diff --git a/creator-onboarding/artists/1-building-your-project.md b/creator-onboarding/artists/1-building-your-project.md
index c221de4e..d192a5d2 100644
--- a/creator-onboarding/artists/1-building-your-project.md
+++ b/creator-onboarding/artists/1-building-your-project.md
@@ -56,43 +56,7 @@ const invocation = parseInt(tokenData.tokenId) % 1_000_000
 
 **Never use `Math.random()` or `Date.now()` as a randomness source.** These are non-deterministic — the same token would produce different outputs on different loads, which breaks the fundamental guarantee of generative art on Art Blocks.
 
-Instead, seed a pseudo-random number generator (PRNG) from `tokenData.hash`. The recommended implementation is the **sfc32** algorithm:
-
-```javascript
-// Seeded PRNG from tokenData.hash
-function sfc32(a, b, c, d) {
-  return function () {
-    a |= 0; b |= 0; c |= 0; d |= 0;
-    let t = (((a + b) | 0) + d) | 0;
-    d = (d + 1) | 0;
-    a = b ^ (b >>> 9);
-    b = (c + (c << 3)) | 0;
-    c = (c << 21) | (c >>> 11);
-    c = (c + t) | 0;
-    return (t >>> 0) / 4294967296;
-  };
-}
-
-function hashToSeeds(hash) {
-  const hex = hash.slice(2); // remove "0x"
-  return [
-    parseInt(hex.slice(0, 8), 16),
-    parseInt(hex.slice(8, 16), 16),
-    parseInt(hex.slice(16, 24), 16),
-    parseInt(hex.slice(24, 32), 16),
-  ];
-}
-
-const [s1, s2, s3, s4] = hashToSeeds(tokenData.hash);
-const rand = sfc32(s1, s2, s3, s4);
-
-// Usage:
-// rand()           → float in [0, 1)
-// rand() * (b - a) + a  → float in [a, b)
-// Math.floor(rand() * n) → integer in [0, n)
-```
-
-Alternatively, use the full `Random` class that ships in the MCP scaffold, which adds convenient helper methods:
+Instead, seed a pseudo-random number generator (PRNG) from `tokenData.hash`:
 
 ```javascript
 class Random {
@@ -255,7 +219,7 @@ Test with specific hashes by appending `?hash=0x...` to the URL. Test with many
 
 If you have an existing p5.js or vanilla JS sketch that you want to convert to Art Blocks format:
 
-1. **Replace `Math.random()`** with calls to your sfc32 PRNG seeded from `tokenData.hash`
+1. **Replace `Math.random()`** with calls to your `Random` class PRNG seeded from `tokenData.hash`
 2. **Remove CDN `<script>` tags** — the generator loads your library automatically
 3. **Remove canvas creation code** — for p5.js, remove `createCanvas()` calls or use `windowWidth`/`windowHeight`; for vanilla JS, select the existing `<canvas>` instead of creating one
 4. **Make dimensions relative** — replace hardcoded pixel values with percentages of `width`/`height`
diff --git a/legacy/features-script.md b/legacy/features-script.md
index 027b8f90..d359c062 100644
--- a/legacy/features-script.md
+++ b/legacy/features-script.md
@@ -40,42 +40,9 @@ function calculateFeatures(tokenData) {
 
 ---
 
-## The Random Class (Legacy)
+## PRNG in the Features Script
 
-The following `Random` class was commonly used with `calculateFeatures()`. It uses the sfc32 PRNG seeded from the token hash:
-
-```javascript
-class Random {
-  constructor(hash) {
-    const hex = hash.slice(2);
-    this.prng = this._sfc32(
-      parseInt(hex.slice(0, 8), 16),
-      parseInt(hex.slice(8, 16), 16),
-      parseInt(hex.slice(16, 24), 16),
-      parseInt(hex.slice(24, 32), 16)
-    );
-  }
-
-  _sfc32(a, b, c, d) {
-    return function () {
-      a |= 0; b |= 0; c |= 0; d |= 0;
-      let t = (((a + b) | 0) + d) | 0;
-      d = (d + 1) | 0;
-      a = b ^ (b >>> 9);
-      b = (c + (c << 3)) | 0;
-      c = (c << 21) | (c >>> 11);
-      c = (c + t) | 0;
-      return (t >>> 0) / 4294967296;
-    };
-  }
-
-  random_dec()       { return this.prng(); }
-  random_num(a, b)   { return a + this.prng() * (b - a); }
-  random_int(a, b)   { return Math.floor(a + this.prng() * (b - a + 1)); }
-  random_bool(p)     { return this.prng() < p; }
-  random_choice(arr) { return arr[Math.floor(this.prng() * arr.length)]; }
-}
-```
+The `calculateFeatures()` function must use the same pseudo-random number generator (PRNG) as the art script, seeded from `tokenData.hash` in the same way and called in the same order. This ensures that the features returned by `calculateFeatures()` are consistent with the actual visual output of the project.
 
 ---