diff --git a/tests/3_signal_pipeline/outputs/anthropic_claude-opus-4.5 TEMP_0.7.js b/tests/3_signal_pipeline/outputs/anthropic_claude-opus-4.5 TEMP_0.7.js
new file mode 100644
index 0000000..e94a589
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/anthropic_claude-opus-4.5 TEMP_0.7.js	
@@ -0,0 +1,46 @@
+async function analyzeSignal(yamlString) {
+  const [
+    { default: jsYaml },
+    math,
+    { default: ndarray },
+    ndarrayFft,
+    DOMPurify
+  ] = await Promise.all([
+    import('https://esm.sh/js-yaml'),
+    import('https://esm.sh/mathjs'),
+    import('https://esm.sh/ndarray'),
+    import('https://esm.sh/ndarray-fft'),
+    import('https://esm.sh/dompurify')
+  ]);
+
+  const cfg = jsYaml.load(yamlString);
+  const N = cfg.sampleRate * cfg.duration;
+  const signal = Array(N).fill(0).map((_, i) => {
+    const t = i / cfg.sampleRate;
+    return cfg.components.reduce((s, c) =>
+      s + c.amplitude * math.sin(2 * math.pi * c.frequency * t), 0);
+  });
+
+  const real = ndarray(new Float64Array(signal), [N]);
+  const imag = ndarray(new Float64Array(N), [N]);
+  ndarrayFft(1, real, imag);
+
+  const half = N / 2;
+  const mags = Array(half + 1).fill(0).map((_, k) =>
+    math.sqrt(real.get(k) ** 2 + imag.get(k) ** 2) / half);
+
+  const peaks = mags
+    .map((m, k) => ({ frequencyHz: Math.round(k * cfg.sampleRate / N), magnitude: +m.toFixed(2) }))
+    .filter(p => p.magnitude > 0.1)
+    .sort((a, b) => b.magnitude - a.magnitude);
+
+  const rows = peaks.map(p => `<tr><td>${p.frequencyHz}</td><td>${p.magnitude}</td></tr>`).join('');
+  const html = DOMPurify.sanitize(
+    `<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>${rows}</table>`
+  );
+
+  return { peaks, html, signalLength: N };
+}
+export default analyzeSignal;
+// Generation time: 6.922s
+// Result: FAIL
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/anthropic_claude-opus-4.6.js b/tests/3_signal_pipeline/outputs/anthropic_claude-opus-4.6.js
new file mode 100644
index 0000000..6e61464
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/anthropic_claude-opus-4.6.js
@@ -0,0 +1,62 @@
+async function analyzeSignal(yamlString) {
+  const [
+    jsYaml,
+    math,
+    ndarray,
+    ndarrayFft,
+    DOMPurify
+  ] = await Promise.all([
+    import("https://cdn.jsdelivr.net/npm/js-yaml@4/+esm").then(m => m.default || m),
+    import("https://cdn.jsdelivr.net/npm/mathjs@13/+esm").then(m => m.default || m),
+    import("https://cdn.jsdelivr.net/npm/ndarray@1/+esm").then(m => m.default || m),
+    import("https://cdn.jsdelivr.net/npm/ndarray-fft@1/+esm").then(m => m.default || m),
+    import("https://cdn.jsdelivr.net/npm/dompurify@3/+esm").then(m => m.default || m),
+  ]);
+
+  const config = jsYaml.load(yamlString);
+  const { sampleRate, duration, components } = config;
+  const N = sampleRate * duration;
+
+  const signalData = new Float64Array(N);
+  for (let i = 0; i < N; i++) {
+    const t = i / sampleRate;
+    let sum = 0;
+    for (const { frequency, amplitude } of components)
+      sum += amplitude * math.sin(2 * math.pi * frequency * t);
+    signalData[i] = sum;
+  }
+
+  const real = ndarray(new Float64Array(signalData), [N]);
+  const imag = ndarray(new Float64Array(N), [N]);
+
+  ndarrayFft(1, real, imag);
+
+  const half = N / 2;
+  const magnitudes = [];
+  for (let k = 0; k <= half; k++) {
+    const r = real.get(k);
+    const im = imag.get(k);
+    magnitudes.push(math.sqrt(r ** 2 + im ** 2) / half);
+  }
+
+  const peaks = magnitudes
+    .map((mag, k) => ({
+      frequencyHz: Math.round(k * sampleRate / N),
+      magnitude: Math.round(mag * 100) / 100
+    }))
+    .filter(p => p.magnitude > 0.1)
+    .sort((a, b) => b.magnitude - a.magnitude);
+
+  const rows = peaks
+    .map(p => `<tr><td>${p.frequencyHz}</td><td>${p.magnitude}</td></tr>`)
+    .join("");
+
+  const html = DOMPurify.sanitize(
+    `<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>${rows}</table>`
+  );
+
+  return { peaks, html, signalLength: N };
+}
+export default analyzeSignal;
+// Generation time: 9.844s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/anthropic_claude-sonnet-4.5 TEMP_0.7.js b/tests/3_signal_pipeline/outputs/anthropic_claude-sonnet-4.5 TEMP_0.7.js
new file mode 100644
index 0000000..c7933fa
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/anthropic_claude-sonnet-4.5 TEMP_0.7.js	
@@ -0,0 +1,54 @@
+const analyzeSignal = async (yamlStr) => {
+  const [
+    { load: loadYaml },
+    math,
+    ndarray,
+    { fft },
+    DOMPurify
+  ] = await Promise.all([
+    import('https://cdn.jsdelivr.net/npm/js-yaml@4/dist/js-yaml.mjs'),
+    import('https://cdn.jsdelivr.net/npm/mathjs@12/lib/esm/index.js'),
+    import('https://cdn.jsdelivr.net/npm/ndarray@1/+esm'),
+    import('https://cdn.jsdelivr.net/npm/ndarray-fft@1/+esm'),
+    import('https://cdn.jsdelivr.net/npm/dompurify@3/dist/purify.es.mjs')
+  ]);
+
+  const config = loadYaml(yamlStr);
+  const N = config.sampleRate * config.duration;
+  
+  const signal = Array.from({ length: N }, (_, i) => {
+    const t = i / config.sampleRate;
+    return config.components.reduce((sum, { frequency, amplitude }) =>
+      sum + amplitude * math.sin(2 * math.pi * frequency * t), 0);
+  });
+
+  const real = ndarray(new Float64Array(signal), [N]);
+  const imag = ndarray(new Float64Array(N), [N]);
+  
+  fft(1, real, imag);
+
+  const magnitude = Array.from({ length: Math.floor(N / 2) + 1 }, (_, k) =>
+    math.sqrt(math.pow(real.get(k), 2) + math.pow(imag.get(k), 2)) / (N / 2));
+
+  const peaks = magnitude
+    .map((mag, k) => ({ 
+      frequencyHz: Math.round(k * config.sampleRate / N), 
+      magnitude: Math.round(mag * 100) / 100 
+    }))
+    .filter(({ magnitude }) => magnitude > 0.1)
+    .sort((a, b) => b.magnitude - a.magnitude);
+
+  const html = `<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>${
+    peaks.map(({ frequencyHz, magnitude }) => 
+      `<tr><td>${frequencyHz}</td><td>${magnitude}</td></tr>`).join('')
+  }</table>`;
+
+  return {
+    peaks,
+    html: DOMPurify.sanitize(html),
+    signalLength: N
+  };
+};
+export default analyzeSignal;
+// Generation time: 8.641s
+// Result: FAIL
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/anthropic_claude-sonnet-4.6.js b/tests/3_signal_pipeline/outputs/anthropic_claude-sonnet-4.6.js
new file mode 100644
index 0000000..2768de3
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/anthropic_claude-sonnet-4.6.js
@@ -0,0 +1,60 @@
+async function analyzeSignal(yamlString) {
+  const CDN = "https://cdn.jsdelivr.net/npm";
+
+  const [{ default: jsyaml }, { create, all }, { default: ndarray }, { default: fft }, { default: DOMPurify }] =
+    await Promise.all([
+      import(`${CDN}/js-yaml/dist/js-yaml.mjs`),
+      import(`${CDN}/mathjs/src/entry/allLimitedExports.mjs`),
+      import(`${CDN}/ndarray/ndarray.mjs`),
+      import(`${CDN}/ndarray-fft/dist/ndarray-fft.mjs`),
+      import(`${CDN}/dompurify/dist/purify.es.mjs`),
+    ]);
+
+  const math = create(all);
+  const config = jsyaml.load(yamlString);
+
+  const { sampleRate, duration, components } = config;
+  const N = sampleRate * duration;
+
+  const signal = Array.from({ length: N }, (_, i) => {
+    const t = i / sampleRate;
+    return components.reduce((sum, { frequency, amplitude }) =>
+      sum + amplitude * math.sin(2 * math.pi * frequency * t), 0);
+  });
+
+  const realData = new Float64Array(signal);
+  const imagData = new Float64Array(N);
+  const real = ndarray(realData, [N]);
+  const imag = ndarray(imagData, [N]);
+
+  fft(1, real, imag);
+
+  const half = N / 2;
+  const magnitude = Array.from({ length: half + 1 }, (_, k) =>
+    math.sqrt(real.get(k) ** 2 + imag.get(k) ** 2) / half
+  );
+
+  const peaks = magnitude
+    .reduce((acc, mag, k) => {
+      if (mag > 0.1) acc.push({
+        frequencyHz: Math.round(k * sampleRate / N),
+        magnitude: Math.round(mag * 100) / 100,
+      });
+      return acc;
+    }, [])
+    .sort((a, b) => b.magnitude - a.magnitude);
+
+  const rows = peaks.map(({ frequencyHz, magnitude }) =>
+    `<tr><td>${frequencyHz}</td><td>${magnitude}</td></tr>`
+  ).join("");
+
+  const rawHtml =
+    `<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>${rows}</table>`;
+
+  const html = DOMPurify.sanitize(rawHtml);
+
+  return { peaks, html, signalLength: N };
+}
+export default analyzeSignal;
+// Generation time: 8.705s
+// Result: FAIL
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/deepseek_deepseek-v3.2.js b/tests/3_signal_pipeline/outputs/deepseek_deepseek-v3.2.js
new file mode 100644
index 0000000..5dd7566
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/deepseek_deepseek-v3.2.js
@@ -0,0 +1,59 @@
+const analyzeSignal = async (yamlString) => {
+    const { load } = await import('https://cdn.jsdelivr.net/npm/js-yaml@4.1.0/+esm');
+    const math = await import('https://cdn.jsdelivr.net/npm/mathjs@11.9.1/+esm');
+    const ndarray = await import('https://cdn.jsdelivr.net/npm/ndarray@1.0.19/+esm');
+    const fft = await import('https://cdn.jsdelivr.net/npm/ndarray-fft@1.0.6/+esm');
+    const DOMPurify = await import('https://cdn.jsdelivr.net/npm/dompurify@3.0.6/+esm');
+
+    const config = load(yamlString);
+    const { sampleRate, duration, components } = config;
+    const N = sampleRate * duration;
+    const signal = new Float64Array(N);
+
+    for (let i = 0; i < N; i++) {
+        let t = i / sampleRate;
+        let value = 0;
+        for (const comp of components) {
+            value += comp.amplitude * math.sin(2 * math.pi * comp.frequency * t);
+        }
+        signal[i] = value;
+    }
+
+    const real = ndarray.default(signal.slice());
+    const imag = ndarray.default(new Float64Array(N));
+    fft.default(1, real, imag);
+
+    const magnitudes = [];
+    const halfN = Math.floor(N / 2);
+    for (let k = 0; k <= halfN; k++) {
+        const re = real.get(k);
+        const im = imag.get(k);
+        magnitudes[k] = Math.sqrt(re * re + im * im) / halfN;
+    }
+
+    const peaks = [];
+    for (let k = 0; k <= halfN; k++) {
+        if (magnitudes[k] > 0.1) {
+            peaks.push({
+                frequencyHz: Math.round(k * sampleRate / N),
+                magnitude: Math.round(magnitudes[k] * 100) / 100
+            });
+        }
+    }
+    peaks.sort((a, b) => b.magnitude - a.magnitude);
+
+    let html = `<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>`;
+    peaks.forEach(p => {
+        html += `<tr><td>${p.frequencyHz}</td><td>${p.magnitude}</td></tr>`;
+    });
+    html += `</table>`;
+
+    return {
+        peaks,
+        html: DOMPurify.default.sanitize(html),
+        signalLength: N
+    };
+};
+export default analyzeSignal;
+// Generation time: 19.364s
+// Result: FAIL
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/google_gemini-3-flash-preview TEMP_0.35.js b/tests/3_signal_pipeline/outputs/google_gemini-3-flash-preview TEMP_0.35.js
new file mode 100644
index 0000000..fb32b51
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/google_gemini-3-flash-preview TEMP_0.35.js	
@@ -0,0 +1,54 @@
+async function analyzeSignal(yamlStr) {
+  const [
+    { load: parseYaml },
+    math,
+    ndarray,
+    fft,
+    { default: purify }
+  ] = await Promise.all([
+    import('https://cdn.skypack.dev/js-yaml'),
+    import('https://cdn.skypack.dev/mathjs'),
+    import('https://cdn.skypack.dev/ndarray'),
+    import('https://cdn.skypack.dev/ndarray-fft'),
+    import('https://cdn.skypack.dev/dompurify')
+  ]);
+
+  const { sampleRate: fs, duration, components } = parseYaml(yamlStr);
+  const N = fs * duration;
+  const signal = new Float64Array(N);
+
+  for (let i = 0; i < N; i++) {
+    const t = i / fs;
+    signal[i] = components.reduce((acc, { frequency: f, amplitude: a }) => 
+      acc + a * math.sin(2 * math.pi * f * t), 0);
+  }
+
+  const real = ndarray(new Float64Array(signal), [N]);
+  const imag = ndarray(new Float64Array(N), [N]);
+  fft(1, real, imag);
+
+  const peaks = [];
+  for (let k = 0; k <= N / 2; k++) {
+    const mag = math.sqrt(real.get(k) ** 2 + imag.get(k) ** 2) / (N / 2);
+    if (mag > 0.1) {
+      peaks.push({
+        frequencyHz: Math.round(k * fs / N),
+        magnitude: +mag.toFixed(2)
+      });
+    }
+  }
+
+  peaks.sort((a, b) => b.magnitude - a.magnitude);
+
+  const rows = peaks.map(p => `<tr><td>${p.frequencyHz}</td><td>${p.magnitude}</td></tr>`).join('');
+  const rawHtml = `<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>${rows}</table>`;
+
+  return {
+    peaks,
+    html: purify.sanitize(rawHtml),
+    signalLength: N
+  };
+}
+export default analyzeSignal;
+// Generation time: 4.379s
+// Result: FAIL
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/google_gemini-3-pro-preview TEMP_0.35.js b/tests/3_signal_pipeline/outputs/google_gemini-3-pro-preview TEMP_0.35.js
new file mode 100644
index 0000000..c7e9f5b
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/google_gemini-3-pro-preview TEMP_0.35.js	
@@ -0,0 +1,50 @@
+const analyzeSignal = async (yamlInput) => {
+  const cdn = 'https://esm.sh/',
+    [Yaml, MathPkg, ndarray, fft, DOMPurify] = await Promise.all(
+      ['js-yaml', 'mathjs', 'ndarray', 'ndarray-fft', 'dompurify'].map(lib => 
+        import(`${cdn}${lib}`).then(m => m.default || m)
+      )
+    );
+
+  const { sampleRate: sr, duration: dur, components: comps } = Yaml.load(yamlInput),
+    N = sr * dur,
+    realData = new Float64Array(N),
+    imagData = new Float64Array(N);
+
+  for (let i = 0; i < N; i++) {
+    const t = i / sr;
+    realData[i] = comps.reduce((acc, { frequency: f, amplitude: a }) => 
+      acc + a * MathPkg.sin(2 * MathPkg.pi * f * t), 0);
+  }
+
+  const r = ndarray(realData, [N]),
+    i = ndarray(imagData, [N]);
+
+  fft(1, r, i);
+
+  const peaks = [];
+  for (let k = 0; k <= N / 2; k++) {
+    const mag = MathPkg.sqrt(r.get(k) ** 2 + i.get(k) ** 2) / (N / 2);
+    if (mag > 0.1) {
+      peaks.push({
+        frequencyHz: Math.round(k * sr / N),
+        magnitude: +mag.toFixed(2)
+      });
+    }
+  }
+
+  peaks.sort((a, b) => b.magnitude - a.magnitude);
+
+  const rows = peaks.map(p => `<tr><td>${p.frequencyHz}</td><td>${p.magnitude}</td></tr>`).join(''),
+    rawHtml = `<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>${rows}</table>`,
+    purifier = DOMPurify(self);
+
+  return {
+    peaks,
+    html: purifier.sanitize(rawHtml),
+    signalLength: N
+  };
+};
+export default analyzeSignal;
+// Generation time: 50.247s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/google_gemini-3.1-flash-lite-preview.js b/tests/3_signal_pipeline/outputs/google_gemini-3.1-flash-lite-preview.js
new file mode 100644
index 0000000..a99c46c
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/google_gemini-3.1-flash-lite-preview.js
@@ -0,0 +1,42 @@
+async function analyzeSignal(yaml) {
+  const [yamlLib, math, ndarray, fft, purify] = await Promise.all([
+    import('https://cdn.skypack.dev/js-yaml'),
+    import('https://cdn.skypack.dev/mathjs'),
+    import('https://cdn.skypack.dev/ndarray'),
+    import('https://cdn.skypack.dev/ndarray-fft'),
+    import('https://cdn.skypack.dev/dompurify')
+  ]);
+
+  const { sampleRate, duration, components } = yamlLib.load(yaml);
+  const N = sampleRate * duration;
+  const real = ndarray(new Float64Array(N));
+  const imag = ndarray(new Float64Array(N));
+
+  for (let i = 0; i < N; i++) {
+    const t = i / sampleRate;
+    real.set(i, components.reduce((acc, c) => 
+      acc + c.amplitude * math.sin(2 * math.pi * c.frequency * t), 0));
+  }
+
+  fft(1, real, imag);
+
+  const peaks = [];
+  for (let k = 0; k <= N / 2; k++) {
+    const mag = math.sqrt(real.get(k) ** 2 + imag.get(k) ** 2) / (N / 2);
+    if (mag > 0.1) peaks.push({ 
+      frequencyHz: Math.round(k * sampleRate / N), 
+      magnitude: Math.round(mag * 100) / 100 
+    });
+  }
+
+  peaks.sort((a, b) => b.magnitude - a.magnitude);
+
+  const html = purify.sanitize(`<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>` +
+    peaks.map(p => `<tr><td>${p.frequencyHz}</td><td>${p.magnitude}</td></tr>`).join('') +
+    `</table>`);
+
+  return { peaks, html, signalLength: N };
+}
+export default analyzeSignal;
+// Generation time: 2.100s
+// Result: FAIL
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/google_gemini-3.1-pro-preview.js b/tests/3_signal_pipeline/outputs/google_gemini-3.1-pro-preview.js
new file mode 100644
index 0000000..4bd1879
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/google_gemini-3.1-pro-preview.js
@@ -0,0 +1,44 @@
+export async function analyzeSignal(y) {
+  const [yM, mM, nM, fM, dM] = await Promise.all([
+    'js-yaml', 'mathjs', 'ndarray', 'ndarray-fft', 'dompurify'
+  ].map(p => import(`https://esm.sh/${p}`)));
+
+  const load = yM.load || yM.default.load || yM.default;
+  const { sin, pi, sqrt } = mM.default || mM;
+  const ndarray = nM.default || nM;
+  const fft = fM.default || fM;
+  const DP = dM.default || dM;
+
+  const c = load(y);
+  const N = c.sampleRate * c.duration;
+  const R = new Float64Array(N), I = new Float64Array(N);
+
+  for (let i = 0; i < N; i++) {
+    let t = i / c.sampleRate, s = 0;
+    for (const p of c.components) s += p.amplitude * sin(2 * pi * p.frequency * t);
+    R[i] = s;
+  }
+
+  const r = ndarray(R), img = ndarray(I);
+  fft(1, r, img);
+
+  const pks = [], norm = N / 2;
+  for (let k = 0; k <= norm; k++) {
+    const m = sqrt(r.get(k) ** 2 + img.get(k) ** 2) / norm;
+    if (m > 0.1) pks.push({
+      frequencyHz: Math.round(k * c.sampleRate / N),
+      magnitude: +m.toFixed(2)
+    });
+  }
+
+  pks.sort((a, b) => b.magnitude - a.magnitude);
+
+  const h = `<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>${
+    pks.map(p => `<tr><td>${p.frequencyHz}</td><td>${p.magnitude}</td></tr>`).join('')
+  }</table>`;
+
+  return { peaks: pks, html: DP.sanitize(h), signalLength: N };
+}
+export default analyzeSignal;
+// Generation time: 50.698s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/minimax_minimax-m2.5.js b/tests/3_signal_pipeline/outputs/minimax_minimax-m2.5.js
new file mode 100644
index 0000000..e6c5f62
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/minimax_minimax-m2.5.js
@@ -0,0 +1,68 @@
+let _jsYaml, _math, _ndarray, _fft, _purify;
+
+
+  if (!_jsYaml) {
+    _jsYaml = (await import('https://cdn.jsdelivr.net/npm/js-yaml@4.1.0/dist/js-yaml.mjs')).default;
+  }
+  const { sampleRate, duration, components } = _jsYaml.load(yamlString);
+  const N = sampleRate * duration;
+
+  if (!_math) {
+    _math = await import('https://cdn.jsdelivr.net/npm/mathjs@11.8.0/lib/esm/index.js');
+  }
+
+  const signal = new Float64Array(N);
+  for (let i = 0; i < N; i++) {
+    const t = i / sampleRate;
+    let sum = 0;
+    for (const { frequency, amplitude } of components) {
+      sum += amplitude * _math.sin(2 * _math.pi * frequency * t);
+    }
+    signal[i] = sum;
+  }
+
+  if (!_ndarray) {
+    const ndMod = await import('https://cdn.jsdelivr.net/npm/ndarray@1.0.19/index.mjs');
+    _ndarray = ndMod.default || ndMod.ndarray;
+  }
+  if (!_fft) {
+    const fftMod = await import('https://cdn.jsdelivr.net/npm/ndarray-fft@1.0.0/index.mjs');
+    _fft = fftMod.fft || fftMod.default;
+  }
+  if (!_purify) {
+    const purifyMod = await import('https://cdn.jsdelivr.net/npm/dompurify@3.0.3/dist/purify.es.js');
+    _purify = purifyMod.default || purifyMod;
+  }
+
+  const real = _ndarray(signal, [N]);
+  const imag = _ndarray(new Float64Array(N), [N]);
+
+  _fft(1, real, imag);
+
+  const half = N / 2;
+  const peaks = [];
+  for (let k = 0; k <= half; k++) {
+    const re = real.get(k);
+    const im = imag.get(k);
+    const mag = _math.sqrt(re * re + im * im) / half;
+    if (mag > 0.1) {
+      const freq = Math.round(k * sampleRate / N);
+      const magRounded = Math.round(mag * 100) / 100;
+      peaks.push({ frequencyHz: freq, magnitude: magRounded });
+    }
+  }
+  peaks.sort((a, b) => b.magnitude - a.magnitude);
+
+  let html = '<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>';
+  for (const p of peaks) {
+    html += `<tr><td>${p.frequencyHz}</td><td>${p.magnitude.toFixed(2)}</td></tr>`;
+  }
+  html += '</table>';
+
+  const sanitized = _purify.sanitize(html);
+
+  return { peaks, html: sanitized, signalLength: N };
+}
+export default analyzeSignal;
+// Generation time: 94.075s
+// Result: FAIL
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/moonshotai_kimi-k2.5.js b/tests/3_signal_pipeline/outputs/moonshotai_kimi-k2.5.js
new file mode 100644
index 0000000..985ad36
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/moonshotai_kimi-k2.5.js
@@ -0,0 +1,27 @@
+const analyzeSignal=async y=>{
+  const[{load},{sin,pi,sqrt},ndarray,fft,{default:DOMPurify}]=await Promise.all([
+    import('https://cdn.jsdelivr.net/npm/js-yaml@4.1.0/dist/js-yaml.mjs'),
+    import('https://cdn.jsdelivr.net/npm/mathjs@11.8.0/lib/esm/index.js'),
+    import('https://cdn.jsdelivr.net/npm/ndarray@1.0.19/+esm'),
+    import('https://cdn.jsdelivr.net/npm/ndarray-fft@1.0.3/+esm'),
+    import('https://cdn.jsdelivr.net/npm/dompurify@3.0.3/dist/purify.es.mjs')
+  ]);
+  const{sampleRate:s,duration:d,components:c}=load(y),N=s*d,
+  signal=Array(N).fill().map((_,i)=>{
+    const t=i/s;
+    return c.reduce((a,{frequency:f,amplitude:m})=>a+m*sin(2*pi*f*t),0)
+  }),
+  real=ndarray(signal),
+  imag=ndarray(Array(N).fill(0));
+  fft(1,real,imag);
+  const H=N/2,
+  mags=Array(H+1).fill().map((_,k)=>sqrt(real.get(k)**2+imag.get(k)**2)/H),
+  peaks=mags.map((m,k)=>({frequencyHz:Math.round(k*s/N),magnitude:Math.round(m*100)/100}))
+    .filter(p=>p.magnitude>.1)
+    .sort((a,b)=>b.magnitude-a.magnitude),
+  html=`<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>${peaks.map(p=>`<tr><td>${p.frequencyHz}</td><td>${p.magnitude}</td></tr>`).join('')}</table>`;
+  return{peaks,html:DOMPurify.sanitize(html),signalLength:N}
+}
+export default analyzeSignal;
+// Generation time: 171.544s
+// Result: FAIL
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/openai_gpt-5.3-codex.js b/tests/3_signal_pipeline/outputs/openai_gpt-5.3-codex.js
new file mode 100644
index 0000000..2337114
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/openai_gpt-5.3-codex.js
@@ -0,0 +1,64 @@
+const libsPromise = (async () => {
+  const [y, m, n, f, d] = await Promise.all([
+    import("https://cdn.jsdelivr.net/npm/js-yaml@4.1.0/+esm"),
+    import("https://esm.sh/mathjs@13.0.3"),
+    import("https://esm.sh/ndarray@1.0.19"),
+    import("https://esm.sh/ndarray-fft@1.0.3"),
+    import("https://unpkg.com/dompurify@3.1.6/dist/purify.es.mjs")
+  ]);
+  return {
+    yaml: y.default?.load ? y.default : y,
+    math: m.default?.sin ? m.default : m,
+    ndarray: n.default || n,
+    fft: f.default || f.fft || f,
+    DOMPurify: d.default?.sanitize ? d.default : d
+  };
+})();
+
+async function analyzeSignal(yamlString) {
+  const { yaml, math, ndarray, fft, DOMPurify } = await libsPromise;
+  const cfg = yaml.load(String(yamlString || "")) || {};
+  const sampleRate = Number(cfg.sampleRate) || 64;
+  const duration = Number(cfg.duration) || 1;
+  const components = Array.isArray(cfg.components) ? cfg.components : [];
+  const N = Math.max(1, Math.floor(sampleRate * duration));
+  const signal = new Float64Array(N);
+
+  for (let i = 0; i < N; i++) {
+    const t = i / sampleRate;
+    let v = 0;
+    for (let j = 0; j < components.length; j++) {
+      const c = components[j] || {};
+      v += (Number(c.amplitude) || 0) * math.sin(2 * math.pi * (Number(c.frequency) || 0) * t);
+    }
+    signal[i] = v;
+  }
+
+  const realData = new Float64Array(signal);
+  const imagData = new Float64Array(N);
+  const real = ndarray(realData, [N]);
+  const imag = ndarray(imagData, [N]);
+  fft(1, real, imag);
+
+  const half = Math.floor(N / 2);
+  const norm = N / 2 || 1;
+  const peaks = [];
+
+  for (let k = 0; k <= half; k++) {
+    const mag = math.sqrt(real.get(k) ** 2 + imag.get(k) ** 2) / norm;
+    if (mag > 0.1) peaks.push({
+      frequencyHz: Math.round((k * sampleRate) / N),
+      magnitude: Number(mag.toFixed(2))
+    });
+  }
+
+  peaks.sort((a, b) => b.magnitude - a.magnitude);
+
+  const rows = peaks.map(p => `<tr><td>${p.frequencyHz}</td><td>${p.magnitude}</td></tr>`).join("");
+  const html = DOMPurify.sanitize(`<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>${rows}</table>`);
+
+  return { peaks, html, signalLength: N };
+}
+export default analyzeSignal;
+// Generation time: 28.814s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/x-ai_grok-4.js b/tests/3_signal_pipeline/outputs/x-ai_grok-4.js
new file mode 100644
index 0000000..103ea05
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/x-ai_grok-4.js
@@ -0,0 +1,51 @@
+async function analyzeSignal(yamlString) {
+  const { load } = await import('https://cdn.jsdelivr.net/npm/js-yaml@4.1.0/dist/js-yaml.mjs');
+  const { create, all } = await import('https://cdn.jsdelivr.net/npm/mathjs@12.4.1/+esm');
+  const math = create(all);
+  const ndarray = (await import('https://unpkg.com/ndarray@1.0.19?module')).default;
+  const fft = (await import('https://unpkg.com/ndarray-fft@1.0.3?module')).default;
+  const DOMPurify = (await import('https://cdn.jsdelivr.net/npm/dompurify@3.1.6/dist/purify.es.js')).default;
+  const config = load(yamlString);
+  const sampleRate = config.sampleRate;
+  const duration = config.duration;
+  const N = sampleRate * duration;
+  const signal = new Array(N);
+  for (let i = 0; i < N; i++) {
+    const t = i / sampleRate;
+    let val = 0;
+    for (let comp of config.components) {
+      val += comp.amplitude * math.sin(2 * math.pi * comp.frequency * t);
+    }
+    signal[i] = val;
+  }
+  const real = ndarray(new Float64Array(signal), [N]);
+  const imag = ndarray(new Float64Array(N), [N]);
+  fft(1, real, imag);
+  const halfN = N / 2;
+  const magnitude = new Array(Math.floor(halfN) + 1);
+  for (let k = 0; k < magnitude.length; k++) {
+    magnitude[k] = math.sqrt(math.pow(real.get(k), 2) + math.pow(imag.get(k), 2)) / halfN;
+  }
+  const peaks = [];
+  for (let k = 0; k < magnitude.length; k++) {
+    const m = magnitude[k];
+    if (m > 0.1) {
+      const freq = k * sampleRate / N;
+      peaks.push({
+        frequencyHz: Math.round(freq),
+        magnitude: Number(m.toFixed(2))
+      });
+    }
+  }
+  peaks.sort((a, b) => b.magnitude - a.magnitude);
+  let html = '<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>';
+  for (let p of peaks) {
+    html += `<tr><td>${p.frequencyHz}</td><td>${p.magnitude}</td></tr>`;
+  }
+  html += '</table>';
+  const sanitized = DOMPurify.sanitize(html);
+  return { peaks, html: sanitized, signalLength: N };
+}
+export default analyzeSignal;
+// Generation time: 85.724s
+// Result: FAIL
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/z-ai_glm-4.7.js b/tests/3_signal_pipeline/outputs/z-ai_glm-4.7.js
new file mode 100644
index 0000000..88de7b8
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/z-ai_glm-4.7.js
@@ -0,0 +1,60 @@
+async function analyzeSignal(str) {
+  const [
+    { load },
+    { create, all },
+    { default: ndarray },
+    { default: ndfft },
+    { default: purify }
+  ] = await Promise.all([
+    import('https://cdn.skypack.dev/js-yaml'),
+    import('https://cdn.skypack.dev/mathjs'),
+    import('https://cdn.skypack.dev/ndarray'),
+    import('https://cdn.skypack.dev/ndarray-fft'),
+    import('https://cdn.skypack.dev/dompurify')
+  ]);
+
+  const m = create(all);
+  const { sampleRate: s, duration: d, components: c } = load(str);
+  const N = s * d;
+  const sig = new Float64Array(N);
+
+  for (let i = 0; i < N; i++) {
+    const t = i / s;
+    let v = 0;
+    for (const { frequency: f, amplitude: a } of c) {
+      v += a * m.sin(2 * m.pi * f * t);
+    }
+    sig[i] = v;
+  }
+
+  const r = ndarray(sig);
+  const im = ndarray(new Float64Array(N));
+  ndfft(1, r, im);
+
+  const peaks = [];
+  const half = N / 2;
+
+  for (let k = 0; k <= half; k++) {
+    const rv = r.get(k);
+    const iv = im.get(k);
+    const mag = m.sqrt(rv * rv + iv * iv) / half;
+    if (mag > 0.1) {
+      peaks.push({
+        frequencyHz: Math.round(k * s / N),
+        magnitude: Number(mag.toFixed(2))
+      });
+    }
+  }
+
+  peaks.sort((x, y) => y.magnitude - x.magnitude);
+
+  const html = peaks.reduce((h, p) => 
+    `${h}<tr><td>${p.frequencyHz}</td><td>${p.magnitude}</td></tr>`, 
+    `<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>`
+  ) + "</table>";
+
+  return { peaks, html: purify.sanitize(html), signalLength: N };
+}
+export default analyzeSignal;
+// Generation time: 341.010s
+// Result: FAIL
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/z-ai_glm-5.js b/tests/3_signal_pipeline/outputs/z-ai_glm-5.js
new file mode 100644
index 0000000..05e31aa
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/z-ai_glm-5.js
@@ -0,0 +1,42 @@
+async function analyzeSignal(yamlStr) {
+  const [{ default: yaml }, { default: math }, { default: nd }, { default: fft }, { default: purify }] = await Promise.all([
+    import('https://esm.sh/js-yaml'),
+    import('https://esm.sh/mathjs'),
+    import('https://esm.sh/ndarray'),
+    import('https://esm.sh/ndarray-fft'),
+    import('https://esm.sh/dompurify')
+  ]);
+
+  const { sampleRate: sr, duration, components } = yaml.load(yamlStr);
+  const N = sr * duration;
+  const sig = Array.from({ length: N }, (_, i) =>
+    components.reduce((s, { frequency, amplitude }) =>
+      s + amplitude * math.sin(2 * math.pi * frequency * i / sr), 0)
+  );
+
+  const re = nd(new Float64Array(sig), [N]);
+  const im = nd(new Float64Array(N), [N]);
+  fft(1, re, im);
+
+  const peaks = [];
+  for (let k = 0; k <= N / 2; k++) {
+    const mag = math.sqrt(re.get(k) ** 2 + im.get(k) ** 2) / (N / 2);
+    if (mag > 0.1) peaks.push({
+      frequencyHz: Math.round(k * sr / N),
+      magnitude: +mag.toFixed(2)
+    });
+  }
+
+  peaks.sort((a, b) => b.magnitude - a.magnitude);
+
+  return {
+    peaks,
+    html: purify.sanitize(`<table><tr><th>Frequency (Hz)</th><th>Magnitude</th></tr>${
+      peaks.map(p => `<tr><td>${p.frequencyHz}</td><td>${p.magnitude}</td></tr>`).join('')
+    }</table>`),
+    signalLength: N
+  };
+}
+export default analyzeSignal;
+// Generation time: 285.288s
+// Result: FAIL
\ No newline at end of file