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Researched both tools 2026-06-23. New M6 milestone captures the 5 feature
gaps: generalized gear optimizer (HH flagship, calibration-independent —
starting here), sim-driven damage-mode optimization (gated on M1), speed-tune
solver, gear-cleanse/equip integration, visual timeline. Notes what we already
do that neither tool does (run battles, IL2CPP game-truth, calibrated damage
sim, cross-location recommender) so we don't regress those.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
**Goal**: close the feature gaps vs the two reference tools — but built our
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way (game-truth inputs, calibrated sim as the objective where damage matters,
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CLI-first). External tools stay sanity-checks; we don't copy their outputs.
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Researched 2026-06-23 (see chat: HH optimiser 3.0, DWJ calc guide).
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| Sub-goal | Status | Notes |
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|---|---|---|
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|**Generalized gear optimizer (per-champion stat targets)**| 🔴 → **in flight**| HH's flagship: per-stat min/max/importance, any champion/location, modes Balanced/Damage/Survivability. Ours is CB-only (`cb_optimizer`/`global_gear_solver`). Build `tools/gear_optimizer.py` — location-agnostic vault-gear assignment to hit targets. **Calibration-independent — starting here.**|
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| Damage-mode gear optimization (sim-driven) | 🔴 | Optimize gear to maximize a hero's real skill damage, using OUR calibrated sim as the objective (HH uses a formula estimate; ours is game-truth-validated). Gated on M1 ±5%. |
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| Speed-tune solver / finder | 🔴 | DWJ helps *find* tunes; we only validate/replay known ones. Search SPD-space for unkillable/N-key tunes via `calc_parity_sim`. We can model survival/damage where DWJ can't. |
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| Gear-cleanse + 1-click equip in-game | 🟡 | Pieces exist (`sell.py`, `sell_rules.py`, `loadouts.py`, `/equip`); integrate into the polished filter→sell and equip-full-build flow. Run pillar. |
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