🤖 Multi-Agent Orchestration & State Management
Source: Microsoft AutoGen / LangGraph / Semantic Kernel
This skill provides the Agent with the logic to manage complex, stateful workflows involving multiple AI "specialists" or autonomous task loops.
🕸️ 1. Stateful Graph Logic (LangGraph Inspired)
- Node-Based Thinking: View complex tasks as a "Graph" of nodes (Steps).
- Conditional Edges: Logic for "If step A fails, go to step B; if success, go to step C".
- Short-term vs. Long-term Memory: Maintain state across multiple turns without losing context of the "Global Goal".
👥 2. Multi-Agent Delegation (AutoGen Inspired)
Assign roles dynamically when the task is large:
- Planner: Outlines the sequence.
- Coder: Implements the logic.
- Reviewer: Audits for bugs/security.
- Executioner: Validates the final output.
🏗️ 3. Semantic Orchestration
- Plugin/Tool Selection: Dynamically choose the best tool (Search, File Read, Command Run) based on "Intent Detection".
- Ambiguity Detection: If an instruction has multiple interpretations, the Agent must PAUSE and clarify before a "branching event" in the graph.
🔄 4. Task Loops & Self-Correction
- Reflexion Pattern: After a step, evaluate: "Did this achieve the subgoal?" If no, retry with a different approach.
- Recursive Scans: Constantly scan the workspace for relevant file changes that might affect the current task.
*Created by Antigravity Orchestrator - Based on Autonomous Agent Architectures.*