v1.3.1 — Canonical IND conditional-GO decision example

Overview

v1.3.1 adds a single canonical IND decision example that demonstrates RGDS
operating under real execution constraints.

This release is designed to answer the question:
“What does this look like in practice?”

Highlights

• Canonical IND conditional-GO decision with:
  • author-at-risk drafting
  • reviewer triage
  • publishing lock points
  • dependency and readiness tracking
• Explicit, human-governed AI support artifacts (informational only)
• Documentation updates for clarity and discoverability

What this shows

• How teams can proceed responsibly with incomplete data
• How decisions are made explicit instead of reconstructed later
• How AI can support awareness without undermining accountability

Compatibility

All examples pass strict schema validation.