realtime-api/.agent/skills/speak/SKILL.md
Speak text aloud using the Magpie TTS container in the realtime-api Docker stack. Zero external dependencies — just curl + aplay.
npx skillsauth add orinachum/autonomous-intelligence speakInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Synthesize speech using the local Magpie TTS container (port 9000) and play through speakers.
/home/spark/git/autonomous-intelligence/realtime-api/scripts/speak.sh "Text to speak"
| Flag | Short | Default | Description |
|------|-------|---------|-------------|
| (positional) | | (required) | Text to speak |
| --voice | -v | Mia.Calm | Voice name |
| --speed | -s | 125 | Speed percentage |
| --url | -u | http://localhost:9000 | Magpie TTS URL |
Mia, Mia.Calm, Mia.Happy, Mia.Sad, Mia.Angry, Aria, Aria.Calm, Aria.Happy, Jason, Jason.Calm, Leo, Leo.Calm
# Default calm voice
/home/spark/git/autonomous-intelligence/realtime-api/scripts/speak.sh "Deploy complete. All seven checks passed."
# Happy announcement
/home/spark/git/autonomous-intelligence/realtime-api/scripts/speak.sh -v Mia.Happy "All tests passed!"
# Different speed
/home/spark/git/autonomous-intelligence/realtime-api/scripts/speak.sh -s 140 "Speaking faster now."
testing
Run TTS round-trip tests — pure-logic unit tests and optional integration tests against live TTS/STT services.
development
Build and deploy the realtime-api Docker container with full verification that deployed code matches local source.
tools
Enhanced coding assistance
development
Unified memory management for notes, knowledge graph, RAG search, and file analysis. Use when working with: (1) Core memory — protected identity, projects, relationships, and system facts that should never be forgotten, (2) Working notes — per-session ephemeral notes organized by section, (3) MongoDB RAG — vector-search-enabled notes with importance scoring, decay, deduplication, and archival, (4) Neo4j knowledge graph — entities, relationships, merge duplicates, reinforce mentions, Cypher queries, (5) File analysis — deep file reading that extracts knowledge into all memory layers, (6) Service initialization — health-check, start/stop MongoDB, Neo4j, TEI embeddings via docker-compose with partial setup support.