Fal Workflow

Fal Workflow

Overview

Generate workflow JSON files for chaining AI models

When to Use This Skill

Use this skill when you need to work with generate workflow json files for chaining ai models.

Instructions

This skill provides guidance and patterns for generate workflow json files for chaining ai 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 Workflow"

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-workflow 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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