feat(isac): link skill chips to abilities

docs/STAT_LEVEL_SCALING.md

@@ -1,25 +1,23 @@
 # Weapon and gear stat level scaling
 
-This document records the empirically observed rules for adjusting weapon and
-gear stat ranges by item level. The rules apply independently to both endpoints
-of a configured range.
+Use these observed rules to adjust weapon and gear stat ranges by item level.
+Apply each rule to both endpoints of a configured range.
 
-These formulas are based on in-game observations rather than published game
-mechanics. Preserve source observations when adding new samples and revise the
-constants if a larger data set disproves them.
+In-game observations, rather than published game mechanics, support these
+formulas. Preserve source observations with new samples and revise constants
+when a larger data set disproves them.
 
 ## Numeric representation and display
 
-Stat ranges must retain their unrounded decimal values. The integer shown by the
-game is consistent with truncation:
+Store stat ranges as unrounded decimals. The game display truncates them:
 
 ```text
 displayedValue = floor(rawValue)
 ```
 
-Do not use `ceil`, and do not repeatedly level an already displayed integer.
-Both approaches accumulate errors. A level-1 value displayed as `0` can still
-have a positive fractional raw value that becomes visible at a higher level.
+Avoid `ceil` and repeated leveling of displayed integers. Both accumulate
+errors. A level-1 display of `0` can hide a positive fractional raw value that
+appears at a higher level.
 
 For example, a standard gear item displayed `0 ENG` at level 1 and `2 ENG` at
 level 42. With a level-42 multiplier of `3.01`, a raw base near `0.7` explains
@@ -30,12 +28,12 @@ floor(0.7)        = 0
 floor(0.7 × 3.01) = 2
 ```
 
-When only displayed integers are available, a prediction can be off by one.
-That is expected information loss, not evidence for rounding upward.
+Predictions from displayed integers can miss by one because truncation loses
+information. That error does not indicate rounding upward.
 
 ## Shared progression model
 
-The stable portion of both progressions is linear, not compounded:
+The stable portion of both progressions is linear:
 
 ```text
 rawStat(level) = hiddenBase × multiplier(level)
@@ -48,8 +46,8 @@ fixed `5%` of the hidden base:
 rawStat(level + 1) - rawStat(level) = hiddenBase × 0.05
 ```
 
-Never calculate a new level as `previousDisplayedValue × 1.05`; that describes
-compound growth and does not match the observations.
+Do not calculate a new level as `previousDisplayedValue × 1.05`. That compound
+growth model conflicts with the observations.
 
 For a range `[minimum, maximum]`, calculate each endpoint separately:
 
@@ -58,7 +56,7 @@ scaledMinimum = hiddenMinimum × multiplier(level)
 scaledMaximum = hiddenMaximum × multiplier(level)
 ```
 
-Only truncate when producing a game-matching display value.
+Truncate at the game-display boundary.
 
 ## Gear
 
@@ -68,9 +66,9 @@ The observed stable gear multiplier is:
 gearMultiplier(level) = 0.91 + 0.05 × level
 ```
 
-This rule is validated for levels 10 through 50 across Standard, Specialized,
-and High-end samples. Quality changes the hidden stat ranges; the observed
-late-level multiplier does not change with quality.
+Samples across Standard, Specialized, and High-end qualities validate this rule
+for levels 10 through 50. Quality changes hidden stat ranges; the observed
+late-level multiplier remains the same.
 
 Given hidden level-independent endpoints:
 
@@ -115,11 +113,10 @@ ENG = floor(0.7   × 3.01) = 2
 
 ### Early gear levels
 
-Levels 1 through 9 show a quality-dependent transition and do not follow the
-stable multiplier directly. Do not extrapolate that transition from a single
-level-1-to-level-2 change. Until the early curves are sampled more completely,
-store authoritative ranges for those levels or mark calculated results as
-estimates.
+Levels 1 through 9 show a quality-dependent transition outside the stable
+multiplier. Do not extrapolate it from one level-1-to-level-2 change. Until
+more samples define the early curves, store authoritative ranges or label
+calculated results as estimates.
 
 ## Weapons
 
@@ -179,9 +176,9 @@ multiplier, then derive the combined pool bounds by multiplying each endpoint
 by three. Redistribution changes the split between the three cores without
 changing the selected item's total allocation.
 
-The `1.14` offset is provisional and is currently validated only for the
-level-40-to-level-50 interval. Preserve enough decimal precision to revise it
-without migrating rounded data.
+The `1.14` offset remains provisional; observations only validate it from level
+40 to 50. Retain enough decimal precision to revise it without migrating
+rounded data.
 
 ### Weapon example
 
@@ -192,9 +189,9 @@ A weapon changed from `753 DMG` at level 40 to `873 DMG` at level 50:
 floor(872.95) = 872
 ```
 
-The displayed-source calculation misses by one because `753` is already
-truncated. Applying the ratio to the unrounded source value produces the
-observed `873`. This is why calculations must use stored decimal endpoints.
+The calculation misses by one because `753` is truncated. The ratio applied to
+the unrounded source value produces `873`, so calculations require stored
+decimal endpoints.
 
 The observed changes over those ten levels were linear:
 
@@ -207,11 +204,10 @@ ENG:  45 → 52   (about 0.7 per level)
 
 ### Early weapon levels
 
-Do not apply the provisional late-level weapon offset to level 1. An Exotic
-sample's displayed level-1 values and level-50 values fit a `2.91` endpoint
-ratio for most stats, which is incompatible with simply extending the
-level-40-to-level-50 offset backward. Weapons therefore also appear to have an
-early transition or another quality-dependent input.
+Do not apply the provisional late-level weapon offset at level 1. An Exotic
+sample's level-1 and level-50 displays fit a `2.91` endpoint ratio for most
+stats, which conflicts with extending the level-40-to-level-50 offset
+backward. Weapons appear to have an early transition or quality-dependent input.
 
 Until more intermediate samples are available: