carlo over the real engine
Trust heuristic weights (estimated) empirical win rates (measured)
Artifact dnd_race_balance.go + TestRaceBalance dnd_class_balance.go + TestClassBalance

2. The matrix (full)

For each of the 10 classes:

  • subclass = none at L1L4
  • each of its 5 subclasses at the L5 / L7 / L10 / L15 / L20 tier-unlock checkpoints

→ ~60 build profiles × level checkpoints × ~6 monster tiers. Each cell = N seeded fights through simulateCombatWithRNG. One-shot sims are cheap; compute is not the constraint.

Opponents: the existing per-tier monster scaling curves (dnd_combat.go:3551) — dungeon Tier and arena ThreatLevel — used as a fixed gauntlet.

Builds: standard array assigned by each class's stat priority (dnd_combat.go:185218), Human race (neutral baseline, +1 all), plus a standardized equipment loadout (see §3).


3. The two hard parts (Phase 0 de-risks these)

  1. Equipment loadout policy. Combat uses equipment-driven AC and real weapon dice. The per-class, per-level kit must be standardized fairly or every downstream number is garbage. Derive from existing starting-gear / level tables if they exist; otherwise define a canonical tiered kit.
  2. Spell-selection policy. Caster damage flows through applyPendingCast. Without a "what would a player cast here" heuristic per class/level, all 8 casters fight as naked weapon-users and read as broken — a measurement artifact, not real imbalance.

4. Balance rule

Per-tier win-rate parity: at each difficulty tier, every class within a tolerance band of the cross-class mean win rate. Band set empirically after the first full run (the race pass's ±0.5 was set the same way). Damage-dealt, HP-remaining, and near-death-rate are logged as diagnostics, not asserted.


5. Phases (one phase ≈ one session; each ends green + committed)

  • Phase 0 — spike. Harness skeleton; equipment + spell-selection policies; run Fighter vs. Mage only across tiers and sanity-check plausibility (both win something; casters not at 0%). If the numbers are implausible, fix the policies before trusting anything. ← current
  • Phase 1 — harness + matrix. Generalize to all 10 classes × 30 subclasses; TestClassBalance logs the full report. No tuning yet — just measurement.
  • Phase 2 — tuning pass. Adjust the levers (class passives → subclass tiers → spell dice → AC floor → attack bonus, in that order) until the parity band holds. Lock the band into the test assertion.
  • Phase 3 (if needed) — second-order. Subclass-vs-subclass spread within a class; the Paladin/Rogue MAD question if the data shows it bites.

6. Tuning levers (priority order)

  1. Class passives — dnd_passives.go
  2. Subclass L5/7/10/15 tiers — dnd_subclass_combat.go
  3. Spell damage dice & upcast — dnd_spells_data.go, dnd_spells_srd_data.go
  4. Spell slot progression — dnd_spells.go
  5. AC floor / armor proficiency — dnd.go:164178
  6. Attack bonus class matrix — dnd_combat.go:2233
  7. Monster scaling curves — dnd_combat.go:3551 (last resort; affects PvE feel)