bridge-advisor

You can preserve strategic context across multi-day PRs and agent handoffs by applying read-only analysis to flag scope drift, review-rule violations, and evidence gaps. This keeps long-running AI collaboration grounded without modifying code.

Enforcing Mastra-first guardrails in PR reviews involves auditing claim quality to ensure canonical platform primitives are used instead of custom workarounds. The process flags drift between proposal and execution, demanding artifact-backed runtime evidence before merge.

Yes, reviewing long-running AI collaboration sessions is the core use case. It audits claim quality and trust boundaries across plans and agent handoffs, applying read-only scrutiny to identify scope creep and preserve strategic context without touching code.

Checking a migration plan for evidence gaps involves scrutinizing runtime evidence and explicitly flagging unsupported assertions. The review coordination process identifies drift between proposal and execution, requiring artifact-backed proof before decisions harden into implementation.

An evidence-first AI review audit should not be used when you need to modify code or execute runtime changes, as it is strictly read-only. It is designed for analysis and flagging scope drift, not for directly resolving unsupported assertions within the codebase.