據 AlphaMoat 統計,截至 2026-09,Gemini STT 累計下載 4,449 次、獲 2 個星標,在全部 5,078 個 AI 技能中排名第 2,183 位,在「設計創意」分類(512 個)中排名第 213 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 146 | 4339 | 2 | - |
| SkillHub ↗ | 275 | 4449 | 2 | — |
各平台的計數口徑不同,統計時間不一致。
呼叫 Gemini API 或 Vertex AI 轉錄音訊檔案。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 4449 | — | 2 |
| 2026-08 | 4240 | +2.4% | 2 |
| 2026-07 | 4140 | +6.4% | 2 |
| 2026-06 | 3890 | +3.7% | 2 |
| 2026-05 | 3753 | — | 2 |
| 2026-03 | 3090 | — | 2 |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 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 架構圖一鍵生成
用 Nano Banana Pro 生成或編輯圖片的指令碼技能。
用 whisper 命令列工具在本機將音訊轉成文字或進行翻譯。
透過 MCP 服務生成與編輯圖表的技能。
面向介面設計的思路與落地建議技能,覆蓋佈局、互動流程、設計令牌與前端改動。
面向多家影片模型 API 的 AI 影片生成與編排技能。
用 ffmpeg 從影片裡取出畫面幀,或生成便於快速檢視的縮圖。
用本地 Whisper 把音訊檔案轉成文字,模型下載完成後可完全離線執行。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。