context-injector-usage-guide

Container-based CFN Loop orchestration coordinates agent spawning, loop execution, and consensus flow using Redis for state management and GOAP-based decision logic. Use the orchestration toolchain—init, execute, spawn-loop3, monitor-loop3, gate-check, spawn-loop2, collect-consensus, trigger-po-decision—to manage iterative governance, task analysis, and robust error handling across Loop 3 implementers, Loop 2 validators, and Product Owner decision stages.

Context patterns vary by agent scope: single-agent contexts isolate individual task execution, multi-agent contexts coordinate parallel spawning and consensus collection, and iteration-aware contexts track loop state across cycles. Format and validate contexts according to your agent count and whether monitoring or gate checks apply; broadcast formatted contexts to agents via the orchestration toolchain.

Yes. Redis manages state across container-based CFN Loop environments, while GOAP-based decision logic drives agent decision-making and consensus thresholding. Both are required to support iterative governance, monitoring, gate checks, and decision triggers in Loop 3 implementers, Loop 2 validators, and Product Owner workflows.

Validate context formatting against your agent pattern type, then broadcast using the orchestration toolchain's execute and spawn commands. Validation ensures contexts match single-agent, multi-agent, or iteration-aware schemas; broadcasting delivers formatted contexts to designated agent pools within your dockerized CFN Loop environment.

Failed consensus triggers collect-consensus and gate-check commands to re-evaluate thresholding logic and agent decisions. Robust error handling in the orchestration toolchain allows retry, reanalysis, or escalation to Product Owner decision triggers; monitor-loop3 provides visibility into failure points and agent state throughout recovery.