What problem does it solve? Getting your messaging contacts into a searchable local network index normally requires manual exports and fragile scripts. This Skill automates the local extraction of iMessage and WhatsApp contact metadata — names, phone numbers, emails, channels, message counts, and timestamps — and stages them as candidate people for downstream enrichment, without uploading anything or calling paid APIs. ## Core Features & Use Cases - Multi-source discovery: Extracts and merges contacts from iMessage (local chat.db plus Contacts.app) and WhatsApp (via a pinned wacli fork with QR pairing), including unnamed contacts and contacts with no messages. - Incremental, resumable sync: Automatically chooses full or incremental WhatsApp history sync, caches successful chat identities, and resumes interrupted targeted chats on rerun. - Privacy-first staging: Writes only contact metadata to fixed local paths (contacts.csv, people.csv); identity matching, enrichment, and indexing are delegated to the separate Deep Context flow. - Use Case: You want your WhatsApp and iMessage contacts to become searchable alongside your LinkedIn network. Run the skill, scan the WhatsApp QR code, grant Full Disk Access, and the contacts are staged locally ready for enrichment. ## Quick Start Ask your agent to run $import-messages to import my iMessage and WhatsApp contacts into my local network search.
