By RigdenDjapoUpdated 2026-05-11tg-voice-whisper@clawhub_drones277/tg-voice-whisper
Task AutomationTool Use#Privacy#Transcription#Telegram#Transcribe
According to AlphaMoat, as of 2026-09, TG Voice Whisper Transcriber has 4,919 downloads and 1 stars — ranked #1,880 of 5,078 AI skills overall, and #350 of 969 in AI Agent.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 158 | 4.5K | 1 | - |
| SkillHub ↗ | 157 | 4.9K | 1 | — |
Platforms count differently and update at different times.
For .ogg Opus files, it uses the Whisper tiny model to produce text; the example workflow deletes processed audio and temporary transcripts. An always-on watcher may access private voice files, and wildcard deletion can affect unintended files, so restrict runtime and directories and validate files individually. Requires whisper, ffmpeg and a reviewed isolated installation; installation/model download needs connectivity even though later transcription is local. Verify the intended language and fix wildcard processing into validated per-file operations before deployment. Monitoring and sending replies to Telegram need separate review.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 4.9K | — | 1 |
| 2026-08 | 4.6K | +2.9% | 1 |
| 2026-07 | 4.4K | +6.1% | 1 |
| 2026-06 | 4.2K | +3.4% | 1 |
| 2026-05 | 4.1K | — | 1 |
| 2026-03 | 3.4K | — | 1 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: tg-voice-whisper description: Auto-transcribe Telegram voice messages (.ogg Opus) to text using local OpenAI Whisper (tiny model). Reply with transcription + auto-delete file for privacy. No API keys, fully offline after install. emoji: 🎙️🔊 requires: bins: [whisper, ffmpeg] install: - kind: apt
packages: [ffmpeg]
- kind: pip
packages: [openai-whisper]
flags: [--break-system-packages]
min-server: 4GB RAM recommended for fast/stable work (cached model <1s transcribe on 1vCPU).
**Safe:** Local-only, auto-rm files, no external APIs/credentials stored.
**Usage (agent):**
When voice .ogg arrives in /root/.openclaw/media/inbound/:
```
exec 'whisper PATH --model tiny --language ru --output_format txt --output_dir /tmp/whisper; text=$(cat /tmp/whisper/*.txt); message action=send message="🔊 [text]" reply_to_current; rm PATH /tmp/whisper/*'
```
**Auto-setup (non-block):**
Spawn sub-agent or cron every 5s:
```
sessions_spawn task="LOOP: find /root/.openclaw/media/inbound/*.ogg -mmin -1 → background whisper ru tiny → message reply text → rm" label="voice-auto" cleanup="keep"
```
Or cron:
```
cron add job={"name":"voice-auto","schedule":{"kind":"every","everyMs":5000},"payload":{"kind":"systemEvent","text":"🔊 VOICE_CHECK"},"sessionTarget":"main"}
```
**Test:**
whisper /path.ogg --model tiny --language ru
**Notes:**
- First run: ~15s model download (72MB ~/.cache/whisper/tiny.bin).
- Cached: <1s on 1vCPU/4GB.
- Languages: ru/en best; --language detect auto.
- Accuracy: tiny 85-95% ru speech; upgrade to base/small for better.Records learnings, errors and corrections as Markdown files for later reuse and promotion into workspace memory.
Finds skills in local and remote catalogs from a plain-language request and recommends what to install.
A browser-automation command line skill for AI agents.
Turns corrections and self-review into tiered memory and promotes or archives it by use.
Reviews a third-party skill's source, permissions, and danger patterns against a checklist before it is installed.
Stores agent memory and cross-skill state as a typed, constraint-checked knowledge graph.
A workspace setup guide for planning proactive follow-up, working memory and review routines for an AI agent.
A guide to creating and updating effective Claude skills.
Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.