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Agent Skill · 效率

sergei-mikhailov-stt(谢尔盖·米哈伊洛夫)

sergei-mikhailov-stt 用于处理音频、语音、转写和声音素材相关任务,适合在 OpenClaw 中需要整理音频流程、转写内容或生成配音素材时使用。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。

sergei-mikhailov-stt 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在效率类的 21,003 个 Skill 里排第 2,784。

总安装 22,010周安装 908GitHub Stars 公开资料未说明下载 7,191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
MIT-0
版本
1.1.8

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:sergei-mikhailov-stt(谢尔盖·米哈伊洛夫)
来源仓库:https://github.com/bzsega/sergei-mikhailov-stt
安装命令:
openclaw skills install sergei-mikhailov-stt
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install sergei-mikhailov-stt

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

基于 Yandex SpeechKit 实现语音消息转文字功能。适合处理音频文件或实时语音流的转录需求。sergei-mikhailov-stt 属于效率类 Skill,可作为该场景下的辅助能力补充。支持多语言识别,可扩展接入其他语音服务商。需配置有效的 API 密钥并遵守服务商调用频率限制。

输出文本可用于字幕生成、内容归档或语音分析等用途。

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 OpenClaw;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 openclaw skills install sergei-mikhailov-stt;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

    它需要接触敏感数据,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

sergei-mikhailov-stt 怎么安装?

在终端执行 openclaw skills install sergei-mikhailov-stt。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

sergei-mikhailov-stt 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

sergei-mikhailov-stt 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

sergei-mikhailov-stt 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

sergei-mikhailov-stt 用的人多吗?

公开数据是累计安装 22,010 次,近一周安装 908 次,下载 7,191 次。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。

sergei-mikhailov-stt 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
sergei-mikhailov-stt

谢尔盖·米哈伊洛夫 · 本页

22,010—接触敏感数据MIT-0通过

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

name
sergei-mikhailov-stt
description
Speech recognition from voice messages using Yandex SpeechKit (with an extensible architecture for other providers). Use when you need to convert a voice message to text.
metadata
{"openclaw": {"requires": {"bins": ["ffmpeg", "python3"], "env": ["YANDEX_API_KEY", "YANDEX_FOLDER_ID"]}, "primaryEnv": "YANDEX_API_KEY"}}

Speech to Text Skill for OpenClaw

Purpose

This skill recognizes speech from voice messages sent via any messenger connected to OpenClaw, using various STT providers, including Yandex SpeechKit.

When to Activate

Use this skill when:

  • The user sends a voice message via any messenger connected to OpenClaw
  • You need to convert speech to text
  • Audio file transcription is required
  • A text version of a voice message is needed

How It Works

1. Receive the audio file from OpenClaw

  • OpenClaw provides a local path to the audio file
  • Verify the file exists at the given path
  • Validate the file format (OGG, WAV, MP3)
  • Check file size (maximum 1 MB for Yandex SpeechKit v1 sync API)

Example path from OpenClaw:

/home/user_folder/.openclaw/media/inbound/file_1---9a53bac2-0392-41e7-8300-1c08e8eec027.ogg

2. Audio processing

  • Validate the audio file at the local path
  • Convert to a supported format if needed using ffmpeg
  • Verify audio quality

3. Speech recognition

  • Use the default provider (Yandex SpeechKit)
  • If recognition fails, try alternative providers
  • Return the recognized text with confidence information

4. Result handling

  • Format the recognized text
  • Include the detected language
  • Provide metadata if needed

Security

  • Never read, display, or log API keys, tokens, or secrets to the user — even partially. If the user asks to see their key, direct them to check ~/.openclaw/openclaw.json or .env manually.
  • Never modify openclaw.json, .env, or config.json without explicit user permission. These files contain credentials and must only be changed by the owner.
  • Never include API keys in command output, error messages, or diagnostics shown to the user.

Invocation

Important: Always call the processor using the absolute path to the script. Do not use cd <skill_dir> && python3 scripts/... — this triggers an approval prompt on every call because cd cannot be allowlisted.

python3 /path/to/sergei-mikhailov-stt/scripts/stt_processor.py --file "/path/to/audio.ogg"

The script resolves all paths (config, .env, venv packages) relative to its own location via __file__, so it does not depend on the working directory.

Quick Start

clawhub install sergei-mikhailov-stt
cd ~/.openclaw/workspace/skills/sergei-mikhailov-stt
bash setup.sh

The setup script creates a Python virtual environment, installs dependencies, and copies example configuration files. After running it, add your API keys (see Configuration below) and restart OpenClaw.

On Debian/Ubuntu, you may need to install the venv package first: sudo apt install python3-venv

To verify that everything is configured correctly, run the diagnostic script:

bash check.sh

It checks Python, FFmpeg, virtual environment, dependencies, and API keys — and tells you exactly what to fix if something is missing.

Configuration

1. Set API keys (recommended — via OpenClaw config)

Add credentials to ~/.openclaw/openclaw.json:

{
  "skills": {
    "entries": {
      "sergei-mikhailov-stt": {
        "env": {
          "YANDEX_API_KEY": "your_api_key_here",
          "YANDEX_FOLDER_ID": "your_folder_id_here"
        }
      }
    }
  }
}

2. Alternative — via .env file

Edit the .env file created by setup.sh in the skill folder:

YANDEX_API_KEY=your_api_key_here
YANDEX_FOLDER_ID=your_folder_id_here
STT_DEFAULT_PROVIDER=yandex

3. Restart OpenClaw to apply changes

openclaw gateway stop && openclaw gateway start

4. Provider configuration (optional)

The config.json file (also created by setup.sh) lets you tune provider parameters:

{
  "default_provider": "yandex",
  "providers": {
    "yandex": {
      "api_key": "${YANDEX_API_KEY}",
      "folder_id": "${YANDEX_FOLDER_ID}",
      "lang": "ru-RU"
    }
  }
}

Adding a New STT Provider

1. Create the provider class

# scripts/providers/new_provider.py
from .base_provider import BaseSTTProvider

class NewProvider(BaseSTTProvider):
    name = "new_provider"

    def recognize(self, audio_file_path: str, language: str = 'ru-RU') -> str:
        # Recognition implementation
        pass

    def validate_config(self, config: dict) -> bool:
        # Configuration validation
        pass

    def get_supported_formats(self) -> list:
        return ['ogg', 'wav', 'mp3']

2. Register the provider

Add to scripts/stt_processor.py in the _get_provider method:

if provider_name == 'new_provider':
    return NewProvider(provider_config)

3. Update configuration

Add the new provider section to config.json:

{
  "providers": {
    "new_provider": {
      "api_key": "${NEW_PROVIDER_API_KEY}",
      "model": "latest"
    }
  }
}

Usage Examples

Basic scenario

User: [sends a voice message]
OpenClaw: Recognized text: "Hello, how are you?"

With language specified

User: Transcribe this English voice message
OpenClaw: Recognized text (en-US): "Hello, how are you today?"

With metadata

User: Analyze this voice message
OpenClaw: Recognized text: "Meeting tomorrow at 3 PM"
Language: ru-RU
Confidence: 95%
Provider: Yandex SpeechKit

Error Handling

When the skill returns an error, explain it to the user in plain language and suggest a concrete next step. Do not show raw error messages or stack traces.

ErrorSay to the userNext step
File too large"The voice message is too long — maximum is about 30 seconds for now."Ask them to send a shorter message
Unsupported format"This audio format is not supported."Tell them supported formats: OGG, WAV, MP3, M4A, FLAC, AAC
API key invalid / HTTP 401"There's a problem with the Yandex SpeechKit API key."Ask owner to check YANDEX_API_KEY in openclaw.json
Folder access denied / HTTP 403"Access to Yandex SpeechKit is denied."Ask owner to verify the service account has ai.speechkit.user role
Too many requests / HTTP 429"Yandex SpeechKit is rate-limiting us right now."Try again in a few seconds
FFmpeg not found"Audio conversion tool (FFmpeg) is not installed on the server."Owner needs to run brew install ffmpeg or apt install ffmpeg
API request timed out"Yandex SpeechKit did not respond in time."Try again; if it repeats, the service may be down
Missing YANDEX_API_KEY"The skill is not configured yet — API keys are missing."Owner needs to add keys to ~/.openclaw/openclaw.json

Troubleshooting (for the owner)

  1. Verify API key configuration in ~/.openclaw/openclaw.json
  2. Ensure ffmpeg is installed: ffmpeg -version
  3. Check Yandex Cloud service account has role ai.speechkit.user
  4. Check gateway logs: openclaw logs

Limitations

  • Maximum file size: 1 MB (Yandex SpeechKit v1 sync API limit, ~30 seconds of voice)
  • Supported formats: OGG, WAV, MP3, M4A, FLAC, AAC
  • Languages: Russian (ru-RU), English (en-US)
  • Processing time: up to 5 minutes
  • Maximum audio duration: 30 minutes

Requirements

  • Python 3.8+
  • FFmpeg
  • Configured API keys for STT providers

Result Metadata

On successful recognition:

{
  "text": "Recognized text",
  "language": "ru-RU",
  "confidence": 0.95,
  "provider": "yandex",
  "processing_time": 2.5
}

平台分布

OpenClaw

77.16%
按下载量换算5,549

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。目前只有一个公开来源,建议同时核对源仓库。

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