[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71PY3NXHNDJGCSR81B8F8ZP":3,"skill-same:01M71PY3NXHNDJGCSR81B8F8ZP":81},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":25,"publishedAt":45,"linkOnly":46,"markdownContent":47,"markdownBody":48,"frontMatter":49,"refName":61,"commitSha":62,"skillDirectory":63,"forksCount":13,"repositoryHtmlUrl":64,"repositoryHomepageUrl":6,"ownerHtmlUrl":65,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":66,"install":67,"resources":80},"01M71PY3NXHNDJGCSR81B8F8ZP","songsee",null,"Generate spectrograms and audio feature visualizations (mel, chroma, MFCC, tempogram, etc.) from audio files via CLI. Useful for audio analysis, music production debugging, and visual documentation.","gjbvsjjvgm-sketch\u002FWORM_V2_SOVEREIGN","gjbvsjjvgm-sketch","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F278511911?v=4","01M71F3JXKZQ70H2KCHHTXKZDA","01M71PENEVFN19DBZFNHJPCHQ7",0,"MIT","https:\u002F\u002Fgithub.com\u002Fgjbvsjjvgm-sketch\u002FWORM_V2_SOVEREIGN\u002Fblob\u002Fmain\u002Fcore\u002Fhermes_sovereign_data\u002Fskills\u002Fmedia\u002Fsongsee\u002FSKILL.md",[17,22],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000013","分析与可视化","SCENARIO","使用场景",{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",[5,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44],"visual","Production","https","useful","generate","via","github","cli","documentation","analysis","debugging","files","for","feature","Audio","chroma","visualization","community","visualizations","2026-11-10 13:02:02",false,"---\nname: songsee\ndescription: Generate spectrograms and audio feature visualizations (mel, chroma, MFCC, tempogram, etc.) from audio files via CLI. Useful for audio analysis, music production debugging, and visual documentation.\nversion: 1.0.0\nauthor: community\nlicense: MIT\nmetadata:\n  hermes:\n    tags: [Audio, Visualization, Spectrogram, Music, Analysis]\n    homepage: https:\u002F\u002Fgithub.com\u002Fsteipete\u002Fsongsee\nprerequisites:\n  commands: [songsee]\n---\n\n# songsee\n\nGenerate spectrograms and multi-panel audio feature visualizations from audio files.\n\n## Prerequisites\n\nRequires [Go](https:\u002F\u002Fgo.dev\u002Fdoc\u002Finstall):\n```bash\ngo install github.com\u002Fsteipete\u002Fsongsee\u002Fcmd\u002Fsongsee@latest\n```\n\nOptional: `ffmpeg` for formats beyond WAV\u002FMP3.\n\n## Quick Start\n\n```bash\n# Basic spectrogram\nsongsee track.mp3\n\n# Save to specific file\nsongsee track.mp3 -o spectrogram.png\n\n# Multi-panel visualization grid\nsongsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux\n\n# Time slice (start at 12.5s, 8s duration)\nsongsee track.mp3 --start 12.5 --duration 8 -o slice.jpg\n\n# From stdin\ncat track.mp3 | songsee - --format png -o out.png\n```\n\n## Visualization Types\n\nUse `--viz` with comma-separated values:\n\n| Type | Description |\n|------|-------------|\n| `spectrogram` | Standard frequency spectrogram |\n| `mel` | Mel-scaled spectrogram |\n| `chroma` | Pitch class distribution |\n| `hpss` | Harmonic\u002Fpercussive separation |\n| `selfsim` | Self-similarity matrix |\n| `loudness` | Loudness over time |\n| `tempogram` | Tempo estimation |\n| `mfcc` | Mel-frequency cepstral coefficients |\n| `flux` | Spectral flux (onset detection) |\n\nMultiple `--viz` types render as a grid in a single image.\n\n## Common Flags\n\n| Flag | Description |\n|------|-------------|\n| `--viz` | Visualization types (comma-separated) |\n| `--style` | Color palette: `classic`, `magma`, `inferno`, `viridis`, `gray` |\n| `--width` \u002F `--height` | Output image dimensions |\n| `--window` \u002F `--hop` | FFT window and hop size |\n| `--min-freq` \u002F `--max-freq` | Frequency range filter |\n| `--start` \u002F `--duration` | Time slice of the audio |\n| `--format` | Output format: `jpg` or `png` |\n| `-o` | Output file path |\n\n## Notes\n\n- WAV and MP3 are decoded natively; other formats require `ffmpeg`\n- Output images can be inspected with `vision_analyze` for automated audio analysis\n- Useful for comparing audio outputs, debugging synthesis, or documenting audio processing pipelines\n","# songsee\n\nGenerate spectrograms and multi-panel audio feature visualizations from audio files.\n\n## Prerequisites\n\nRequires [Go](https:\u002F\u002Fgo.dev\u002Fdoc\u002Finstall):\n```bash\ngo install github.com\u002Fsteipete\u002Fsongsee\u002Fcmd\u002Fsongsee@latest\n```\n\nOptional: `ffmpeg` for formats beyond WAV\u002FMP3.\n\n## Quick Start\n\n```bash\n# Basic spectrogram\nsongsee track.mp3\n\n# Save to specific file\nsongsee track.mp3 -o spectrogram.png\n\n# Multi-panel visualization grid\nsongsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux\n\n# Time slice (start at 12.5s, 8s duration)\nsongsee track.mp3 --start 12.5 --duration 8 -o slice.jpg\n\n# From stdin\ncat track.mp3 | songsee - --format png -o out.png\n```\n\n## Visualization Types\n\nUse `--viz` with comma-separated values:\n\n| Type | Description |\n|------|-------------|\n| `spectrogram` | Standard frequency spectrogram |\n| `mel` | Mel-scaled spectrogram |\n| `chroma` | Pitch class distribution |\n| `hpss` | Harmonic\u002Fpercussive separation |\n| `selfsim` | Self-similarity matrix |\n| `loudness` | Loudness over time |\n| `tempogram` | Tempo estimation |\n| `mfcc` | Mel-frequency cepstral coefficients |\n| `flux` | Spectral flux (onset detection) |\n\nMultiple `--viz` types render as a grid in a single image.\n\n## Common Flags\n\n| Flag | Description |\n|------|-------------|\n| `--viz` | Visualization types (comma-separated) |\n| `--style` | Color palette: `classic`, `magma`, `inferno`, `viridis`, `gray` |\n| `--width` \u002F `--height` | Output image dimensions |\n| `--window` \u002F `--hop` | FFT window and hop size |\n| `--min-freq` \u002F `--max-freq` | Frequency range filter |\n| `--start` \u002F `--duration` | Time slice of the audio |\n| `--format` | Output format: `jpg` or `png` |\n| `-o` | Output file path |\n\n## Notes\n\n- WAV and MP3 are decoded natively; other formats require `ffmpeg`\n- Output images can be inspected with `vision_analyze` for automated audio analysis\n- Useful for comparing audio outputs, debugging synthesis, or documenting audio processing 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