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Reviewed

Assessment complete; awaiting evidence revision.

Agent Architecture Review, Validation snapshot

Evaluated 30 April 2026 against the AI Design Blueprint doctrine · focus: code-review agent governance for software engineering workflows

Needs Changes

Status: Needs Changes

0/4

aligned of applicable principles · 0%

This is an autonomous agentic PR triage workflow, so the listed agentic design principles apply strictly. The implementation has strong governance-oriented structure: scoped repo policy, explicit plan display, structured model parsing, per-PR statuses, audit records, and a blocking approval gate. However, several controls are incomplete: `allowed_actions` and `auto_merge_max_score` are not enforced, the approval UI can offer actions that policy does not allow, action functions log successful external effects without actually performing them, audit persistence is overwrite-based rather than immutable, and failures are not converted into meaningful terminal states. Overall, the design is directionally sound but needs changes before it can be considered governance-ready.

Per-principle findings

4 principles evaluated. Verdict, severity, evidence and recommendation for each.

P0

Design for delegation rather than direct manipulation

needs changes

Classified as category (A), an autonomous agentic workflow: `run()` iterates through `PULL_REQUESTS`, calls the LLM in `review_pr()`, makes policy/risk decisions, invokes an approval gate, and conditionally performs actions such as `post_comment()`, `apply_suggested_fix()`, and `merge_pr()`. For Principle 1, the code defines a clear `DelegationPolicy` with `allowed_repos`, `allowed_actions`, `high_risk_paths`, and `auto_merge_enabled`, and it filters repos via `in_scope = [pr for pr in PULL_REQUESTS if pr["repo"] in policy.allowed_repos]`. However, `allowed_actions` is never enforced before execution. The approval UI offers merge via `[m]erge` even though `DEFAULT_POLICY.allowed_actions` exc…

Recommendation

Enforce `policy.allowed_actions` at the decision and execution layers. Do not display or accept actions that are not allowed by policy. Before any action branch, validate the requested action against `policy.allowed_actions`; for merge, also enforce `auto_merge_enabled`, `auto_merge_max_score`, repo scope, high-risk path rules, and approval identity/role.

P0

Replace implied magic with clear mental models

needs changes

The code improves the mental model by publishing an `ExecutionPlan` from `build_plan()`, printing `EXECUTION PLAN`, logging events through `TriageState.log()`, and parsing model output through `parse_review()`. It also distinguishes statuses such as `BLOCKED_INVALID_OUTPUT`, `BLOCKED_HIGH_RISK`, and `AWAITING_APPROVAL`. However, several user-facing claims are misleading or incomplete. The plan says `Execute only approved actions (comment, suggest_fix, merge)` even though `merge` is not in `DEFAULT_POLICY.allowed_actions`. The plan says `Persist immutable audit record to disk`, but `save_audit()` writes to a fixed `audit_log.json` path with mode `"w"`, overwriting previous records. `post_comm…

Recommendation

Make the displayed plan derive from the actual effective policy and implementation. Mark stubbed actions as dry-run or replace them with real tool/API calls and error handling. Change audit persistence language or implement append-only/immutable storage. Strengthen structured-output validation with required fields, explicit types, and schema validation, and block downstream actions on all validation failures.

P0

Expose meaningful operational state, not internal complexity

needs changes

The `PRStatus` enum provides meaningful user-level states such as `QUEUED`, `REVIEWING`, `AWAITING_APPROVAL`, `BLOCKED_HIGH_RISK`, `BLOCKED_INVALID_OUTPUT`, `COMPLETED`, and `FAILED`. Per-PR state is stored in `AuditRecord.status` and updated during `run()`. This aligns with the principle at a structural level. Gaps remain: `FAILED` is never used because `review_pr()`, `post_comment()`, `apply_suggested_fix()`, `merge_pr()`, and `save_audit()` are not wrapped in exception handling; an LLM/API/file-write failure would terminate the workflow without updating `rec.status` or preserving a final audit state. Also, `save_audit()` logs `AUDIT_TRAIL_SAVED` after writing the file, and `run()` logs `W…

Recommendation

Add try/except/finally handling around each PR and around audit persistence so failures transition records to `FAILED` with user-relevant error details. Persist terminal workflow events as part of the audit trail, or log them before writing. Consider adding a run-level status in addition to per-PR status.

P0

Make hand-offs, approvals, and blockers explicit

needs changes

The code has an explicit blocking approval mechanism in `approval_gate()`, logs `APPROVAL_REQUESTED`, prints PR details, shows high-risk warnings, and requires an operator decision through `input("Decision: ")`. It also blocks invalid model output by returning `reject` when `record.status == PRStatus.BLOCKED_INVALID_OUTPUT`. However, the gate is not fully robust. It logs `APPROVAL_GRANTED` for every mapped decision, including `reject`, and silently maps invalid input to `reject`. It hardcodes `rec.approver = "operator"` rather than capturing an authenticated approver. It presents `[m]erge` even when merge is not an allowed action in `policy.allowed_actions` or when `policy.auto_merge_enabled…

Recommendation

Make the approval menu policy-aware, showing only currently valid actions and clear reasons for unavailable actions. Log `APPROVAL_REJECTED` or `APPROVAL_DECISION_REJECT` separately from granted approvals. Capture authenticated approver identity and authorization. Persist the approval decision before executing any mutation such as suggested fixes or merge.

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Run ID: 380d6b8c-3291-47e6-ba71-6f4f4f43ae4b · Results expire after 90 days

Run by agents. Governed by humans. Validated by the AI Design Blueprint.