agentic-flow-builder

Agentic Flow Builder

This skill provides comprehensive guidance for building production-grade agentic flows that combine:

• ReAcTree hierarchical agent tree decomposition for long-horizon task planning
• Anthropic's workflow patterns for effective agent design
• Business Rules Engine (BRE) for deterministic decision-making at gates
• Dual memory system (episodic + working) for context management
• SQLite persistence with full audit trails

Core Philosophy

Start simple, add complexity only when justified. Many problems can be solved with a single optimized LLM call. Only use agentic flows when the task requires:

• Multi-step decomposition
• Dynamic routing based on conditions
• Iterative refinement
• Complex orchestration across multiple specialized agents

When to Use Agentic Flows

Create an agentic flow when you need:

1. Long-horizon task planning - Complex goals requiring hierarchical decomposition
2. Deterministic gating - Business rule-based decisions (not AI guesswork)
3. Workflow orchestration - Coordinating multiple specialized agents
4. Audit requirements - Complete traceability of decisions and outcomes
5. Memory across executions - Learning from past successful/failed attempts

Architecture Components

0. Dynamic Agent Assignment

The system automatically selects the best agent for each task based on:

• Task description - Semantic matching with agent capabilities
• Required tags - Specific skills needed (e.g., "code", "security", "data")
• Agent type preference - General Claude models, Task agents, or External services
• Performance history - Learns from past successes/failures

Agents are discovered dynamically:

• Claude models (Sonnet, Opus, Haiku)
• Claude Code Task agents (auto-discovered)
• Custom plugin agents
• External API services

Hot-reload support: New agents are automatically available without restarting.

Configuration example:

agent_node_config = {
    "goal": "Review code for security vulnerabilities",
    "required_tags": ["code", "security", "review"],
    "prefer_agent_type": "task",  # Prefer task agents if available
    "store_episodic": True  # Learn from this execution
}