fal-audio

Fal Audio

Overview

Text-to-speech and speech-to-text using fal.ai audio models

When to Use This Skill

Use this skill when you need to work with text-to-speech and speech-to-text using fal.ai audio models.

Instructions

This skill provides guidance and patterns for text-to-speech and speech-to-text using fal.ai audio models.

For more information, see the source repository.

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AGI Framework Integration

Adapted for @techwavedev/​agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior agent configurations, team compositions, and orchestration patterns. Critical for multi-agent system consistency.

# Check for prior AI agent orchestration context before starting
python3 execution/​memory_manager.py auto --query "agent patterns and orchestration strategies for Fal Audio"

Storing Results

After completing work, store AI agent orchestration decisions for future sessions:

python3 execution/​memory_manager.py store \
  --content "Agent pattern: hierarchical orchestration with Control Tower dispatcher, 3 specialist sub-agents" \
  --type decision --project <project> \
  --tags fal-audio ai-agents

Multi-Agent Collaboration

This skill is inherently multi-agent. Use cross-agent context to coordinate task distribution and avoid duplicate work.

python3 execution/​cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Agent architecture designed — Control Tower + specialist agents with shared Qdrant memory" \
  --project <project>

Control Tower Integration

Register agents and tasks with the Control Tower (execution/​control_tower.py) for centralized orchestration across machines and LLM providers.

Blockchain Identity

Each agent has a cryptographic Ed25519 identity. All memory writes are signed — enabling trust verification in multi-agent systems.

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