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/songsee

Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.

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From plugin
xiaohongshu-mcp-python
14660 skills
Install
$ npx -y skills add luyike221/xiaohongshu-mcp-python --skill songsee --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/songsee

Context preview

The summary Claude sees to decide when to auto-load this skill.

Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.

SKILL.md

songsee.SKILL.md
name: songsee
description: Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.
homepage: https://github.com/steipete/songsee
metadata:
  {
    "openclaw":
      {
        "emoji": "🌊",
        "requires": { "bins": ["songsee"] },
        "install":
          [
            {
              "id": "brew",
              "kind": "brew",
              "formula": "steipete/tap/songsee",
              "bins": ["songsee"],
              "label": "Install songsee (brew)",
            },
          ],
      },
  }

songsee

Generate spectrograms + feature panels from audio.

Quick start

  • Spectrogram: `songsee track.mp3`
  • Multi-panel: `songsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux`
  • Time slice: `songsee track.mp3 --start 12.5 --duration 8 -o slice.jpg`
  • Stdin: `cat track.mp3 | songsee - --format png -o out.png`

Common flags

  • `--viz` list (repeatable or comma-separated)
  • `--style` palette (classic, magma, inferno, viridis, gray)
  • `--width` / `--height` output size
  • `--window` / `--hop` FFT settings
  • `--min-freq` / `--max-freq` frequency range
  • `--start` / `--duration` time slice
  • `--format` jpg|png

Notes

  • WAV/MP3 decode native; other formats use ffmpeg if available.
  • Multiple `--viz` renders a grid.
Ships withxiaohongshu-mcp-python

xiaohongshu-mcp-python 是一个基于现代 Python 技术栈开发的小红书内容自动化发布工具,通过 Model Context Protocol(MCP)协议为 AI 客户端提供强大的小红书操作能力。项目核心功能包括小红书账户登录管理、图文内容发布、视频内容发布、内容搜索与获取、帖子详情查看以及评论互动等。支持多种图片格式(JPG、PNG、GIF)和视频格式(MP4、MOV、AVI),既可处理本地文件路径,也支持 HTTP/HTTPS 链接,为用户提供灵活的内容发布方案。 该工具特别适合内容创作者、营销人员和开发者使用,能够显著提升小红书内容发布的效率和自动化程度。通过标准化的 MCP 接口,用户可以轻松地将小红书操作能力集成到各种 AI 工作流中,实现智能化的内容管理

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