Agent Architecture Review, Validation snapshot

This is an autonomous agentic workflow: `run()` builds an `ExecutionPlan`, iterates through PRs, calls the OpenAI API in `review_pr()`, makes routing decisions in `_process_pr()`, and can execute side-effecting actions via `post_comment()`, `apply_suggested_fix()`, and `merge_pr()`. Delegation scope is explicit through `DelegationPolicy.allowed_repos`, `allowed_actions`, `high_risk_paths`, `auto_merge_enabled`, and `auto_merge_max_score`. Execution is policy-gated through `available_actions()` and re-checked before mutation in `_process_pr()`. However, mid-process steering is incomplete: `ACTION_TO_POLICY_NAME` includes `skip` and `reject` but no `abort`, despite the stated operator-steering…

The workflow provides perceptibility while the process is alive through `TriageState.log()`, `state.event_log`, per-record `events`, and console messages such as `WORKFLOW_STARTED`, `PLAN_PUBLISHED`, `REVIEW_STARTED`, `APPROVAL_PENDING`, and `PR_BLOCKED`. It also writes an audit file in `save_audit()`. However, operational state is mostly in memory until the final `save_audit()` call. If the process is killed, the host crashes, or a long-running review is interrupted outside the top-level exception path, intermediate progress can be lost. There is no durable job state, resumable checkpoint, heartbeat, or external status endpoint for a user to leave and return to.

The implementation has a concrete audit structure: `AuditRecord` tracks `pr_id`, `repo`, `diff_hash`, `review`, `status`, `approval_decision`, `approver`, `actions_taken`, `rollback_token`, and per-PR `events`; `save_audit()` serializes these along with `run_id`, `plan`, and `event_log`. This supports basic inspectability. However, the provenance is not audit-grade: `diff_hash()` uses Python's built-in `hash(diff)`, which is salted and not stable across processes; the audit omits the actual `raw_response` from `ParsedReview`, even though it is stored in memory; it also omits the exact model name, prompts/messages, branch/title/author metadata, and any external API response identifiers. As a…

The code exposes user-relevant workflow states through `PRStatus`, including `QUEUED`, `REVIEWING`, `AWAITING_APPROVAL`, `BLOCKED_HIGH_RISK`, `BLOCKED_INVALID_OUTPUT`, `COMPLETED`, and `FAILED`. `_process_pr()` maps model/output and policy outcomes to those statuses, and `approval_gate()` presents operator-facing information such as PR id, repo, branch, AI score, summary, and permitted actions. The event names such as `PR_BLOCKED`, `APPROVAL_REQUESTED`, `COMMENT_RECORDED`, and `MERGE_DENIED` are generally understandable and tied to operator-relevant outcomes rather than low-level implementation details.