aming-claw-hn-challenge

Multi-agent orchestration with auditable graphs uses a single observer to guide multiple workers against a unified commit-bound project graph, capturing contracts and timeline events to derive deterministic, replayable results.

Observer-driven choreography is a coordination pattern where one AI observer guides multiple worker contracts against the same project graph to produce reproducible outcomes and traceable decisions.

Generate audit reports by capturing graph traces, contracts, fences, and timeline events during the orchestration, then deriving the final merge state and audit logs from the observed evidence.

Yes, MCP resource integration is required to bootstrap safe project contexts, relying on current-context, skill, and graph-first resources to establish guardrails that prevent unsafe steps.

Yes, replayability is supported by capturing contracts, fences, graph traces, and timeline events, enabling you to replay and verify the deterministic outcomes of the worker contracts.

Using a single observer requires a commit-bound project graph and strict contract-based governance, meaning orchestration is constrained to deterministic, guardrail-protected scenarios rather than open-ended execution.