dragon/v2 has already reached a stable RC1 forward candidate, but the execution core is still a monolithic, order-sensitive rule tree. The biggest remaining risk is no longer a single threshold; it is change safety, explainability, and weak-family governance. Future optimization without structural control will keep exposing core alpha to accidental path drift.
dragon/v2 with RC1 frozen as baseline.core, secondary, and bridge, while keeping compatibility wrappers.deep_oversold_*, predictive_*, post_sell_rebound_*) to new research branches with mandatory added/removed trade attribution.layered-rule-engine: Evaluate rules by explicit core/secondary/bridge layers with compatibility-preserving orchestration.structured-decision-state: Maintain structured reason/state metadata for both output attribution and internal control transitions.weak-family-research-governance: Enforce branch-level isolation and attribution-first evaluation for weak-family optimization.golden-regression-governance: Treat RC1 core-hash and release-window summaries as hard guardrails for behavior-preserving refactors.dragon-strategy-execution: Move from monolithic tree-only governance to layered orchestration with compatibility entry points.strategy-research-workflow: Shift acceptance from return-only checks to governance-quality checks (attribution, replay stability, rollback readiness).dragon_strategy.py, new layered rule modules, structured context/state modules, tests, and reporting scripts.dragon_rc1_golden_manifest.json, rule-layer attribution outputs, new OpenSpec change package, and migration audit notes.