oma-orchestrator

Multi-agent orchestration coordinates parallel execution by decomposing complex requests into priority-tiered tasks and dispatching specialist subagents concurrently with configurable limits. This removes the manual burden of managing multiple AI agents.

MCP memory coordination creates session-level artifacts like session state and task boards. It manages persistent task state by ensuring per-agent progress and result files avoid write conflicts during parallel execution.

Automated QA cross-review runs mechanical self-checks and executes verification loops with structured feedback and bounded retries. It iteratively verifies results until a usable output is produced, ensuring high-quality feature builds.

Yes, CLI dispatch supports native vendor dispatch and fallback spawning for specialist agents. It orchestrates automated execution while managing persistent session state and aggregating final results into session summaries.

Workflow retry loops apply bounded retry limits during verification and QA cross-review. When retries are exhausted without producing a verified result, the loop terminates and aggregates the current state into a final session summary.