Transcribe WhatsApp voice messages using local Whisper CLI. Use when: owner or contact sends an audio/ogg voice message. Combines Whisper transcription + CRM update + task creation. Works offline for short clips, uses OpenAI API for long clips. Hebrew and English supported.
The English summary is being prepared. Showing the original description.
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
This is a use-case skill, not a standalone integration. It combines:
Select model based on audio length:
| Tier | Model | When | Est. Time |
|---|---|---|---|
| 1 — Fast | tiny (local) | ≤ 15 seconds | 5-15s |
| 2 — Balanced | small (local) | 15-60 seconds | 30-90s |
| 3 — Accurate | OpenAI Whisper API | > 60 seconds | 2-5s |
#!/bin/bash
FILE="$1"
# Get duration
DURATION=$(ffprobe -v quiet -show_entries format=duration -of csv=p=0 "$FILE" 2>/dev/null | cut -d. -f1)
DURATION=${DURATION:-0}
if [ "$DURATION" -le 15 ]; then
MODEL="tiny"; TIMEOUT=30
elif [ "$DURATION" -le 60 ]; then
MODEL="small"; TIMEOUT=120
else
USE_API=true
fi
if [ "${USE_API:-false}" = true ]; then
RESULT=$(curl -s https://api.openai.com/v1/audio/transcriptions \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-F file="@$FILE" \
-F model="whisper-1" \
-F language="he" \
| jq -r '.text')
else
OUTDIR="/tmp/whisper-$$"
mkdir -p "$OUTDIR"
whisper "$FILE" --model "$MODEL" --language he --output_format txt --output_dir "$OUTDIR" 2>/dev/null
RESULT=$(cat "$OUTDIR/"*.txt 2>/dev/null)
# If tiny returned too few words, retry with small
WORD_COUNT=$(echo "$RESULT" | wc -w)
if [ "$MODEL" = "tiny" ] && [ "$WORD_COUNT" -le 1 ]; then
whisper "$FILE" --model small --language he --output_format txt --output_dir "$OUTDIR" 2>/dev/null
RESULT=$(cat "$OUTDIR/"*.txt 2>/dev/null)
fi
fi
echo "$RESULT"
# Install Whisper CLI (local)
pip install openai-whisper
# ffprobe for duration detection
apt install ffmpeg # Linux
brew install ffmpeg # macOS
Models download automatically to ~/.cache/whisper/ on first run.
When owner sends a voice message:
Voice OGG → [Whisper] → Text → [Intent] → [CRM update] + [monday task] + [execute]
--language he — auto-detect often defaults to Englishsmall model handles natural Hebrew speech wellWhatsApp inbound media:
/path/to/openclaw/media/inbound/<uuid>.ogg
File path is in system metadata for each inbound media attachment.
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AI Personal Assistant network skill for multi-agent PA coordination. Use when: contacting another PA, coordinating with peer agents, scheduling meetings between owners, broadcasting messages to PA groups, or looking up contacts from the local PA directory. Reads contact data from data/pa-directory.json in the workspace.
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Route and execute inter-PA coordination tasks in the OpenClaw multi-agent PA network. Triggers when: contacting another PA, passing a message between owners, broadcasting to a PA group, handling group lead/silence rules, or adding a new PA to the directory. NOT for: contact lookups (use contact-list skill), calendar invites (use meetings skill), or billing issues (use billing-monitor skill).
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AI Personal Assistant network skill. Use when: contacting another PA, coordinating with peer agents, scheduling meetings between owners, broadcasting messages, looking up contacts from the local PA directory, or performing any cross-PA task. Reads contact data from data/pa-directory.json in the workspace. Does NOT contain hardcoded contact data — each PA maintains their own directory file.
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OpenClaw API gateway proxy for authenticated SaaS calls (100+ services in references/SERVICES.md). Use ONLY when making an HTTP request to a third-party service that requires the gateway's stored credentials. NOT for direct API calls with bearer tokens already in scope, NOT for monday.com (use monday-for-agents), NOT for WhatsApp (use heleni-whatsapp). Triggers: "call the X API", "fetch from <service>", "send to Slack via gateway", "use the gateway for".
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Automatically creates new skills from complex problem-solving sessions. Triggers at the end of multi-step tasks that required novel approaches, debugging sessions, or workflow creation. Use when: a task took 3+ tool calls, involved a non-obvious solution, or established a pattern likely to recur. Also triggers on: "create a skill from this", "save this as a skill", "this should be a skill".
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Monitor for API billing errors and alert the owner and admin immediately. Use when: an API billing error is detected, a peer PA reports a billing error, or during routine health checks. Handles detection, notification, and fallback model switching. Model-agnostic: works with any LLM provider (Anthropic, OpenAI, Google, etc.).
The English summary is being prepared. Showing the original description.