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Agent Skill · 研究检索

speak-tts(说 tts)

speak-tts 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

speak-tts 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 8,133。

总安装 17,112周安装 713GitHub Stars 6下载 5,704核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:speak-tts(说 tts)
来源仓库:https://github.com/emzod/speak
仓库路径:skills/speak-tts
安装命令:
npx skills add https://github.com/emzod/speak --skill speak-tts
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/emzod/speak --skill speak-tts

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

通过 Apple Silicon 上的语音克隆实现实时文本转语音,完全在设备上进行。

支持多种输入源(文本文件、markdown、stdin、网络文章、PDF)和输出模式(流式传输、文件保存、播放或两者兼而有之) 从 24000 Hz 单声道 10-30 秒 WAV 样本克隆语音;包括情感标签,例如[笑] ,[叹气] ,和[喘气] 用于听觉效果 具有长文档自动分块功能的批处理、串联实用程序以及中断生成的恢复功能 需要 Apple Silicon Mac、macOS 12.0+ 和命令行工具(sox、ffmpeg、poppler);完全通过 MLX 在本地运行,无需 API 密钥

来源仓库内路径:skills/speak-tts

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/emzod/speak --skill speak-tts;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

speak-tts 怎么安装?

在终端执行 npx skills add https://github.com/emzod/speak --skill speak-tts。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

speak-tts 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

speak-tts 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/emzod/speak --skill speak-tts 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

speak-tts 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

speak-tts 用的人多吗?

公开数据是累计安装 17,112 次,近一周安装 713 次,下载 5,704 次,GitHub 6 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

speak-tts 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
speak-tts

说 tts · 本页

17,1126执行命令未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

speak - Talk to your Claude!

Give your agent the ability to speak to you real-time. Local text-to-speech, voice cloning, and audio generation on Apple Silicon. Give your agent the ability to speak to you real-time. Local TTS with voice cloning on Apple Silicon.

Prerequisites

RequirementCheckInstall
Apple Silicon Macuname -m → arm64Intel not supported
macOS 12.0+sw_vers-
soxwhich soxbrew install sox
ffmpegwhich ffmpegbrew install ffmpeg
poppler (PDF)which pdftotextbrew install poppler

Input Sources

SourceExample
Text filespeak article.txt
Markdownspeak doc.md
Direct stringspeak "Hello"
Clipboard`pbpaste \speak`
Stdin`cat file.txt \speak`

Web Articles

lynx -dump -nolist "https://example.com/article" | speak --output article.wav

Converting Formats

FormatConvert Command
PDFpdftotext doc.pdf doc.txt
DOCXtextutil -convert txt doc.docx
HTMLpandoc -f html -t plain doc.html > doc.txt

Output Modes

GoalCommand
Save for laterspeak text.txt --output file.wav
Listen now (streaming)speak text.txt --stream
Listen now (complete)speak text.txt --play
Bothspeak text.txt --stream --output file.wav

Default Behavior

speak article.txt          # → ~/Audio/speak/article.wav (no playback)
speak "Hello"              # → ~/Audio/speak/speak_<timestamp>.wav

Directory Auto-Creation

DirectoryAuto-Created?
~/Audio/speak/✓ Yes
~/.chatter/voices/✗ No
Custom directories✗ No

Always create custom directories first:

mkdir -p ~/.chatter/voices/
mkdir -p ~/Audio/custom/

Voice Cloning

Voice cloning generates speech that matches your vocal characteristics (pitch, tone, cadence) from a short recording.

Quality Expectations

  • Output captures general voice characteristics but is not a perfect replica
  • Quality depends heavily on sample quality
  • 15-25 seconds is optimal (10s minimum, 30s maximum)

Recording Your Voice

Using QuickTime:

  1. Open QuickTime Player → File → New Audio Recording
  2. Record 20 seconds of clear speech
  3. File → Export As → Audio Only (.m4a)
  4. Convert to WAV (see below)

Using sox (command line):

# -d = use default microphone
# Recording starts immediately and stops after 25 seconds
sox -d -r 24000 -c 1 ~/.chatter/voices/my_voice.wav trim 0 25

Converting to Required Format

Voice samples MUST be: WAV, 24000 Hz, mono, 10-30 seconds.

# From MP3
ffmpeg -i voice.mp3 -ar 24000 -ac 1 voice.wav

# From M4A (QuickTime)
ffmpeg -i voice.m4a -ar 24000 -ac 1 voice.wav

# Trim to 25 seconds
ffmpeg -i long.wav -t 25 -ar 24000 -ac 1 trimmed.wav

# Check sample properties
ffprobe -i voice.wav 2>&1 | grep -E "Duration|Stream"
# Should show: Duration ~15-25s, 24000 Hz, mono

Using Your Voice

# Create directory
mkdir -p ~/.chatter/voices/

# Move sample
mv voice.wav ~/.chatter/voices/my_voice.wav

# Test
speak "Testing my voice" --voice ~/.chatter/voices/my_voice.wav --stream

# Use for content
speak notes.txt --voice ~/.chatter/voices/my_voice.wav --output presentation.wav

Path requirements:

  • ✓ Works: ~/.chatter/voices/my_voice.wav (tilde expanded by shell)
  • ✓ Works: /Users/name/.chatter/voices/my_voice.wav
  • ✗ Fails: my_voice.wav (relative path)
  • ✗ Fails: ./voices/my_voice.wav (relative path)

Voice Sample Tips

Good SampleBad Sample
Quiet roomBackground noise
Natural paceRushed or monotone
Clear dictionMumbling
Varied contentRepetitive phrases

Default Voice

When --voice is omitted, a built-in default voice is used:

speak "Hello world" --stream  # Uses default voice

Emotion Tags

Tags produce audible effects (actual sounds), not spoken words:

speak "[sigh] Monday again." --stream
# Output: (sigh sound) "Monday again."
TagEffect
[laugh]Laughter
[chuckle]Light chuckle
[sigh]Sighing
[gasp]Gasping
[groan]Groaning
[clear throat]Throat clearing
[cough]Coughing
[crying]Crying
[singing]Sung speech

NOT supported: [pause], [whisper] (ignored)

For pauses: Use punctuation: "Wait... let me think."

Batch Processing

mkdir -p ~/Audio/book/
speak ch01.txt ch02.txt ch03.txt --output-dir ~/Audio/book/
# Creates: ch01.wav, ch02.wav, ch03.wav

# With auto-chunking (for long files)
speak chapters/*.txt --output-dir ~/Audio/book/ --auto-chunk

# Skip completed files
speak chapters/*.txt --output-dir ~/Audio/book/ --skip-existing

Auto-Chunk Behavior

When using --auto-chunk with batch processing:

  1. Each input file is chunked independently
  2. Chunks are generated and automatically concatenated per file
  3. Final output: one .wav per input file (e.g., ch01.wav)
  4. Intermediate chunks deleted (unless --keep-chunks)

You don't need to manually concatenate chunks — only concatenate final chapter files.

Concatenating Audio

# Explicit order (recommended)
speak concat ch01.wav ch02.wav ch03.wav --output book.wav

# Glob pattern (REQUIRES zero-padded filenames)
speak concat audiobook/*.wav --output book.wav

Zero-Padding Rules

Critical for correct concatenation order:

FilesCorrectWrong
1-901, 02,..., 091, 2,..., 9
10-9901, 02,..., 991, 10, 2,...
100+001, 002,..., 9991, 100, 2,...

Why: Shell glob expansion sorts alphabetically. 1, 10, 2 vs 01, 02, 10.

PDF to Audiobook (Complete Workflow)

Step 1: Find Chapter Boundaries

# Preview table of contents
pdftotext -f 1 -l 5 textbook.pdf toc.txt
cat toc.txt  # Note chapter page numbers

# Or search for "Chapter" markers
pdftotext textbook.pdf - | grep -n "Chapter"

Step 2: Extract Chapters (Zero-Padded!)

# For 100-page book with ~10 chapters
pdftotext -f 1 -l 12 -layout textbook.pdf ch01.txt
pdftotext -f 13 -l 25 -layout textbook.pdf ch02.txt
pdftotext -f 26 -l 38 -layout textbook.pdf ch03.txt
# ... continue for all chapters

Step 3: Estimate Time

speak --estimate ch*.txt
# Shows: total audio duration, generation time, storage needed

# Quick estimates:
# 1 page ≈ 2 min audio ≈ 1 min generation
# 100 pages ≈ 200 min audio ≈ 100 min generation ≈ 500 MB

Step 4: Generate Audio

mkdir -p audiobook/
speak ch01.txt ch02.txt ch03.txt --output-dir audiobook/ --auto-chunk
# Creates: audiobook/ch01.wav, audiobook/ch02.wav, audiobook/ch03.wav

Step 5: Concatenate

speak concat audiobook/ch01.wav audiobook/ch02.wav audiobook/ch03.wav --output complete_audiobook.wav
# Or with glob (only if zero-padded):
speak concat audiobook/ch*.wav --output complete_audiobook.wav

PDF Troubleshooting

IssueSolution
Empty/garbled textScanned PDF — use OCR: brew install tesseract
Wrong encodingTry: pdftotext -enc UTF-8 doc.pdf
Check word count`pdftotext doc.pdf - \wc -w` (should be >100)

Multi-Voice Content

mkdir -p podcast/scripts podcast/wav

echo "Welcome to the show." > podcast/scripts/01_host.txt
echo "Thanks for having me." > podcast/scripts/02_guest.txt

speak podcast/scripts/01_host.txt --voice ~/.chatter/voices/host.wav --output podcast/wav/01.wav
speak podcast/scripts/02_guest.txt --voice ~/.chatter/voices/guest.wav --output podcast/wav/02.wav

speak concat podcast/wav/01.wav podcast/wav/02.wav --output podcast.wav

Options Reference

OptionDescriptionDefault
--streamStream as it generatesfalse
--playPlay after completefalse
--output <path>Output file~/Audio/speak/
--output-dir <dir>Batch output directory-
--voice <path>Voice sample (full path)default
--timeout <sec>Timeout per file300
--auto-chunkSplit long documentsfalse
--chunk-size <n>Chars per chunk6000
--resume <file>Resume from manifest-
--keep-chunksKeep intermediate filesfalse
--skip-existingSkip if output existsfalse
--estimateShow duration estimatefalse
--dry-runPreview onlyfalse
--quietSuppress outputfalse

Commands

CommandDescription
speak setupSet up environment
speak healthCheck system status
speak modelsList TTS models
speak concatConcatenate audio
speak daemon killStop TTS server
speak configShow configuration

Performance

MetricValue
Cold start~4-8s
Warm start~3-8s
Speed0.3-0.5x RTF (faster than real-time)
Storage~2.5 MB/min, ~150 MB/hour

Resume Capability

For interrupted long generations:

# Single file with auto-chunk — use --resume
speak long.txt --auto-chunk --output book.wav
# If interrupted, manifest saved at ~/Audio/speak/manifest.json
speak --resume ~/Audio/speak/manifest.json

# Batch processing — use --skip-existing
speak ch*.txt --output-dir audiobook/ --auto-chunk
# If interrupted, re-run same command:
speak ch*.txt --output-dir audiobook/ --auto-chunk --skip-existing

Common Errors

ErrorCauseSolution
"Voice file not found"Relative pathUse full path: ~/.chatter/voices/x.wav
"Invalid WAV format"Wrong specsConvert: ffmpeg -i in.wav -ar 24000 -ac 1 out.wav
"Voice sample too short"<10 secondsRecord 15-25 seconds
"Output directory doesn't exist"Not createdmkdir -p dirname/
"sox not found"Not installedbrew install sox
Scrambled concat orderNon-zero-paddedUse 01, 02, not 1, 2
Timeout>5 min generationUse --auto-chunk or --timeout 600
"Server not running"Stale daemonspeak daemon kill && speak health

Setup

speak "test"     # Auto-setup on first run (downloads model ~500MB)
speak setup      # Or manual setup
speak health     # Verify everything works

Server Management

Server auto-starts and shuts down after 1 hour idle.

speak health        # Check status
speak daemon kill   # Stop manually

平台分布

Codex

36.29%
按下载量换算2,070

Claude

27.98%
按下载量换算1,596

Cursor

17.94%
按下载量换算1,023

Gemini CLI

8.25%
按下载量换算471

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/emzod/speak --skill speak-tts 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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