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apple-voice-memosApple voice memos 搜索

Agent Skill

用于辅助音频、音乐、语音转写、语音合成或声音素材处理。它适合让 Agent 生成配乐说明、整理音频流程、调用语音工具或处理播客和视频配音素材。使用时需要确认输入音频来源、输出格式、时长和模型限制;涉及人声克隆、版权音乐或公开发布时,应先核对授权和合规边界。

总安装

380

周安装

16

GitHub Stars

10

下载量

133
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:apple-voice-memos(Apple voice memos 搜索)
来源仓库:https://github.com/jessedc/claude-apple-voice-memos-skill
仓库路径:skills/apple-voice-memos
安装命令:
npx skills add https://github.com/jessedc/claude-apple-voice-memos-skill --skill apple-voice-memos
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/jessedc/claude-apple-voice-memos-skill --skill apple-voice-memos

简介

用于从 iCloud 同步的 Apple Voice Memos 中提取元数据和内嵌转录文本。

  • 适合处理语音备忘录、生成字幕或分析录音内容,需 macOS 设备开启 iCloud 同步。
  • 调用 extract-apple-voice-memos-metadata 获取录音列表,再用 extract-apple-voice-memos-transcript 提取指定文件的转录文本。
  • 安装后需确认本地数据库路径和音频文件访问权限,输出为 CSV 或文本格式。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Apple Voice Memos

Extract and process transcripts from Apple Voice Memos synced via iCloud.

Prerequisites

Voice Memos must be synced with iCloud on macOS.

Tools

This skill includes two scripts in its scripts/ directory:

  • extract-apple-voice-memos-metadata — Queries the CloudRecordings.db SQLite database (read-only) and outputs CSV with columns: title, date, duration, path. Supports optional flags: --limit N (default 10), --offset N, --search TERM, --after YYYY-MM-DD, --before YYYY-MM-DD.
  • extract-apple-voice-memos-transcript — Extracts the embedded transcript from a .m4a file's tsrp atom. Outputs timestamped text with filler words removed, intelligent line breaks, and paragraph breaks at natural pauses.

Step 1: Select a voice memo

Run the metadata script to find the right recording. Choose flags based on what the user asked for:

  • No specific request → run with no flags (returns 10 most recent)
  • User mentions a topic or keyword → use --search TERM
  • User mentions a time period → use --after YYYY-MM-DD and/or --before YYYY-MM-DD
  • User wants to see more results → use --offset N to paginate, or --limit N to increase the batch size

Flags can be combined, e.g. --search work --after 2026-01-01 --limit 5.

python3 scripts/extract-apple-voice-memos-metadata [flags]

Present the results as a numbered list showing title, date, and duration. Ask the user which memo they'd like to work with.

Error handling:

  • "Database not found" → Voice Memos iCloud sync is not enabled on this Mac.

Step 2: Extract the transcript

Run the transcript script with the path value from the selected recording:

python3 scripts/extract-apple-voice-memos-transcript "<FILENAME>.m4a"

Present the timestamped transcript to the user.

Error handling:

  • "tsrp atom not found" → This recording does not have an embedded transcript. Apple generates transcripts on-device and not all recordings will have one.
  • File not found → The recording file may not have synced to this Mac yet.

Step 3: Process the transcript

Read PROMPT.md from this skill's directory. Append the transcript after the ## Transcript heading. Send the complete prompt and transcript to a subagent with fresh context for processing.

The subagent will produce a structured markdown document with narrative summary, detailed notes, asides, and action items. Present this output to the user.

After presenting the output, ask the user if they'd like to save it as a markdown file. Suggest a filename in the format YYYY-MM-DD-slugified-title.md derived from the memo's title and date (e.g., 2026-02-04-the-soul-of-a-new-machine.md). Save to the current working directory by default. The user may accept, provide a different name or path, request adjustments to the content first, or skip saving.

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02

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03

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平台分布

Codex

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按下载量换算48

Claude

27.4%
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Cursor

17.88%
按下载量换算24

Gemini CLI

8.87%
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