Notre avis
Ce skill parse les exports de chats WhatsApp (.txt) pour en extraire des données structurées en JSON : participants, horodatages, messages.
Points forts
- Gère plusieurs formats de date (EU, US, ISO)
- Détecte les messages média et système
- Supporte les messages multi-lignes
- Fournit des métadonnées comme le nombre de messages et la plage de dates
Limites
- Dépend de l'encodage UTF-8 (avec fallback latin-1)
- Ne gère pas les pièces jointes ou médias réels
- Peut échouer sur des formats non standard ou des variantes régionales
Pour analyser des historiques de discussion WhatsApp et les convertir en données exploitables pour du traitement ou de l'analyse.
Si vous avez besoin de traiter des fichiers binaires ou des messages chiffrés de bout en bout, ou si le format d'export n'est pas textuel.
Analyse de sécurité
SûrThe skill only reads a specified file and parses its text content, with no destructive operations, network access, or execution of external commands. All code is standard Python, and there is no risk of exfiltration or system compromise.
Aucun point d'attention détecté
Exemples
Parse the WhatsApp chat in examples/sample-whatsapp-chat.txtExtract all participants and messages from this WhatsApp export file: /data/chat.txt. Return JSON.Parse this WhatsApp chat and tell me how many media messages were sent, and by whom.Directory: launch-agent-skills/skills/whatsapp-parser/skill.md
name: WhatsApp Chat Parser description: Parse WhatsApp chat exports into structured JSON data with participants, timestamps, and messages triggers:
- chat export
- parse chat
- message history
- chat file
WhatsApp Chat Parser
Purpose
Parse WhatsApp chat export files (.txt) and extract structured data including:
- Participant list
- Message count and date range
- Individual messages with timestamps and senders
- Media placeholders and system messages
WhatsApp Export Format
WhatsApp exports follow this pattern (may vary by locale):
[DD/MM/YYYY, HH:MM:SS] Sender Name: Message content
Format Variations
| Region | Date Format | Example | |--------|-------------|---------| | US | MM/DD/YY | [01/28/26, 9:15:32 AM] | | EU/UK | DD/MM/YYYY | [28/01/2026, 09:15:32] | | ISO | YYYY-MM-DD | [2026-01-28, 09:15:32] |
Special Message Types
- Media:
<Media omitted>or<image omitted>,<video omitted> - System: Messages without sender (e.g., "Alice added Bob to the group")
- Multi-line: Continuation lines without timestamp prefix
- Links: URLs embedded in message text
- Replies: May include quoted text with formatting
Instructions
Step 1: Read the Chat File
with open(chat_file_path, 'r', encoding='utf-8') as f:
content = f.read()
Step 2: Parse Messages Using Regex
import re
from datetime import datetime
# Pattern for WhatsApp message format (handles multiple date formats)
patterns = [
# EU format: [DD/MM/YYYY, HH:MM:SS]
r'\[(\d{2}/\d{2}/\d{4}),\s*(\d{2}:\d{2}:\d{2})\]\s*([^:]+):\s*(.*)',
# US format: [MM/DD/YY, H:MM:SS AM/PM]
r'\[(\d{2}/\d{2}/\d{2}),\s*(\d{1,2}:\d{2}:\d{2}\s*[AP]M)\]\s*([^:]+):\s*(.*)',
]
messages = []
current_message = None
for line in content.split('\n'):
matched = False
for pattern in patterns:
match = re.match(pattern, line)
if match:
if current_message:
messages.append(current_message)
date_str, time_str, sender, text = match.groups()
current_message = {
'date': date_str,
'time': time_str,
'sender': sender.strip(),
'content': text.strip(),
'is_media': '<media omitted>' in text.lower() or '<omitted>' in text.lower()
}
matched = True
break
# Handle multi-line messages
if not matched and current_message and line.strip():
current_message['content'] += '\n' + line
if current_message:
messages.append(current_message)
Step 3: Extract Metadata
participants = list(set(msg['sender'] for msg in messages))
date_range = {
'start': messages[0]['date'] if messages else None,
'end': messages[-1]['date'] if messages else None
}
message_count = len(messages)
media_count = sum(1 for msg in messages if msg['is_media'])
Step 4: Return Structured Output
{
"metadata": {
"participants": ["Alice Developer", "Bob Engineer"],
"message_count": 42,
"media_count": 3,
"date_range": {
"start": "28/01/2026",
"end": "28/01/2026"
}
},
"messages": [
{
"timestamp": "28/01/2026 09:15:32",
"sender": "Alice Developer",
"content": "Hey Bob, did you push the code?",
"is_media": false
}
]
}
Edge Cases
| Scenario | How to Handle | |----------|---------------| | System messages | Sender = "System" or skip | | Empty lines | Skip or treat as message separator | | Emoji-only messages | Parse normally, emoji preserved | | Very long messages | No truncation, preserve full content | | Non-UTF8 encoding | Try latin-1 fallback |
Example Usage in Claude Code
User: "Parse the WhatsApp chat in examples/sample-whatsapp-chat.txt"
Claude should:
- Read the file using the path provided
- Apply the parsing logic above
- Return structured JSON with metadata and messages
- Highlight interesting stats (most active participant, busiest hour, etc.)
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