tools/imsg/SKILL.md
iMessage/SMS CLI for listing chats, history, and sending messages via Messages.app.
npx skillsauth add letta-ai/skills imsgInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use imsg to read and send iMessage/SMS via macOS Messages.app.
imsg chats --limit 10 --json
# By chat ID
imsg history --chat-id 1 --limit 20 --json
# With attachments info
imsg history --chat-id 1 --limit 20 --attachments --json
# Filter by date
imsg history --chat-id 1 --start 2026-01-01T00:00:00Z --json
imsg watch --chat-id 1 --attachments
imsg watch --chat-id 1 --debounce 250ms
# Send to phone number
imsg send --to "+14155551212" --text "Hello!"
# Send to existing chat by ID (useful for replies)
imsg send --chat-id 86 --text "Hello!"
# With attachment
imsg send --to "+14155551212" --text "Check this out" --file /path/to/image.jpg
# Specify service
imsg send --to "+14155551212" --text "Hi" --service imessage
imsg send --to "+14155551212" --text "Hi" --service sms
--service imessage — Force iMessage (requires recipient has iMessage)--service sms — Force SMS (green bubble)--service auto — Let Messages.app decide (default)User: "Text mom that I'll be late"
# 1. Find mom's chat
imsg chats --limit 20 --json | jq '.[] | select(.displayName | contains("Mom"))'
# 2. Confirm with user
# "Found Mom at +1555123456. Send 'I'll be late' via iMessage?"
# 3. Send after confirmation
imsg send --to "+1555123456" --text "I'll be late"
testing
Navigates archived ChatGPT or Claude-style conversation exports and a MemFS reference archive on demand. Use when recalling what a past assistant knew, searching old conversations, rendering specific chats, seeding reference memory from export sidecars, or mining historical context without doing a full import.
testing
Migrates deprecated Letta Filesystem folders/files to MemFS using markdown document corpora, chunking, local lexical search, and QMD semantic search via the memfs-search skill. Use when replacing folders.files.upload, working with PDFs or document QA, or emulating open_file, grep_file, and search_file behavior.
data-ai
Configures Letta agent compaction settings and custom summarization prompts. Use when a user asks to change an agent's compaction prompt, improve summaries after context eviction, tune sliding-window or all-message compaction, or design companion/coding-agent continuity summaries.
development
Semantic search over agent memory files. Use when you need to find conceptually related memory blocks, discover forgotten reference files, check what you already know before creating new memory, or search beyond exact keyword matching. Currently supports QMD (local, no API keys).