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Decode battle passive activation state

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gamer147
2026-07-24 08:58:32 -04:00
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@@ -3267,3 +3267,34 @@ Evidence regressions protect the exact corpus xrefs and clear geometry, all seve
readers, both SETROUTE flood-score copies, the INIT2 cardinal vectors, and every canonical name.
**Next:** investigate the remaining unnamed stride-300 table at `G[0x15261f]`.
## Data-semantics sidebar: battle triggered-passive matrix (2026-07-24)
The former stride-300 auto table at `G[0x15261f]` is the reserved `2 × 300`
`battle_triggered_passive_skill_flags` work matrix. Its first dimension is BTL's two battle sides,
and its second dimension is the SKINIT skill id. The complete corpus surface is compact and exact:
BTL and CALCDMG are its only readers/writers, with 37 two-dimensional lookups and three full
600-cell clears.
CALCDMG rebuilds the matrix for each exchange. A local eligibility surface first assigns the
actor/target roles of shipped passive ids 28..50 (with Seal/id 44 absent from this activation path).
The script then scans the four equipped skills on both battle entities, accepts category-4 passives,
applies the configured `skill_proc_chance_percent`, and filters surviving cells through the concrete
combat contract: species and boss slayers, anti-air/anti-sub movement skills, ordinary-versus-special
attack categories, role-specific defensive/offensive passives, and mutually exclusive reactions.
The result is an activation record for this exchange rather than the entity's persistent skill
ownership; `entity_skill_flags` remains the latter source.
BTL proves the output side. It indexes each participant's four equipped skills through the matrix
to draw the triggered-passive icons, and repeats the dynamic join for actor- and target-side passive
battle animations. Direct column tests then implement Roar, Counter, Reflect, Absorb, Pierce, Shield,
Parry, and Revive behavior. The adjacent `G[0x15261e]` is now
`battle_actor_hp_recovery`: CALCDMG adds Absorb's half-damage return and any level-scaled HP-absorption
condition amount, while BTL adds the result to the actor's HP and renders the green recovery number.
Evidence regressions protect the exact two-script/40-reference surface, all three `2 × 300` clears,
the passive-id eligibility range, category gate and dynamic filters, BTL's three skill-indexed
presentation consumers, and the actor-recovery producer/consumer pair.
**Next:** investigate the highest-use remaining auto-shaped row table, the stride-14 table at
`G[0x6f70]` (27 references across ADDEXP, EVOLVE, GAMECLEAR, GAMESTART, TRAIN, and UNITECH).