据 AlphaMoat 统计,截至 2026-09,Gemini STT 累计下载 4,449 次、获 2 个星标,在全部 5,078 个 AI 技能中排名第 2,183 位,在「设计创意」分类(512 个)中排名第 213 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 146 | 4,339 | 2 | - |
| SkillHub ↗ | 275 | 4,449 | 2 | — |
各平台的计数口径不同,统计时间不一致。
调用 Gemini API 或 Vertex AI 转录音频文件。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 4,449 | — | 2 |
| 2026-08 | 4,240 | +2.4% | 2 |
| 2026-07 | 4,140 | +6.4% | 2 |
| 2026-06 | 3,890 | +3.7% | 2 |
| 2026-05 | 3,753 | — | 2 |
| 2026-03 | 3,090 | — | 2 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
---
name: gemini-stt
description: Transcribe audio files using Google's Gemini API or Vertex AI
metadata: {"clawdbot":{"emoji":"🎤","os":["linux","darwin"]}}
---
# Gemini Speech-to-Text Skill
Transcribe audio files using Google's Gemini API or Vertex AI. Default model is `gemini-2.0-flash-lite` for fastest transcription.
## Authentication (choose one) ### Option 1: Vertex AI with Application Default Credentials (Recommended) ```bash gcloud auth application-default login gcloud config set project YOUR_PROJECT_ID ``` The script will automatically detect and use ADC when available. ### Option 2: Direct Gemini API Key Set `GEMINI_API_KEY` in environment (e.g., `~/.env` or `~/.clawdbot/.env`) ## Requirements - Python 3.10+ (no external dependencies) - Either GEMINI_API_KEY or gcloud CLI with ADC configured ## Supported Formats - `.ogg` / `.opus` (Telegram voice messages) - `.mp3` - `.wav` - `.m4a` ## Usage ```bash # Auto-detect auth (tries ADC first, then GEMINI_API_KEY) python ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg # Force Vertex AI python ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --vertex # With a specific model python ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --model gemini-2.5-pro # Vertex AI with specific project and region python ~/.claude/skills/gemini-stt/transcribe.py /path/to/audio.ogg --vertex --project my-project --region us-central1 # With Clawdbot media python ~/.claude/skills/gemini-stt/transcribe.py ~/.clawdbot/media/inbound/voice-message.ogg ``` ## Options | Option | Description | |--------|-------------| | `<audio_file>` | Path to the audio file (required) | | `--model`, `-m` | Gemini model to use (default: `gemini-2.0-flash-lite`) | | `--vertex`, `-v` | Force use of Vertex AI with ADC | | `--project`, `-p` | GCP project ID (for Vertex, defaults to gcloud config) | | `--region`, `-r` | GCP region (for Vertex, default: `us-central1`) | ## Supported Models Any Gemini model that supports audio input can be used. Recommended models: | Model | Notes | |-------|-------| | `gemini-2.0-flash-lite` | **Default.** Fastest transcription speed. | | `gemini-2.0-flash` | Fast and cost-effective. | | `gemini-2.5-flash-lite` | Lightweight 2.5 model. | | `gemini-2.5-flash` | Balanced speed and quality. | | `gemini-2.5-pro` | Higher quality, slower. | | `gemini-3-flash-preview` | Latest flash model. | | `gemini-3-pro-preview` | Latest pro model, best quality. | See [Gemini API Models](https://ai.google.dev/gemini-api/docs/models) for the latest list. ## How It Works 1. Reads the audio file and base64 encodes it 2. Auto-detects authentication: - If ADC is available (gcloud), uses Vertex AI endpoint - Otherwise, uses GEMINI_API_KEY with direct Gemini API 3. Sends to the selected Gemini model with transcription prompt 4. Returns the transcribed text ## Example Integration For Clawdbot voice message handling: ```bash # Transcribe incoming voice message TRANSCRIPT=$(python ~/.claude/skills/gemini-stt/transcribe.py "$AUDIO_PATH") echo "User said: $TRANSCRIPT" ``` ## Error Handling The script exits with code 1 and prints to stderr on: - No authentication available (neither ADC nor GEMINI_API_KEY) - File not found - API errors - Missing GCP project (when using Vertex) ## Notes - Uses Gemini 2.0 Flash Lite by default for fastest transcription - No external Python dependencies (uses stdlib only) - Automatically detects MIME type from file extension - Prefers Vertex AI with ADC when available (no API key management needed)
ContextWeave 架构图一键生成
用 Nano Banana Pro 生成或编辑图片的脚本技能。
用 whisper 命令行在本地把音频转写成文字或做翻译的技能。
通过 MCP 服务生成与编辑图表的技能。
面向界面设计的思路与落地建议技能,覆盖布局、交互流程、设计令牌与前端改动。
面向多家视频模型 API 的 AI 视频生成与编排技能。
用 ffmpeg 从视频里取出画面帧,或生成便于快速查看的缩略图。
用本地 Whisper 把音频文件转成文字,模型下载完成后可完全离线运行。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。