quietlight/skraak_mcp - Change 7HRFWKAFNNCCK2GMGHUL6G7KUEQP6TPBSMZEILIY5ELWU4LSUKOAC

me, and fix skill to include cyclic recording pattern

Created by quietlight 2 days ago

7HRFWKAFNNCCK2GMGHUL6G7KUEQP6TPBSMZEILIY5ELWU4LSUKOAC

Dependencies

In channels

main

Change contents

Deletion in tools/calls_clip_bench_test.go at line 5 [2.1]
B:BD[2.45] → [2.45:54]
```
	"image"
```
Deletion in tools/calls_clip_bench_test.go at line 10 [2.1]
B:BD[2.96] → [2.96:176]
```
	"github.com/madelynnblue/go-dsp/fft"
	"github.com/madelynnblue/go-dsp/window"
```
Replacement in tools/calls_clip_bench_test.go at line 12 [2.1]
B:BD[2.179] → [2.179:226]
```
const testWAV = "../audio/20211028_211500.WAV"
```
[2.179]
[2.226]
```
const benchWAV = "../audio/20211028_211500.WAV"
```

Replacement in tools/calls_clip_bench_test.go at line 14 [2.1]

B:BD[2.227] → [2.227:289]

// ========== Individual pipeline stage benchmarks ==========

[2.227]

[2.289]

// ==================== WAV I/O ====================

Replacement in tools/calls_clip_bench_test.go at line 19 [2.1]
B:BD[2.374] → [2.374:419]
```
		_, _, err := utils.ReadWAVSamples(testWAV)
```
[2.374]
[2.419]
```
		_, _, err := utils.ReadWAVSamples(benchWAV)
```

Insertion in tools/calls_clip_bench_test.go at line 23 [2.1]

[2.457]

	}
}
func BenchmarkConvertToFloat64_16bit(b *testing.B) {
	// Simulate 16-bit mono WAV data (same size as test file: 14.32M samples)
	numSamples := 14320000
	data := make([]byte, numSamples*2)
	for i := range numSamples {
		binary.LittleEndian.PutUint16(data[i*2:], uint16(i%65536))

Insertion in tools/calls_clip_bench_test.go at line 33 [2.1]

[2.460]

	b.ResetTimer()
	b.ReportAllocs()
	for i := 0; i < b.N; i++ {
		_ = convertToFloat64Bench(data, 16, 1)
	}

Replacement in tools/calls_clip_bench_test.go at line 40 [2.1]

B:BD[2.463] → [2.463:615]

func BenchmarkExtractSegment(b *testing.B) {
	samples, sr, _ := utils.ReadWAVSamples(testWAV)
	b.Logf("full file: %d samples, sr=%d", len(samples), sr)

[2.463]

[2.615]

// Duplicate of convertToFloat64 for benchmarking (unexported in utils)
func convertToFloat64Bench(data []byte, bitsPerSample, channels int) []float64 {
	bytesPerSample := bitsPerSample / 8
	blockAlign := bytesPerSample * channels
	numSamples := len(data) / blockAlign
	samples := make([]float64, numSamples)
	for i := range numSamples {
		offset := i * blockAlign
		sample := int16(binary.LittleEndian.Uint16(data[offset : offset+2]))
		samples[i] = float64(sample) / 32768.0
	}
	return samples
}
func BenchmarkWriteWAV(b *testing.B) {
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)
	segSamples := utils.ExtractSegmentSamples(samples, sr, 872, 895)
	b.Logf("segment samples=%d", len(segSamples))

Replacement in tools/calls_clip_bench_test.go at line 61 [2.1]

B:BD[2.677] → [2.677:790]

		seg := utils.ExtractSegmentSamples(samples, sr, 872, 895)
		if len(seg) == 0 {
			b.Fatal("empty segment")
		}

[2.677]

[2.790]

		f, _ := os.CreateTemp("", "bench_*.wav")
		utils.WriteWAVFile(f.Name(), segSamples, sr)
		f.Close()
		os.Remove(f.Name())

Replacement in tools/calls_clip_bench_test.go at line 68 [2.1]

B:BD[2.796] → [2.796:1014]

func BenchmarkResampleRate(b *testing.B) {
	samples, _, _ := utils.ReadWAVSamples(testWAV)
	// Simulate 48kHz source by treating the 16kHz data as 48kHz
	b.Logf("resampling %d samples from 48000->16000", len(samples))

[2.796]

[2.1014]

// ==================== Resample ====================
func BenchmarkResampleRate_48k(b *testing.B) {
	samples, _, _ := utils.ReadWAVSamples(benchWAV)
	b.Logf("resampling %d samples 48000->16000", len(samples))

Replacement in tools/calls_clip_bench_test.go at line 80 [2.1]

B:BD[2.1126] → [2.1126:1336]

func BenchmarkResampleRate250k(b *testing.B) {
	samples, _, _ := utils.ReadWAVSamples(testWAV)
	// Simulate 250kHz source (AudioMoth high-gain)
	b.Logf("resampling %d samples from 250000->16000", len(samples))

[2.1126]

[2.1336]

func BenchmarkResampleRate_250k(b *testing.B) {
	samples, _, _ := utils.ReadWAVSamples(benchWAV)
	b.Logf("resampling %d samples 250000->16000", len(samples))

Insertion in tools/calls_clip_bench_test.go at line 89 [2.1]
[2.1448]
[2.1448]
```
// ==================== Spectrogram pipeline ====================
```

Replacement in tools/calls_clip_bench_test.go at line 92 [2.1]

B:BD[2.1449] → [2.1449:1540]

func BenchmarkSpectrogram(b *testing.B) {
	samples, sr, _ := utils.ReadWAVSamples(testWAV)

[2.1449]

[2.1540]

func BenchmarkExtractSegment(b *testing.B) {
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)
	b.Logf("full file: %d samples, sr=%d", len(samples), sr)
	b.ResetTimer()
	b.ReportAllocs()
	for i := 0; i < b.N; i++ {
		seg := utils.ExtractSegmentSamples(samples, sr, 872, 895)
		if len(seg) == 0 {
			b.Fatal("empty segment")
		}
	}
}
func BenchmarkPowerSpectrumFFT_512(b *testing.B) {
	n := 512
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)
	segSamples := utils.ExtractSegmentSamples(samples, sr, 872, 895)
	frameData := make([]float64, n)
	power := make([]float64, n/2+1)
	scratch := make([]complex128, n)
	b.ResetTimer()
	b.ReportAllocs()
	for i := 0; i < b.N; i++ {
		// Simulate the windowing step (Hann) + FFT
		for j := 0; j < n; j++ {
			frameData[j] = segSamples[j] * 0.5 * (1.0 - math.Cos(2.0*math.Pi*float64(j)/float64(n-1)))
		}
		utils.PowerSpectrumFFT(frameData, power, scratch)
	}
}
func BenchmarkSpectrogram_23s(b *testing.B) {
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)

Replacement in tools/calls_clip_bench_test.go at line 138 [2.1]

B:BD[2.1931] → [2.1931:2070]

func BenchmarkSpectrogramLong(b *testing.B) {
	// 60-second segment — typical long clip
	samples, sr, _ := utils.ReadWAVSamples(testWAV)

[2.1931]

[2.2070]

func BenchmarkSpectrogram_60s(b *testing.B) {
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)

Replacement in tools/calls_clip_bench_test.go at line 142 [2.1]
B:BD[2.2179] → [2.2179:2231]
```
	b.Logf("long segment samples=%d", len(segSamples))
```
[2.2179]
[2.2231]
```
	b.Logf("60s segment samples=%d", len(segSamples))
```
Insertion in tools/calls_clip_bench_test.go at line 152 [2.1]
[2.2406]
[2.2406]
```
// ==================== Image creation & resize ====================
```
Replacement in tools/calls_clip_bench_test.go at line 156 [2.1]
B:BD[2.2458] → [2.2458:2507]
```
	samples, sr, _ := utils.ReadWAVSamples(testWAV)
```
[2.2458]
[2.2507]
```
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)
```
Replacement in tools/calls_clip_bench_test.go at line 171 [2.1]
B:BD[2.2874] → [2.2874:2923]
```
	samples, sr, _ := utils.ReadWAVSamples(testWAV)
```
[2.2874]
[2.2923]
```
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)
```

Insertion in tools/calls_clip_bench_test.go at line 186 [2.1]

[2.3287]

func BenchmarkApplyL4Colormap(b *testing.B) {
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)
	segSamples := utils.ExtractSegmentSamples(samples, sr, 872, 895)
	cfg := utils.DefaultSpectrogramConfig(16000)
	spect := utils.GenerateSpectrogram(segSamples, cfg)
	b.ResetTimer()
	b.ReportAllocs()
	for i := 0; i < b.N; i++ {
		colorData := utils.ApplyL4Colormap(spect)
		if colorData == nil {
			b.Fatal("nil colormap")
		}
	}
}

Replacement in tools/calls_clip_bench_test.go at line 202 [2.1]
B:BD[2.3331] → [2.3331:3380]
```
	samples, sr, _ := utils.ReadWAVSamples(testWAV)
```
[2.3331]
[2.3380]
```
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)
```
Replacement in tools/calls_clip_bench_test.go at line 218 [2.1]
B:BD[2.3796] → [2.3796:3845]
```
	samples, sr, _ := utils.ReadWAVSamples(testWAV)
```
[2.3796]
[2.3845]
```
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)
```
Insertion in tools/calls_clip_bench_test.go at line 232 [2.1]
[2.4216]
[2.4216]
```
// ==================== PNG write ====================
```

Replacement in tools/calls_clip_bench_test.go at line 235 [2.1]

B:BD[2.4217] → [2.4217:4305]

func BenchmarkWritePNG(b *testing.B) {
	samples, sr, _ := utils.ReadWAVSamples(testWAV)

[2.4217]

[2.4305]

func BenchmarkWritePNG_224(b *testing.B) {
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)

Deletion in tools/calls_clip_bench_test.go at line 247 [2.1]

B:BD[2.4691] → [2.4691:5084]

		f.Close()
		os.Remove(f.Name())
	}
}
func BenchmarkWriteWAV(b *testing.B) {
	samples, sr, _ := utils.ReadWAVSamples(testWAV)
	segSamples := utils.ExtractSegmentSamples(samples, sr, 872, 895)
	b.Logf("segment samples=%d", len(segSamples))
	b.ResetTimer()
	b.ReportAllocs()
	for i := 0; i < b.N; i++ {
		f, _ := os.CreateTemp("", "bench_*.wav")
		utils.WriteWAVFile(f.Name(), segSamples, sr)

Deletion in tools/calls_clip_bench_test.go at line 249 [2.1]

B:BD[2.5118] → [2.5118:6748]

	}
}
// ========== Raw FFT benchmark (to isolate FFT cost from spectrogram overhead) ==========
func BenchmarkFFTRaw(b *testing.B) {
	const windowSize = 512
	hann := window.Hann(windowSize)
	samples, sr, _ := utils.ReadWAVSamples(testWAV)
	segSamples := utils.ExtractSegmentSamples(samples, sr, 872, 895)
	numFrames := (len(segSamples)-windowSize)/256 + 1
	b.Logf("frames=%d", numFrames)
	frameData := make([]float64, windowSize)
	b.ResetTimer()
	b.ReportAllocs()
	for i := 0; i < b.N; i++ {
		for frame := 0; frame < numFrames; frame++ {
			start := frame * 256
			for j := 0; j < windowSize; j++ {
				frameData[j] = segSamples[start+j] * hann[j]
			}
			fft.FFTReal(frameData)
		}
	}
}
// ========== convertToFloat64 isolated benchmark ==========
func BenchmarkConvertToFloat64_16bit(b *testing.B) {
	// Simulate 16-bit mono WAV data (same size as test file)
	numSamples := 14320000
	data := make([]byte, numSamples*2)
	// Fill with dummy data
	for i := range numSamples {
		binary.LittleEndian.PutUint16(data[i*2:], uint16(i%65536))
	}
	b.ResetTimer()
	b.ReportAllocs()
	for i := 0; i < b.N; i++ {
		_ = convertToFloat64Bench(data, 16, 1)
	}
}
// Duplicate of convertToFloat64 for benchmarking (unexported in utils)
func convertToFloat64Bench(data []byte, bitsPerSample, channels int) []float64 {
	bytesPerSample := bitsPerSample / 8
	blockAlign := bytesPerSample * channels
	numSamples := len(data) / blockAlign
	samples := make([]float64, numSamples)
	for i := range numSamples {
		offset := i * blockAlign
		sample := int16(binary.LittleEndian.Uint16(data[offset : offset+2]))
		samples[i] = float64(sample) / 32768.0

Deletion in tools/calls_clip_bench_test.go at line 250 [2.1]
B:BD[2.6751] → [2.6751:6767]
```
	return samples
```
Replacement in tools/calls_clip_bench_test.go at line 252 [2.1]
B:BD[2.6770] → [2.6770:6820]
```
// ========== Full pipeline benchmarks ==========
```
[2.6770]
[2.6820]
```
// ==================== Full pipeline ====================
```
Replacement in tools/calls_clip_bench_test.go at line 255 [2.1]
B:BD[2.6871] → [2.6871:6920]
```
	samples, sr, _ := utils.ReadWAVSamples(testWAV)
```
[2.6871]
[2.6920]
```
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)
```
Replacement in tools/calls_clip_bench_test.go at line 280 [2.1]
B:BD[2.7611] → [2.7611:7660]
```
	samples, sr, _ := utils.ReadWAVSamples(testWAV)
```
[2.7611]
[2.7660]
```
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)
```

Replacement in tools/calls_clip_bench_test.go at line 305 [2.1]

B:BD[2.8342] → [2.8342:8414]

// ========== Allocation profiling: measure allocs per stage ==========

[2.8342]

[2.8414]

func BenchmarkFullPipelineWavOnly(b *testing.B) {
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)
	b.ResetTimer()
	b.ReportAllocs()
	for i := 0; i < b.N; i++ {
		segSamples := utils.ExtractSegmentSamples(samples, sr, 872, 895)
		outputSR := sr
		if sr > 16000 {
			segSamples = utils.ResampleRate(segSamples, sr, 16000)
			outputSR = 16000
		}
		f, _ := os.CreateTemp("", "bench_*.wav")
		utils.WriteWAVFile(f.Name(), segSamples, outputSR)
		f.Close()
		os.Remove(f.Name())
	}
}
// ==================== Data dimension report ====================

Replacement in tools/calls_clip_bench_test.go at line 325 [2.1]

B:BD[2.8415] → [2.8415:8513]

func TestPipelineAllocationSizes(t *testing.T) {
	samples, sr, _ := utils.ReadWAVSamples(testWAV)

[2.8415]

[2.8513]

func TestPipelineDimensions(t *testing.T) {
	samples, sr, _ := utils.ReadWAVSamples(benchWAV)

Replacement in tools/calls_clip_bench_test.go at line 329 [2.1]

B:BD[2.8580] → [2.8580:8671]

	t.Logf("Input: %d samples, sr=%d, segment=%d samples", len(samples), sr, len(segSamples))

[2.8580]

[2.8671]

	t.Logf("Input: %d samples, sr=%d, segment=%d samples (%.1fs)",
		len(samples), sr, len(segSamples), float64(len(segSamples))/float64(sr))

Replacement in tools/calls_clip_bench_test.go at line 333 [2.1]

B:BD[2.8718] → [2.8718:8844]

	spect := utils.GenerateSpectrogram(segSamples, cfg)
	t.Logf("Spectrogram: %d x %d (freq x time)", len(spect), len(spect[0]))

[2.8718]

[2.8844]

	numFrames := (len(segSamples)-cfg.WindowSize)/cfg.HopSize + 1
	numBins := cfg.WindowSize/2 + 1
	t.Logf("Spectrogram: %d freq bins x %d time frames = %d values",
		numBins, numFrames, numBins*numFrames)

Replacement in tools/calls_clip_bench_test.go at line 338 [2.1]

B:BD[2.8845] → [2.8845:8960]

	colorData := utils.ApplyL4Colormap(spect)
	t.Logf("ColorData: %d x %d pixels", len(colorData), len(colorData[0]))

[2.8845]

[2.8960]

	spect := utils.GenerateSpectrogram(segSamples, cfg)
	t.Logf("Output: %d x %d (freq x time)", len(spect), len(spect[0]))

Replacement in tools/calls_clip_bench_test.go at line 342 [2.1]

B:BD[2.9003] → [2.9003:9087]

	bounds := img.Bounds()
	t.Logf("Grayscale image: %dx%d", bounds.Dx(), bounds.Dy())

[2.9003]

[2.9087]

	t.Logf("Grayscale image: %dx%d pixels, %d bytes",
		img.Bounds().Dx(), img.Bounds().Dy(), img.Bounds().Dx()*img.Bounds().Dy())

Replacement in tools/calls_clip_bench_test.go at line 346 [2.1]

B:BD[2.9133] → [2.9133:9218]

	rBounds := resized.Bounds()
	t.Logf("Resized: %dx%d", rBounds.Dx(), rBounds.Dy())
}

[2.9133]

[2.9218]

	t.Logf("Resized 224: %dx%d", resized.Bounds().Dx(), resized.Bounds().Dy())

Replacement in tools/calls_clip_bench_test.go at line 348 [2.1]

B:BD[2.9219] → [2.9219:9514]

// ========== Math benchmarks: isolate costly operations ==========
func BenchmarkMathLog10(b *testing.B) {
	vals := make([]float64, 10000)
	for i := range vals {
		vals[i] = float64(i+1) * 0.001
	}
	b.ResetTimer()
	for i := 0; i < b.N; i++ {
		for _, v := range vals {
			math.Log10(v)
		}
	}

[2.9219]

[2.9514]

	resized448 := utils.ResizeImage(img, 448, 448)
	t.Logf("Resized 448: %dx%d", resized448.Bounds().Dx(), resized448.Bounds().Dy())

Deletion in tools/calls_clip_bench_test.go at line 351 [2.1]
B:BD[2.9516] → [2.9516:9604]
```
// Dummy to satisfy image.Image interface check
var _ image.Image = (*image.Gray)(nil)
```

Deletion in me.txt at line 1 [3.1]

B:BD[3.1] → [4.92:210]

N14,cMla8Vtfl3uj,/media/david/Pomona-4/Pomona/N14/2026-04-06,2025-14-06,16000,2242
change cluster name to 2026-04-06

Replacement in me.txt at line 175 [3.1]

B:BD[5.2998] → [6.828:1532]

skraak calls classify --folder . --reviewer David --color --filter opensoundscape-multi-1.0 --species lotkoe1 \
  --bind a=eurbla, \
  --bind b=nezbel1, \
  --bind c=comcha, \
  --bind d=saddle3, \
  --bind e=pipipi1, \
  --bind f=nezfan1, \
  --bind g=gryger1, \
  --bind i=tui1, \
  --bind j=nezkak1, \
  --bind k=kea1, \
  --bind l=lotkoe1, \
  --bind m=morepo2, \
  --bind n=nezrob3, \
  --bind o=soioys1, \
  --bind p=malpar2, \
  --bind r=riflem1, \
  --bind s=silver3, \
  --bind t=tomtit1, \
  --bind u=nezpig2, \
  --bind v=brncre, \
  --bind w=weka1,  \
  --bind x=Noise, \
  --bind z="Don't Know", \
  --bind 1=Kiwi+Duet, \
  --bind 2=Kiwi+Female, \
  --bind 3=Kiwi+Male, \
  --bind 4=Kiwi, \

[5.2998]

[6.1532]

skraak calls classify --folder A05/2026-04-06 --reviewer David --color --filter opensoundscape-kiwi-1.2 --species Kiwi+Male \
  --bind a=eurbla \
  --bind b=nezbel1 \
  --bind c=comcha \
  --bind d=saddle3 \
  --bind e=pipipi1 \
  --bind f=nezfan1 \
  --bind g=gryger1 \
  --bind i=tui1 \
  --bind j=nezkak1 \
  --bind k=kea1 \
  --bind l=lotkoe1 \
  --bind m=morepo2 \
  --bind n=nezrob3 \
  --bind o=soioys1 \
  --bind p=malpar2 \
  --bind r=riflem1 \
  --bind s=silver3 \
  --bind t=tomtit1 \
  --bind u=nezpig2 \
  --bind v=brncre \
  --bind w=weka1  \
  --bind x=Noise \
  --bind z="Don't Know" \
  --bind 1=Kiwi+Duet \
  --bind 2=Kiwi+Female \
  --bind 3=Kiwi+Male \
  --bind 4=Kiwi \

Insertion in me.txt at line 295 [3.1]
[7.10591]

Replacement in .claude/skills/bulk-import-setup/SKILL.md at line 29 [8.27072]

B:BD[8.28439] → [8.28439:28485]

9. **Verify** and provide bulk import command

[8.28439]

[8.28485]

9. **Set cyclic recording pattern** on all clusters if data is from an AudioMoth
10. **Verify** and provide bulk import command

Replacement in .claude/skills/bulk-import-setup/SKILL.md at line 433 [8.27072]

B:BD[8.40988] → [8.40988:41021]

## Step 7: Update CSV and Verify

[8.40988]

[8.41021]

## Step 7: Set Cyclic Recording Pattern (AudioMoth Only)
If the data is from an **AudioMoth**, every cluster **must** have a `cyclic_recording_pattern_id` set.
### Detecting AudioMoth Data
AudioMoth filenames follow the pattern `YYYYMMDD_HHMMSS.wav` (e.g. `20250422_173008.wav`) or contain an AudioMoth prefix (e.g. `AUDIOMOTH_...`). The log.txt file also identifies the device. When in doubt, ask the user.
### Determine the Pattern from File Intervals
Compute record_s and sleep_s from the files:
```python
# record_s = file duration (from WAV header or duration field)
# sleep_s = gap between end of one file and start of next
#   gap = next_start - (this_start + duration)
# cycle = record_s + sleep_s (should be constant, e.g. 900s, 1800s, 2400s)
# Sample a few consecutive files to confirm the pattern is consistent
```
### Always Use an Existing Pattern
Query existing patterns first — only create a new one if none match:
```python
cmd = ["./skraak", "sql", "--db", db_path,
       "SELECT id, record_s, sleep_s FROM cyclic_recording_pattern WHERE active = true"]
```
Match by `record_s` AND `sleep_s`. If a match exists, use that ID. If no match, create a new pattern:
```python
cmd = ["./skraak", "create", "cyclic-recording-pattern",
       "--db", db_path,
       "--record", str(record_s),
       "--sleep", str(sleep_s)]
```
### Set Pattern on Every Cluster
After clusters are created (via bulk import), set the pattern on each:
```python
cmd = ["./skraak", "update", "cluster",
       "--db", db_path,
       "--id", cluster_id,
       "--cyclic-recording-pattern", pattern_id]
```

Insertion in .claude/skills/bulk-import-setup/SKILL.md at line 483 [8.27072]

[8.41022]

Or use the MCP tool `create_or_update_cluster` with `cyclic_recording_pattern_id`.
Include this step in the confirmation summary shown to the user before execution:
```
PLAN READY - AWAITING CONFIRMATION
===================================
...
Cyclic recording pattern: 895s record / 5s sleep (ID: c-l6D6TPlRVO) — will be set on all clusters
```
## Step 8: Update CSV and Verify

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[8.53308]

- **AudioMoth data requires cyclic recording pattern** on every cluster — always check existing patterns first, only create a new one if none match

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[8.53627]
```
✅ Cyclic recording pattern set on all clusters (AudioMoth data only)
```

me, and fix skill to include cyclic recording pattern

Dependencies

In channels

Change contents

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