code-review

name	code-review
version	2.4.0
description	[Code Quality] Use when evaluating review feedback, requesting targeted code-quality review, or verifying completion claims.
execution-mode	subagent
context-budget	critical

[BLOCKING] Execute skill steps in declared order. NEVER skip, reorder, or merge steps without explicit user approval. [BLOCKING] Before each step or sub-skill call, update task tracking: set in_progress when step starts, set completed when step ends. [BLOCKING] Every completed/skipped step MUST include brief evidence or explicit skip reason. [BLOCKING] If Task tools are unavailable, create and maintain an equivalent step-by-step plan tracker with the same status transitions.

Quick Summary

Goal: Ensure reviewed code is correct, easy to change, convention-aligned, and verification-backed before acceptance or handoff — via receiving feedback with verification (not performative agreement), requesting targeted systematic reviews through the code-reviewer subagent, and enforcing verification gates before completion claims.

Routing boundary: If the user asks to review current changes, uncommitted work, staged/unstaged diffs, or a branch-to-branch diff, use changes-review instead.

Shared engine (keep in sync): code-review and changes-review share the same review-protocol SYNC: blocks. Canonical source: .claude/skills/shared/sync-inline-versions.md; policy: SYNC:shared-protocol-duplication-policy. When you change a shared block in one skill, update the canonical file AND the sibling skill so the two never drift. The skills differ only in entry intent (explicit scope / feedback / completion-gate vs git diff) — not in review quality.

MANDATORY Before reviewing, search for project-specific reference docs:

Coding standards — search: code-review-rules, coding-standards, style-guide, contributing Architecture — search: patterns-reference, architecture, adr Test conventions — search: integration-test-reference, test-guide, test-conventions Design system — search: design-system, design-tokens, component-library

Read found docs before reviewing. None found → rely on tech stack knowledge from file extensions/directory structure.

Workflow:

1. Create Review Report — Init plans/reports/code-review-{date}-{slug}.md
2. Phase 0: Blast Radius — Run graph analysis first if .code-graph/graph.db exists
3. Phase 0.1: Change Context & Full-Pipeline Impact Trace (MANDATORY comprehension-first) — Note the change context, then holistically trace the main affected area's full pipeline across BOTH boundaries — client↔server tier (FE↔BE) AND service/event/external — classifying each seam/touchpoint NONE/ADDITIVE/BREAKING (explicit N/A for single-tier or monolith)
4. Phase 0.3: Risk Detection — Detect dependency, migration, bus/event, API, security, config, and infra risks
5. Phase 0.5: Plan Compliance — Verify changed files and tests against active plan when present
6. Phase 0.7: Surface Detection — Classify files by language + directory semantics + change nature → route sub-agents; invoke /ui-review when frontend/UI files are present
7. Phase 1: File-by-File — Review each file, update report with correctness, convention, DRY, intent, test, and docs checks
8. Phase 2: Holistic — Re-read accumulated report, assess overall approach, architecture, duplication, and cross-boundary behavior
9. Phase 3: Final Result — Update report with overall assessment, critical issues, recommendations, docs staleness, and test gaps
10. Fix Loop: Validate → Fix → Full Re-Review — When findings exist, validate them first, fix only validated findings, then restart the full review after the fix cycle

Key Rules:

• Report-Driven: Build report incrementally; re-read for big picture
• Detect First: Run graph blast radius when available, then classify change types and file surfaces before any review
• Easy to Change for Code: Treat future change cost as the primary code-quality metric; DRY, SOLID, abstraction, and patterns are tools only when they reduce change amplification
• No Performative Agreement: Technical evaluation only ("You're right!" banned)
• Verification Gates: Evidence required before completion claims
• Review Current Diffs Elsewhere: Current changes, staged/unstaged diffs, and branch diffs belong to changes-review
• A clean review pass ENDS the review. Do not spend a fresh-context pass re-reviewing known findings before validation/fix; only re-review after fixes change the target.

Code Review

Three practices: receiving feedback with technical rigor, requesting systematic reviews via code-reviewer subagent, enforcing verification gates before completion claims.

Run python .claude/scripts/code_graph query tests_for <function> --json on changed functions to flag coverage gaps.

Review Mindset (NON-NEGOTIABLE)

Skeptical. Every claim needs traced proof file:line. Confidence >80% to act.

• NEVER accept code correctness at face value — trace call paths
• NEVER include finding without file:line evidence (grep results, read confirmations)
• ALWAYS question: "Does this actually work?" → trace it. "Is this all?" → grep cross-service
• ALWAYS verify side effects: check consumers + dependents before approving

First Principle — Easy to Change

The success metric of every coding decision is future change cost. DRY, SRP, abstraction, design patterns, naming, layering, tests — every technique exists to serve one goal: making the next change cheaper.

When evaluating code, a refactor, a test, or an abstraction, ask: does this make the next change cheaper or more expensive?

• Reject "best practices" that raise change cost (premature abstraction, speculative generality, leaky indirection, ceremony without payoff).
• Name the real enemies in findings: coupling, hidden state, duplicated knowledge, unclear intent, irreversible decisions exposed too early.
• Favor project-owned boundaries around external libraries, for example component/service input-output contracts, when they localize future library changes; reject pass-through wrappers that add ceremony without lowering change cost.
• A simpler design that is easy to change beats a sophisticated design that isn't.

Apply this lens before invoking any specific rule, pattern, or checklist below — if a downstream rule would raise change cost, this principle wins.

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Core Principles (ENFORCE ALL)

Principle	Rule
YAGNI	Flag code solving hypothetical problems (unused params, speculative interfaces)
KISS	Flag unnecessary complexity. "Is there a simpler way?"
DRY	Grep for similar/duplicate code. 3+ similar patterns → flag for extraction
Clean Code	Readable > clever. Names reveal intent. Functions do ONE thing. Nesting <=3. Methods <30 lines
Convention	MUST ATTENTION grep 3+ existing examples before flagging violations. Codebase convention wins over textbook
No Bugs	Trace logic paths. Verify edge cases (null, empty, boundary). Check error handling
Proof Required	Every claim backed by file:line evidence. Speculation is forbidden
Doc Staleness	Cross-ref changed files against related docs. Flag stale/missing updates

Technical correctness over social comfort. Verify before implementing. Evidence before claims.

Graph-Enhanced Review (RECOMMENDED if graph.db exists)

1. python .claude/scripts/code_graph graph-blast-radius --json — prioritize files by impact (most dependents first)
2. python .claude/scripts/code_graph query tests_for <function_name> --json — flag untested changed functions
3. python .claude/scripts/code_graph trace <file> --direction downstream --json — downstream impact (events, bus, cross-service)
4. python .claude/scripts/code_graph trace <file> --direction both --json — full flow context for controllers/commands/handlers
5. Wide blast radius (>20 impacted nodes) = high-risk. Flag in report.

Review Approach (Report-Driven Two-Phase — CRITICAL)

MANDATORY FIRST: Create Todo Tasks

Task	Status
[Review] Create report file	in_progress
[Review Phase 0] Run graph blast-radius if available	pending
[Review Phase 0.1] Note change context + holistic full-pipeline trace across BOTH boundaries — client↔server tier (FE↔BE) AND service/event/external — classify each seam/touchpoint NONE/ADDITIVE/BREAKING (MANDATORY comprehension-first; N/A for single-tier/monolith)	pending
[Review Phase 0.3] Detect high-risk change types	pending
[Review Phase 0.5] Plan compliance check (skip if no active plan)	pending
[Review Phase 0.7] Detect categories + route sub-agents	pending
[Review Phase 0.7b] /ui-review sub-review — skip if no frontend/UI files in changeset	pending
[Review Phase 1] File-by-file review + update report	pending
[Review Phase 2] Holistic assessment	pending
[Review Phase 3] Final findings, docs triage, and test sync findings	pending
[Review Fix Loop] Validate findings, fix validated issues, and full re-review if fixes are applied	pending
[Review Final] Consolidate all rounds	pending

Step 0: Create Report File

Create plans/reports/code-review-{date}-{slug}.md with Scope, Files to Review sections.

Phase 0: Graph Blast Radius (FIRST WHEN AVAILABLE)

If .code-graph/graph.db exists, run graph impact analysis before reviewing:

• python .claude/scripts/code_graph graph-blast-radius --json or the project equivalent
• Record impacted files count, untested changed functions, and risk level in the report
• Prioritize high-impact files during Phase 1

If graph data is unavailable, record "Graph not available — skipping blast radius" and proceed to Phase 0.1.

Phase 0.1: Change Context Comprehension & Full-Pipeline Impact Trace (MANDATORY — comprehension-first)

IMPORTANT MANDATORY MUST ATTENTION: First comprehension step — before any file-by-file or dimensional review. Blast radius (Phase 0) gathers impact data; here holistically UNDERSTAND the change, trace main affected area's full pipeline across every boundary it crosses. Apply BOTH the Cross-Stack Impact Trace and Cross-Service Check protocols (bodies in the SYNC section below). This holistic first-pass map FEEDS the later Phase 0.3 change-type risk tasks and the Phase 2 holistic cross-boundary assessment — does not replace them.

Write a one-paragraph Change Context note (what changed · intent · originating tier · main affected feature/flow), then run both traces per the Cross-Stack Impact Trace and Cross-Service Check protocols (SYNC blocks below).

Phase 0.3: Detect High-Risk Change Types

Before file review, inspect the target diff or explicit file set for:

• Bugfix, failed verification, stale/incorrect final output, regression, or behavior-changing fix — require Debugger Trace: End -> Start, all feeder paths, hypothesis matrix, owning fix layer, and forward convergence proof; missing trace evidence is a High/Critical review finding
• Dependency upgrades — semver, breaking changes, advisories, peer compatibility
• Migrations or schema changes — rollback, lock/volume impact, zero-downtime deployment, idempotent backfill
• Bus events/messages — consumer existence, idempotency, retries, poison/dead-letter handling
• API contract changes — backward compatibility, caller alignment, auth, required response fields
• Security changes — enforcement coverage, privilege escalation, negative tests, duplicated permission strings
• Config/env changes — all environments covered, no secrets, fail-fast behavior, setup docs
• Infra changes — dev/prod parity, pinned versions, CI/CD permissions, reproducible builds

Create focused review tasks for every true signal and complete them before dimensional review.

Phase 0.5: Plan Compliance Check (CONDITIONAL)

If active plan context exists, verify scope, test evidence, and success criteria against the plan before file review; otherwise record the skip reason.

Goal Contract mapping (CONDITIONAL — when an active goal exists): Resolve the active Goal Contract per the goal-contract-satisfaction-loop protocol (active plan goal.md → plans/goals/{YYMMDD-HHmm}-{slug}/goal.md). When found, map the reviewed changes to the saved success criteria in the report — which criteria this changeset advances (with file:line evidence), which it leaves untouched, and any change serving NO saved criterion (flag as scope drift unless justified). Record No active goal — mapping skipped. when none exists; do NOT create a goal file from inside a review.

Phase 0.7: Detect Review Categories

Before any review — classify the changeset and route sub-agents:

Signal in changed files	Route to
Auth/permission/token/encryption files	security-auditor
Query files, caching, batch processing	performance-optimizer
Source code (logic, handlers, services)	code-reviewer
Frontend/UI files (components, templates, .html/.scss/.css, design-system)	/ui-review skill (see Phase 0.7b)
Docs, plans, specs, markdown	general-purpose
Mixed changeset with security/perf files	Spawn specialized sub-agent first, then code-reviewer

Phase 0.7b: Frontend/UI Sub-Review (CONDITIONAL — /ui-review)

If the changeset contains any frontend/UI files matching the project's configured UI patterns (components, templates, .html/.scss/.css, design-system tokens), invoke the /ui-review skill as a sub-review so UI-specific concerns are covered — long-content overflow (wrap vs ellipsis+tooltip), responsive multi-screen flex, flex-grow with min/max over fixed px, semantic z-index discipline (no raw numbers, no !important), and BEM classes on all template elements. Fold its findings into this report's Phase 3 results.

Skip (record reason) when no frontend/UI files are present in the changeset — log "Skipped Phase 0.7b — no frontend/UI files in changeset".

Phase 0.8: Derive Review Categories

Group changed files by: file language (extension), directory semantics (path), change nature (new entity, schema, config, UI, test).

For each category: name it, create sub-task, derive concerns using SYNC:category-review-thinking (first principles — NOT a fixed checklist).

Category list = Phase 1 work breakdown. Each category → own section in report.

Phase 1: File-by-File Review (Build Report)

For EACH file, immediately update report:

• File path, Change Summary, Purpose, Issues Found
• Convention check: Grep 3+ similar patterns — does new code follow existing convention?
• Correctness check: Trace logic — null, empty, boundary, error cases handled?
• DRY check: Grep for similar/duplicate code — does this logic exist elsewhere?
• Intention check: Does the change serve the stated purpose? Flag unrelated modifications
• Test check: Changed behavior has corresponding test/spec coverage or a documented gap
• Documentation check: Related docs/specs/READMEs still match the changed behavior

Phase 2: Holistic Review (Re-read Report)

After all files reviewed, re-read accumulated report:

• Technical Solution: Overall approach coherent as unified plan?
• Responsibility: Logic in LOWEST layer? Business logic not in controllers?
• Data ownership: Constants/config in model/entity, not controller/component?
• Duplication: Grep to verify — duplicated logic across changes?
• Architecture: Clean Architecture? Service boundaries respected?
• Plan Compliance: If active plan → check ## Plan Context: impl matches requirements, TCs have code evidence (not "TBD"), no requirement unaddressed
• Design Patterns: Pattern opportunities (switch→Strategy)? Anti-patterns (God Object, Copy-Paste, Circular Dep)? DRY via base classes?
• Cross-Boundary Behavior: Callers/callees aligned? API/event contracts consistent? New wiring reachable?
• Test Sync: Business logic changes have corresponding tests or explicit user-facing gap
• Translation Sync: Multilingual UI text changes have translation updates or explicit risk acceptance
• Bugfix Trace Completeness: If the diff is a bugfix or behavior-changing fix, the review report must state whether final-state trace, feeder paths, hypothesis matrix, owning fix layer, forward convergence proof, and tests/proof mapping are complete

MUST ATTENTION CHECK — Spec-Loop Test Discipline (changed core logic): Beyond the happy/error path traces above, hold changed core logic to a hard-to-fake bar. Apply a MUTATION-SCORE bar — a surviving mutant means a missing invariant, so demand the killing test — and do NOT accept a line-coverage % as proof of test strength. Flag any [HARD]/§5 invariant whose only coverage is example tests with no universally-quantified property TC (plus boundary counter-case) as a HIGH finding. Every behavior-changing finding requires a Dual-Feedback row (does it feed the spec? does it feed the tests? a blank axis = INCOMPLETE) — record it in the report. Adjudicate any spec divergence per SYNC:spec-drift-adjudication (CODE-WRONG / SPEC-STALE / AMBIGUOUS / SPEC-SILENT); a SPEC-SILENT finding — the code correctly enforces an invariant NO spec artifact states — has BOTH axes non-N/A: Spec feedback = add the missing §4 BR / §3 AC (+ §5 invariant if applicable) and a §8 TC via /spec [update] + /spec [mode=tests]; Test feedback = the new property/regression test guarding the now-written invariant — never leave a discovered invariant only in code or only in tests. Review the whole package (spec + tests + code), not just the diff, so the spec is enriched, not just patched.

MUST ATTENTION CHECK — Clean Code: YAGNI (unused params, speculative interfaces)? KISS (simpler exists)? Methods >30 lines or nesting >3?

MUST ATTENTION CHECK — Correctness: Null/empty/boundary handled? Error paths caught? Async race conditions? Trace happy + error paths.

Documentation Staleness Check:

For each changed file — grep file name/module across docs/ and AI tooling dirs. Changed behavior → flag stale doc (specific section + what changed). Flag the staleness only — never auto-fix docs here.

Common staleness patterns: count/limit changed → docs embedding that number | API/contract changed → API usage docs | hook/skill added/removed → catalogs/README | schema changed → entity reference docs.

Phase 3: Final Review Result

Update report: Overall Assessment, Critical Issues, High Priority, Architecture Recommendations, Cross-Boundary Impact (from Phase 0.1 — per client↔server seam AND per service/event/external touchpoint: NONE / ADDITIVE / BREAKING with routed fix; or explicit "Single-tier / monolith — N/A"), Documentation Staleness, Positive Observations.

If documentation staleness is detected, recommend docs-update and list exact stale sections; do not silently pass stale docs.

Validated Fix + Full Re-Review (MANDATORY when findings are fixed)

After Phase 3, do not spawn a fresh reviewer just to re-review the same finding set. First validate findings, then fix only validated findings. Because fixes change the review target, restart the full review after the fix cycle. If that restarted protocol uses sub-agents, construct each Agent call with the canonical template from SYNC:review-protocol-injection:

1. Copy Agent call shape from SYNC:review-protocol-injection verbatim
2. Embed full verbatim body of all 11 SYNC blocks: SYNC:spec-tests-code-triangulation, SYNC:evidence-based-reasoning, SYNC:bug-detection, SYNC:design-patterns-quality, SYNC:complexity-prevention, SYNC:logic-and-intention-review, SYNC:test-spec-verification, SYNC:fix-layer-accountability, SYNC:rationalization-prevention, SYNC:graph-assisted-investigation, SYNC:understand-code-first
3. Task: "Run a full fresh code-review pass over the current assigned scope after validated fixes were applied. Focus: cross-cutting concerns, interaction bugs, convention drift, missing pieces, subtle edge cases, logic errors, test spec gaps, and regressions introduced by the fixes."
4. Target Files: "use the explicit files, plan scope, or reviewer-provided target range"
5. Report: plans/reports/code-review-rerun{N}-{date}.md

After sub-agent returns:

1. Read report from plans/reports/code-review-rerun{N}-{date}.md
2. Integrate findings as ## Re-Review {N} Findings — DO NOT filter or override
3. If findings remain: validate the new finding set before any additional fixes
4. Repeat only after another fix cycle: restart the full review again after validated fixes are applied; if the same blocker repeats across 3 full invocations with no progress, escalate via AskUserQuestion

Clean Code Rules (MUST ATTENTION CHECK)

#	Rule	Details
1	No Magic Values	All literals → named constants
2	Type Annotations	Explicit parameter and return types on all functions
3	Single Responsibility	One concern per method/class. Event handlers/consumers: one handler = one concern. NEVER bundle — a framework event dispatcher can swallow handler exceptions silently
4	DRY	No duplication; extract shared logic
5	Naming	Specific (orderRecords not data), Verb+Noun methods, is/has/can/should booleans, no abbreviations
6	Performance	No O(n²) (use dictionary). Project in query (not load-all). ALWAYS paginate. Batch-by-IDs (not N+1)
7	Entity Indexes	Collections: index management methods. EF Core: composite indexes. Expression fields match index order. Text search → text indexes

Data Lifecycle Rules (MUST ATTENTION CHECK)

Decision test: "Delete the DB and start fresh — does this data still need to exist?" Yes → Seeder/fixture. No → Migration.

Type	Contains	NEVER contains
Seeder / Fixture	Default records, system config, reference data (idempotent — safe to run every startup)	Schema changes
Migration	Schema changes, column adds/removes, data transforms, index changes	Default records, permission seeds, system config

Apply project's language/framework conventions. Principle universal — implementation project-specific.

Legacy Pattern Compliance

When reviewing files with legacy and modern patterns:

1. Detect legacy signals — search project-config.json, package.json, or equivalent for "legacy", version flags, feature annotations
2. Read what "legacy" means — grep 3+ legacy files to understand pattern constraints vs. modern files
3. Derive compliance rules — what lifecycle/memory management differences exist between legacy/modern for this tech stack?
4. Apply tech stack knowledge to flag anti-patterns

NEVER assume any specific framework's lifecycle. Derive from codebase evidence.

When to Use This Skill

Practice	Triggers	MUST ATTENTION READ
Receiving Feedback	Review comments received, feedback unclear/questionable, conflicts with existing decisions	references/code-review-reception.md
Requesting Review	After each subagent task, major feature done, targeted review scope, after complex bug fix	references/requesting-code-review.md
Verification Gates	Before any completion claim, commit, push, or PR. ANY success/satisfaction statement	references/verification-before-completion.md

Quick Decision Tree

SITUATION?
│
├─ Received feedback
│  ├─ Unclear items? → STOP, ask for clarification first
│  ├─ From human partner? → Understand, then implement
│  └─ From external reviewer? → Verify technically before implementing
│
├─ Completed work
│  ├─ Major feature/task? → Request code-reviewer subagent review
│  └─ Before merge? → Request code-reviewer subagent review
│
└─ About to claim status
   ├─ Have fresh verification? → State claim WITH evidence
   └─ No fresh verification? → RUN verification command first

Receiving Feedback Protocol

Pattern: READ → UNDERSTAND → VERIFY → EVALUATE → RESPOND → IMPLEMENT

• NEVER use performative agreement ("You're right!", "Great point!", "Thanks for...")
• NEVER implement before verification
• MUST ATTENTION restate requirement, ask questions, or push back with technical reasoning
• ask for clarification on ALL unclear items BEFORE starting
• grep for usage before implementing suggested "proper" features (YAGNI check)

Source handling: Human partner → implement after understanding. External reviewer → verify technically, push back if wrong.

Full protocol: references/code-review-reception.md

Requesting Review Protocol

1. Get git SHAs: BASE_SHA=$(git rev-parse HEAD~1) and HEAD_SHA=$(git rev-parse HEAD)
2. Dispatch code-reviewer subagent with: WHAT_WAS_IMPLEMENTED, PLAN_OR_REQUIREMENTS, BASE_SHA, HEAD_SHA, DESCRIPTION
3. Act on feedback: Critical → fix immediately. Important → fix before proceeding. Minor → note for later.

Full protocol: references/requesting-code-review.md

Verification Gates Protocol

Iron Law: NO COMPLETION CLAIMS WITHOUT FRESH VERIFICATION EVIDENCE

Gate: IDENTIFY command → RUN it → READ output → VERIFY it confirms claim → THEN claim. Skip any step = lying.

Claim	Required Evidence
Tests pass	Test output shows 0 failures
Build succeeds	Build command exit 0
Bug fixed	Original symptom test passes
Requirements met	Line-by-line checklist verified

Red Flags — STOP: "should"/"probably"/"seems to", satisfaction before verification, committing without verification, trusting agent reports.

Full protocol: references/verification-before-completion.md

Related

• code-simplifier
• debug-investigate
• refactoring

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Systematic Review Protocol (10+ changed files)

When Phase 1 finds 10+ changed files, apply the Systematic Review Batching protocol (map-reduce: size-capped batches + hierarchical synthesis) defined below.

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Workflow Recommendation

MANDATORY — NO EXCEPTIONS: If NOT already in a workflow, use AskUserQuestion to ask user:

1. Activate workflow-review-changes workflow (Recommended) — full review → validated fix cycle → re-review until clean
2. Execute /code-review directly — run standalone

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Architecture Boundary Check

For each changed file, verify no forbidden layer imports:

1. Read rules from docs/project-config.json → architectureRules.layerBoundaries
2. Determine layer — match file path against each rule's paths glob patterns
3. Scan imports — grep for the configured language's import/include statements
4. Check violations — import path contains forbidden layer name → violation
5. Exclude framework — skip files matching architectureRules.excludePatterns
6. BLOCK on violation — "BLOCKED: {layer} layer file {filePath} imports from {forbiddenLayer} ({importStatement})"

If architectureRules absent in project-config.json → skip silently.

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Phase 4: Why-Review Self-Validation Gate (MANDATORY when findings exist)

Purpose: Adversarial validation of own findings BEFORE handoff. Catches over-flagged Highs, false positives, and severity inflation at the source rather than letting them propagate downstream.

Trigger: Any finding produced (Critical, High, Medium, OR Low). Skip ONLY when the report's verdict is unconditional PASS with literally zero findings.

Protocol:

1. Read own finalized report from plans/reports/{skill}-{date}-{slug}.md
2. Invoke /why-review skill with arg: validate findings in plans/reports/{skill}-{date}-{slug}.md — verify each finding has file:line proof, steel-man each rejected interpretation, and stress-test severity classifications
3. Read the validation verdict path returned by why-review, expected as plans/reports/why-review-validate-{date}.md
4. If why-review demotes/removes any finding: UPDATE own finalized report with revised severities, remove false positives, and add a ## Why-Review Validation Notes section citing what changed and why
5. If why-review confirms all findings: Append ## Why-Review Validation line to own report stating "All N findings re-validated against actual code; no severity changes."

Skip conditions (record explicit reason if skipping):

• Verdict is unconditional PASS with zero findings → log "Skipped — no findings to validate"
• Why-review skill itself is the active context (avoid recursion)

Why this exists: AI sub-agent reports inherit confirmation bias — the orchestrator absorbs severity claims as ground truth. The 2026-05-09 review incident produced 5 Highs; adversarial validation demoted 3 of them. Codify this as standard practice.

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Next Steps

MANDATORY — NO EXCEPTIONS after completing, use AskUserQuestion:

• "/fix (Recommended)" — review found issues needing fixes
• "/watzup" — review clean, wrap up session
• "Skip, continue manually" — user decides

AI Agent Integrity Gate (NON-NEGOTIABLE)

Completion ≠ Correctness. Before reporting ANY work done:

1. Grep every removed name. Extraction/rename/delete → grep confirms 0 dangling refs across ALL file types.
2. Ask WHY before changing. Existing values intentional until proven otherwise.
3. Verify ALL outputs. One build passing ≠ all builds passing.
4. Evaluate pattern fit. Copying nearby code? Verify preconditions match — scope, lifetime, base class, constraints.
5. New artifact = wired artifact. Created something? Prove it's registered, imported, reachable by all consumers.

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[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

Critical Purpose: Ensure quality — no flaws, bugs, missing updates, stale content. Verify code AND documentation.

External Memory: Complex work → write findings incrementally to plans/reports/ — prevents context loss, serves as deliverable.

Evidence Gate: MANDATORY — every claim, finding, recommendation requires file:line proof + confidence % (>80% act, <80% verify first).

OOP & DRY: MANDATORY — flag patterns extractable to base class/generic/helper. Same-suffix/lifecycle/responsibility classes share common base. Apply idiomatic abstraction (base class, mixin, trait, protocol) for project's language. Verify linting/analyzer configured.

Cross-Stack Impact Trace — FIRST review action: comprehend change holistically, THEN judge files. Every reviewed diff: note change context, trace full pipeline of main affected area end-to-end across client↔server seam, so a change on one tier can never silently break the other. (Distinct from SYNC:cross-service-check, which owns service-to-service / event boundary — this owns client↔server tier seam inside one app; pair both for full-pipeline coverage.)

1. Comprehend context FIRST — before file-by-file review, write short Change Context note: what changed, intent (why), originating tier (frontend / backend / shared / infra), main affected feature/flow. Do before flagging anything.
2. Identify cross-stack seam(s) — for main affected area, locate contract seam(s) between client and server: API route/endpoint + verb, request/response DTO or payload shape, shared type/schema, event/message contract, query/route params. Infer tier layout from docs/project-config.json and project conventions.
3. Trace full pipeline end-to-end, in change's direction:
   • Backend change → trace FORWARD to every frontend consumer: handler/controller → response DTO/serializer → API client/service → store/state → component/template rendering or submitting it.
   • Frontend change → trace BACKWARD to backend contract: component/form → API client call → route/endpoint → request DTO/validation → handler/domain.
   • When .code-graph/graph.db exists, use /graph-connect-api and python .claude/scripts/code_graph trace <file> --direction both --json to map connection; otherwise grep route path, DTO/type name, each field name across BOTH tiers.
4. Verify BOTH sides still agree — for every changed seam confirm other tier matches: route path & verb, field names & types, nullability/optionality, required vs optional params, enum values, auth/permission, error/status shape. Any mismatch = BREAKING finding (backend change breaks a frontend consumer, or frontend now sends what backend rejects).
5. Classify each seam: NONE (no contract change) / ADDITIVE (backward-compatible) / BREAKING (consumer on other tier must change too). BREAKING seam whose other-tier consumer NOT updated in same diff = HIGH severity minimum (CRITICAL for auth/money/data-integrity paths).

Skip ONLY when change has no cross-tier seam — pure docs, pure styling with no data contract, or single-tier tooling. State explicitly: Single-tier change — no cross-stack seam. Backend-only or single-tier repo still traces internal consumers (SYNC:cross-service-check for service/event boundaries).

BLOCKED until: Change Context noted · seam(s) identified or explicit N/A · full pipeline traced in change direction · every changed seam classified NONE / ADDITIVE / BREAKING.

Cross-Service Check — Microservices/event-driven: MANDATORY before concluding investigation, plan, spec, or feature doc. Missing downstream consumer = silent regression.

Boundary	Grep terms
Event producers	Publish, Dispatch, Send, emit, EventBus, outbox, IntegrationEvent
Event consumers	Consumer, EventHandler, Subscribe, @EventListener, inbox
Sagas/orchestration	Saga, ProcessManager, Choreography, Workflow, Orchestrator
Sync service calls	HTTP/gRPC calls to/from other services
Shared contracts	OpenAPI spec, proto, shared DTO — flag breaking changes
Data ownership	Other service reads/writes same table/collection → Shared-DB anti-pattern

Per touchpoint: owner service · message name · consumers · risk (NONE / ADDITIVE / BREAKING).

BLOCKED until: Producers scanned · Consumers scanned · Sagas checked · Contracts reviewed · Breaking-change risk flagged

Systematic Review Batching (map-reduce) — When a changeset is large, do NOT review files one-by-one. Partition into size-capped batches, fire one specialized sub-agent per batch in parallel, then reduce. This bounds EVERY context — each batch agent AND the orchestrator — so coverage stays complete as file count grows.

Trigger ladder (one ordered escalation — not competing thresholds):

1. < 10 changed files → sequential per-file review (default; no batching).
2. ≥ 10 changed files → switch to systematic parallel mode. Announce: "Detected {N} changed files. Switching to systematic parallel review protocol." Then: categorize → size-capped batches → flat consolidation.
3. categories > 6 OR files > 40 → additionally insert the hierarchical synthesis tier (below). Everything from rung 2 still applies.

Step 1 — Categorize. Group changed files into logical categories derived from the project's actual structure (not forced). Category is the concern axis; orient with these examples, derive what fits the repository:

Category Type	Example Groupings
Agent/Tooling	AI scripts, hooks, skill definitions, workflow configs, linting rules
Root config/docs	Root README, project config, CI/CD pipeline configs
Reference docs	Architecture docs, patterns references, setup guides
Feature/domain docs	Business feature documentation, spec files, ADRs
Backend logic	Service/handler/controller source (infer from project structure)
Frontend logic	UI component/state/API source (infer from project structure)
Data/Schema	Migrations, schema files, seed data
Tests	Unit, integration, E2E test files
Infrastructure	Docker, k8s, CI/CD, cloud manifests

Step 2 — Size-capped batches. One sub-agent per batch of ≤8 files OR ≤2000 diff-lines, whichever hits first. Category stays the concern axis, but any category exceeding a cap splits into multiple size-capped batches (30 backend files → 4 batches). Size caps — not category caps — make "many files" safe: a category cap alone lets one giant category blow a single agent's context.

Step 2a — Sub-agent type per batch (match the batch's dominant concern):

• Code logic (any stack) → code-reviewer
• Security-sensitive changes → security-auditor
• Performance-critical paths → performance-optimizer
• Docs, plans, specs, configs, infra → general-purpose

Each batch sub-agent receives: its full file list; SYNC:category-review-thinking as its primary thinking model — derive each category's concerns from first principles, NOT a fixed checklist (if the consuming skill does not carry that block, apply category-first thinking directly); project reference docs relevant to its concern (discover via *patterns*, *conventions*, *style-guide*); cross-reference verification instructions (counts, tables, links). All batch agents run in parallel and write findings to plans/reports/ (per SYNC:task-tracking-external-report); reducers read from disk, never from memory.

Step 3 — Reduce.

• Flat reduction (rung 2, ≤6 categories AND ≤40 files): the orchestrator collects each batch report, cross-references counts/tables/contracts ACROSS batches, detects gaps visible only across categories (feature in code but missing from docs; new API endpoint with no client call), and consolidates into one categorized holistic report.
• Hierarchical reduction (rung 3, > 6 categories OR > 40 files): insert a mid-tier — each concern gets ONE synthesizer agent that reads only its own batch reports and emits a single concern-synthesis. The orchestrator reads the concern-syntheses (~5), never the raw batch reports — keeping the reducer's context O(#concerns), not O(#files).
  • Cross-concern interaction pass (mandatory at rung 3 — closes the synthesis-tier blind spot): concern-siloed synthesis can drop an interaction spanning two concerns AND two batches (tainted source in data-layer/batch 7 → sink in api/batch 3). So: (a) each concern-synthesizer MUST emit an explicit "cross-concern interaction candidates" list — entities/symbols/contracts it touched that plausibly bind to another concern (shared DTOs, event names, table/collection names, exported symbols); (b) the orchestrator MUST run the Step-3 cross-reference/gap step over those candidate lists across all concern-syntheses, not only within a batch, before concluding. Without this pass the tier trades completeness for context-bounding on exactly the large diffs it targets.

Step 4 — Holistic assessment. With all findings combined, judge: overall coherence as a unified intent; cross-category sync (docs match code? contracts match callers?); risk areas where categories interact; missing doc/spec updates for changed artifacts.

No silent truncation. If any cap forces sampling or a batch is dropped for budget, ANNOUNCE the dropped/sampled scope explicitly — bounded coverage must never read as complete coverage.

End-to-Start Debugger Trace — For non-trivial bugs, failed verification, regression fixes, behavior-changing code, or unclear code flow, start from the observed final state and walk backward before proposing a fix.

1. Frame 0: observed end state — Name the exact user-visible output, failing assertion, log line, persisted value, API response, rendered UI, or aggregate bucket. Record the reader/query/renderer that produced it with file:line evidence.
2. Walk backward one hop at a time — Trace final reader -> projection/cache/storage -> writer -> consumer/handler/job -> producer/caller -> original trigger. At every hop record: input, transformation, output, owner, and evidence.
3. Enumerate all feeder paths — Find every upstream producer/caller/event/job that can write into the final path, including retry, async, cache, background, and alternate UI/API paths. Mark each path verified, ruled out, or still unknown.
4. Build the hypothesis matrix — For each plausible cause, list evidence for, evidence against, how to reproduce/verify, blast radius, and status (primary, contributing, ruled out, latent). Do not fix until competing causes are explicitly resolved or bounded.
5. Choose the owning fix layer — Identify the invariant owner and the lowest shared point that protects all downstream consumers. A fix at the symptom site is rejected unless the symptom site owns the invariant.
6. Prove convergence forward — After choosing the fix, walk start -> end again and show how the corrected state reaches the observed final output. Map each root cause to a fix part and each fix part to a test/proof.

BLOCKED until: final state named · backward trace written · all feeder paths enumerated · hypothesis matrix completed · owning fix layer justified · forward convergence proof mapped to tests.

NEVER: Start at the first suspicious code path. Collapse multiple producers into one "flow". Treat duplicate symptoms as duplicate records without proving the read model. Skip ruled-out hypotheses.

Graph-Assisted Investigation — MANDATORY when .code-graph/graph.db exists.

HARD-GATE: MUST ATTENTION run at least ONE graph command on key files before concluding any investigation.

Pattern: Grep finds files → trace --direction both reveals full system flow → Grep verifies details

Task	Minimum Graph Action
Investigation/Scout	trace --direction both on 2-3 entry files
Fix/Debug	callers_of on buggy function + tests_for
Feature/Enhancement	connections on files to be modified
Code Review	tests_for on changed functions
Blast Radius	trace --direction downstream

CLI: python .claude/scripts/code_graph {command} --json. Use --node-mode file first (10-30x less noise), then --node-mode function for detail.

Category Review Thinking — A thinking framework for reviewing any category of changed files. NOT a fixed checklist — derive concerns from domain knowledge; the examples are starting points only. Your knowledge of the category exceeds any list here — trust it.

Step 1 — Understand the category's role. What is this category responsible for in the overall system? What invariants must it uphold? What are its consumer contracts (who depends on it, what do they expect)?

Step 2 — Read project conventions for this category. Search for reference docs, style guides, ADRs, or READMEs specific to this area. Grep 3+ existing similar files — extract naming conventions, structural patterns, shared base classes. If no docs exist, derive conventions empirically from existing code.

Step 3 — Derive concerns from first principles. Apply all that are relevant; expand beyond this list based on the actual category:

• Correctness: Does the logic match the intent? Trace happy path AND error path.
• Boundary contracts: Are interfaces/APIs/events/protocols honored? No implicit coupling introduced?
• Project conventions: Does new code follow the patterns found in Step 2? Evidence-confirmed, not assumed.
• Security: Auth enforced at every entry point? Input validated at boundaries? No secrets in the diff?
• Performance: Unbounded operations? N+1 patterns? Blocking calls in async context? Unindexed queries?
• Maintainability: DRY? Single responsibility? Complexity within reason? Names reveal intent?
• Test coverage: Are the changed paths covered by tests? Are existing tests still valid after the change?
• Documentation: Do related docs, specs, or READMEs reflect the changes?

Step 4 — Create sub-tasks and execute. For each identified concern: create a TaskCreate sub-task, work through it with file:line evidence, mark done. No findings without proof.

Illustrative concern examples by category type (not exhaustive — trust your knowledge beyond this):

• Server-side logic: handler/service structure conventions, validation layer placement, side-effect isolation, cross-service boundary enforcement, data-access layer separation, error propagation strategy
• Client-side logic: component lifecycle management, resource cleanup (subscriptions, listeners, timers), state management patterns, API integration layer separation, reactive stream composition
• Data/Schema: migration reversibility (rollback script), lock impact on table volume, backfill idempotency, index coverage for query patterns, deployment ordering
• Configuration: present in ALL environments? No secrets in diff? App fails fast if config missing (not silently null)? Documented in setup guide?
• Infrastructure: dev/prod parity? No hardcoded dev values (localhost, debug flags)? Pinned image/dependency versions? CI/CD secret requirements documented?
• Styles/Assets: follows project naming conventions? Uses design variables/tokens (no hardcoded magic values)? Correct scope (no global side effects from component styles)?
• Documentation: accurate? Links valid? Examples still match current code/behavior? Covers new scenarios?
• Tests: assertions verify specific outcomes (not just "no exception")? Idempotent (repeatable N times)? Covers edge cases, not just happy path?
• Security artifacts: all code paths reach the gate? Negative tests exist (unauthorized denied)? Both enforcement AND display control updated?
• Build/Tooling: rule changes apply consistently? No exceptions that silently swallow violations? Impact on CI runtime documented?

Sub-Agent Return Contract — When this skill spawns a sub-agent, the sub-agent MUST return ONLY this structure. Main agent reads only this summary — NEVER requests full sub-agent output inline.

## Sub-Agent Result: [skill-name]

Status: ✅ PASS | ⚠️ PARTIAL | ❌ FAIL
Confidence: [0-100]%

### Findings (Critical/High only — max 10 bullets)

- [severity] [file:line] [finding]

### Actions Taken

- [file changed] [what changed]

### Blockers (if any)

- [blocker description]

Full report: plans/reports/[skill-name]-[date]-[slug].md

Main agent reads Full report file ONLY when: (a) resolving a specific blocker, or (b) building a fix plan. Sub-agent writes full report incrementally (per SYNC:incremental-persistence) — not held in memory.

Context budget — the return payload is a SUMMARY, not a transcript: ≤10 finding bullets, no raw file contents / full diffs / verbatim logs inline, no re-pasted source. Everything beyond the summary lives in the Full report on disk. A sub-agent that would exceed the summary shape MUST write the detail to its report and return only the pointer — the orchestrator's context is the scarce resource the whole map-reduce protects.

Nested Task Expansion Contract — For workflow-step invocation, the [Workflow] ... row is only a parent container; the child skill still creates visible phase tasks.

1. Call TaskList first. If a matching active parent workflow row exists, set nested=true and record parentTaskId; otherwise run standalone.
2. Create one task per declared phase before phase work. When nested, prefix subjects [N.M] $skill-name — phase.
3. When nested, link the parent with TaskUpdate(parentTaskId, addBlockedBy: [childIds]).
4. Orchestrators must pre-expand a child skill's phase list and link the workflow row before invoking that child skill or sub-agent.
5. Mark exactly one child in_progress before work and completed immediately after evidence is written.
6. Complete the parent only after all child tasks are completed or explicitly cancelled with reason.

Blocked until: TaskList done, child phases created, parent linked when nested, first child marked in_progress.

Project Reference Docs Gate — Run after task-tracking bootstrap and before target/source file reads, grep, edits, or analysis. Project docs override generic framework assumptions.

1. Identify scope: file types, domain area, and operation.
2. Read docs/project-config.json first — the project's machine-readable map. It is the single source of truth for THIS repo (modules/paths, framework + search keywords, test/E2E/integration run-commands, design system, architecture rules, workflow patterns); ground exact paths, run-commands, and conventions on it before investigating, planning, or coding — never assume framework defaults (CLAUDE.md + reference docs are derived from it). If it — or the docs index, lessons.md, CLAUDE.md, AGENTS.md, or any required reference doc — is missing or stale, auto-run /project-init or the narrow route (/project-config, /docs-init, /scan-all, /scan --target=<key>, /claude-md-init) first; if Codex mirrors or AGENTS.md are stale, ask the user to run /sync-codex (never auto-run it).
3. Required docs by trigger: always docs/project-reference/lessons.md; doc lookup docs-index-reference.md; review code-review-rules.md; backend/CQRS/API backend-patterns-reference.md; domain/entity domain-entities-reference.md; frontend/UI frontend-patterns-reference.md; styles/design scss-styling-guide.md + design-system/design-system-canonical.md; integration tests integration-test-reference.md; E2E e2e-test-reference.md; feature docs/specs feature-spec-reference.md + spec-system-reference.md + spec-principles.md; behavior/public-contract/spec-test-code sync workflow-spec-test-code-cycle-reference.md; derived spec index/ERD/reimplementation guides spec-system-reference.md + source Feature Specs under docs/specs/; architecture/new area project-structure-reference.md.
4. Read every required doc, then before target work state: Reference docs read: ... | Not applicable: ....

Ready when: scope evaluated, docs/project-config.json consulted, required docs checked/read or setup route completed, lessons.md confirmed, citation emitted.

Task Tracking & External Report Persistence — Bootstrap this before execution; then run project-reference doc prefetch before target/source work.

1. Create a small task breakdown before target file reads, grep, edits, or analysis. On context loss, inspect the current task list first.
2. Mark one task in_progress before work and completed immediately after evidence; never batch transitions.
3. For plan/review work, create plans/reports/{skill}-{YYMMDD}-{HHmm}-{slug}.md before first finding.
4. Append findings after each file/section/decision and synthesize from the report file at the end.
5. Final output cites Full report: plans/reports/{filename}.

Blocked until: task breakdown exists, report path declared for plan/review work, first finding persisted before the next finding.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

Sequential Thinking Protocol — Structured multi-step reasoning for complex/ambiguous work. Use when planning, reviewing, debugging, or refining ideas where one-shot reasoning is unsafe.

Trigger when: complex problem decomposition · adaptive plans needing revision · analysis with course correction · unclear/emerging scope · multi-step solutions · hypothesis-driven debugging · cross-cutting trade-off evaluation.

Format (explicit mode — visible thought trail):

1. Thought N/M: [aspect] — one aspect per thought, state assumptions/uncertainty
2. Thought N/M [REVISION of Thought K]: ... — when prior reasoning invalidated; state Original / Why revised / Impact
3. Thought N/M [BRANCH A from Thought K]: ... — explore alternative; converge with decision rationale
4. Thought N/M [HYPOTHESIS]: ... then [VERIFICATION]: ... — test before acting
5. Thought N/N [FINAL] — only when verified, all critical aspects addressed, confidence >80%

Mandatory closers: Confidence % stated · Assumptions listed · Open questions surfaced · Next action concrete.

Stop conditions: confidence <80% on any critical decision → escalate via AskUserQuestion · ≥3 revisions on same thought → re-frame the problem · branch count >3 → split into sub-task.

Implicit mode: apply methodology internally without visible markers when adding markers would clutter the response (routine work where reasoning aids accuracy).

Deep-dive: see /sequential-thinking skill (.claude/skills/sequential-thinking/SKILL.md) for worked examples (API design, debugging, architecture), advanced techniques (spiral refinement, hypothesis testing, convergence), and meta-strategies (uncertainty handling, revision cascades).

Evidence-Based Reasoning — Speculation is FORBIDDEN. Every claim needs proof.

1. Cite file:line, grep results, or framework docs for EVERY claim
2. Declare confidence: >80% act freely, 60-80% verify first, <60% DO NOT recommend
3. Cross-service validation required for architectural changes
4. "I don't have enough evidence" is valid and expected output

BLOCKED until: - [ ] Evidence file path (file:line) - [ ] Grep search performed - [ ] 3+ similar patterns found - [ ] Confidence level stated

Forbidden without proof: "obviously", "I think", "should be", "probably", "this is because" If incomplete → output: "Insufficient evidence. Verified: [...]. Not verified: [...]."

Design Patterns Quality — Priority checks for every code change:

1. DRY via OOP: Identify classes/modules with the same purpose, naming pattern, or lifecycle. Apply your knowledge of the project's language/framework to determine the idiomatic abstraction (base class, mixin, trait, protocol, decorator). 3+ similar patterns → extract to shared abstraction.
2. Right Responsibility: Logic in LOWEST layer (Entity > Domain Service > Application Service > Controller). Never business logic in controllers.
3. SOLID: Single responsibility (one reason to change). Open-closed (extend, don't modify). Liskov (subtypes substitutable). Interface segregation (small interfaces). Dependency inversion (depend on abstractions).
4. After extraction/move/rename: Grep ENTIRE scope for dangling references. Zero tolerance.
5. YAGNI gate: NEVER recommend patterns unless 3+ occurrences exist. Don't extract for hypothetical future use.

Anti-patterns to flag: God Object, Copy-Paste inheritance, Circular Dependency, Leaky Abstraction.

Serial Attention for Design Quality — Scan one quality dimension at a time (serial passes), not all concerns at once. — why: split attention misses violations that single-focus passes catch.

1. Identify applicable dimensions — Based on the code's language, domain, and patterns, determine which quality dimensions apply: DRY, SOLID principles (SRP/OCP/LSP/ISP/DIP), OOP idioms, cohesion/coupling, GRASP, Law of Demeter, CQRS invariants, etc. Your list is NOT fixed — derive from what the code actually does.
2. One focused pass per dimension — Dedicate single-focus attention to EACH dimension in sequence. Do NOT mix concerns across passes.
3. Threshold: 3+ similar patterns = MANDATORY extraction — Not optional suggestion. Flag as mandatory structural fix requiring action.
4. 2+ violations of same kind = structural finding — Report as "pattern problem" needing architectural resolution, not a list of individual instances.

Complexity Prevention (Ousterhout) — MANDATORY. Measure code by cost of change: one business change should map to one code change. Flag ALL of the following in review:

1. Change amplification — small business change forces edits in >3 places → structural flaw. Count edit sites for a plausible future change (add variant, add field, add authorization). >3 = reject.
2. Cognitive load — reader must hold too much context to safely modify. Flag deep inheritance, long parameter lists, boolean traps, implicit ordering dependencies.
3. Cross-cutting duplication at entry points — logging, error handling, validation, auth, transactions reimplemented per controller/handler/route. Lift to middleware / interceptor / filter / decorator / aspect.
4. Leaked implementation technology — repos returning IQueryable/QuerySet/Criteria/raw cursors/ORM entities to callers. Return finished results + intent-revealing methods (GetActiveVipUsers() not Query()).
5. Type-switch scattering — switch/if-chains on enum/discriminator in >1 place. New variant = new file, not N edits. One factory/registry switch at the boundary OK; scattered switches = reject.
6. Anemic models — domain objects with only getters/setters, logic floats in services. Move invariants/behavior onto the object (order.Checkout(), not order.Status = ...).
7. Primitive obsession — raw string/int/decimal for account numbers, emails, money, percentages, date ranges, with re-validation at every entry. Wrap in value objects / records / structs that validate once at construction.
8. Inline cross-cutting concerns — authorization/tenant isolation/audit/sanitization hand-written at top of every handler. Flag intent with declarative markers (@RequirePermission("Order.Delete")), enforce once centrally.
9. Shallow modules — tiny class, big interface (many public methods, many flags, many ctor params) wrapping little logic. A module is deep when a small interface hides a lot of implementation. If interface ≈ implementation cost to learn → inline.
10. Missing base class for repeated component/handler lifecycle — 3+ forms/CRUD handlers/list views reimplementing loading/dirty/submit/pagination → extract to base class / hook / composable / mixin / trait.
11. Premature vs delayed abstraction — rule-of-three. First occurrence: write it. Second: notice duplication. Third: extract. Don't build generic frameworks before real variation; don't copy-paste for the 4th time.
12. Embedded utility logic not extracted to helpers — inline paging loops (while (hasMore) { skip += take; ... }), ad-hoc datetime math, string parsing/formatting, collection partitioning, retry/backoff loops, URL/query-string building. If the algorithm is non-trivial AND stack-generic (not business-specific), extract to util/helper/extensions and let consumers call one line. Inline duplicates → duplicated bug surface.
13. Logic in wrong (higher) layer — downshift to callee — business/derivation logic written in the caller when the callee owns the data. Defaults: Controller code that should be App Service. App Service code that should be Domain Service or Entity. Component code that should be ViewModel/Store/Service. Caller reaching into callee's data shape to compute something → move the computation behind an intent-revealing method on the callee. Lowest responsible layer wins (Entity > Domain Service > App Service > Controller · Model/VM > Store > Component). Higher-layer placement = duplicated logic when a sibling caller needs the same thing.
14. Owner owns the rule — extract on first write — if a caller inlines logic that derives, normalizes, validates, or computes from another type's data, MOVE it to the owning type. Single use is sufficient — the trigger is wrong responsibility, not duplication. Sibling callers always arrive; inline copies drift silently with no compile error and no name to grep. Common offenders: Backend — inlined rules in application-layer handlers / commands / queries / services / controllers that belong on the domain entity / value object / domain service. Frontend — inlined derivations / formatting / validation in components that belong on the model / store / view-model / API service. Fix: name the rule once as a method (static or instance) on the owning type; callers invoke by name. Future variant → SECOND named method on the owner, never an inline near-duplicate. Right responsibility first; reuse is the consequence.

Extraction target — where the named rule lives:

Shape of the rule	Goes to
Pure function over an entity's own data	static method on the entity
Behavior that mutates / guards entity state	instance method on the entity
Always-true invariant on a primitive value	value object constructor
Needs DI (repo / settings / clock)	helper class registered in DI
Domain-agnostic algorithm reused across types	util / extension method
Pure shape / projection conversion	DTO mapping

Pre-commit edit-site test (reject if answer is "many"):

Change Scenario	Should touch
Add new variant (customer type, payment method)	1 new file
Change HTTP error response format	1 middleware/filter
Add timestamp field to every persisted entity	1 base entity/interceptor
Add authorization to a new endpoint	1 declarative marker
Swap database/ORM	Data layer only
Change business calculation rule	1 method on owning entity
Add loading indicator pattern to forms	1 base component/hook
Add validation rule to a domain primitive	1 value-object ctor
Change paging/retry/datetime algorithm	1 helper/util function
Change a derivation of entity data	1 method on the entity

Operating heuristics:

• Write the call site first.
• Count edit sites for plausible future change.
• Prefer removing code over adding it.
• Surface assumptions at boundaries, hide details inside.
• Pre-reuse scan — before writing a non-trivial block, grep for similar algorithms (while.*skip, DateTime.*Add, split/join chains, paging loops, retry loops). Match existing helper → call it. None exists but pattern is stack-generic → extract to util before second caller appears.
• Layer placement test — ask "if a sibling caller needed this tomorrow, would they re-derive it?" If yes, the logic is in the wrong layer. Move it down.
• Open-case-for-future-reuse — if reviewer spots a block that is likely to appear in another feature (domain-agnostic algorithm, shared lifecycle, recurring derivation), do NOT rationalize with pure YAGNI. Either extract now (if cheap) or create a tracked TODO with the exact extraction target so the second caller does not duplicate silently. Silent duplication is the default failure mode.
• When in doubt ask: "What would need to change if the requirement shifts?"

The measure of good code is the cost of change. Not shortest. Not cleverest. Not most abstracted. Cheapest to safely modify having read a small local portion.

Validated-Finding Fix + Full Re-Review Loop — Re-review is triggered by a validated finding fix cycle, not by a round number. Review purpose: review → validate findings → fix validated findings → full re-review until a complete review pass finds no issues. A clean review ENDS the loop — no further rounds required.

aka Self-Review Convergence Loop. The name is historical — there is NO 2-round cap; "double-round-trip" only means a validated-finding fix cycle forces at least one fresh re-review. It runs until a clean pass, bounded by the 5-round ceiling below.

Round cap — 5 rounds MAX (a ceiling, NEVER a target). A clean pass ENDS the loop immediately at ANY round — round 1 included; the cap never obliges you to keep spinning. Hitting round 5 with validated findings still open → STOP and escalate via AskUserQuestion with the still-open findings listed; NEVER emit a silent "good enough" PASS on cap exhaustion, and NEVER let the cap substitute for the clean-review requirement. The 3-repeated-no-progress blocker rule stays an EARLIER exit — escalate at whichever trips first.

Universal scope (any new output/judgment): any newly produced output or judgment gets ≥1 self-review; any new judgment gets ≥1 /why-review --validate-findings pass; anything flagged to re-check is re-checked ≥1 time — before that output is treated as final. This loop is the default convergence contract for ANY work-producing skill, not review skills only.

Routing invariant (author-facing): a skill that validates findings MUST route them through /why-review --validate-findings (the terminal validator) — NEVER fork an inline finding-validation. Routing through why-review is what makes the finding-survival bar and this loop apply; the verify-review-validate-coverage sensor enforces this exact route mechanically.

Round 1: Main-session review. Read target files, build understanding, note issues. Output findings + verdict (PASS / FAIL).

Decision after Round 1:

• No issues found (PASS, zero findings) → review ENDS. Do NOT spawn a fresh sub-agent for confirmation.
• Issues found (FAIL, or any non-zero findings) → run the active review skill's findings-validation gate first; for review skills the default gate is /why-review --validate-findings <report-path>. Fix only validated findings, then restart the full review protocol from the beginning with a fresh task breakdown.

Fresh full re-review after every fix cycle: Re-run the whole review protocol over the current full target. When sub-agents are part of that protocol, spawn NEW Agent calls — never reuse prior agents. Reviewers re-read ALL files from scratch with ZERO memory of prior rounds. See SYNC:fresh-context-review for the spawn mechanism and SYNC:review-protocol-injection for the canonical Agent prompt template. Each fresh full review must catch:

• Cross-cutting concerns missed in the prior round
• Interaction bugs between changed files
• Convention drift (new code vs existing patterns)
• Missing pieces that should exist but don't
• Subtle edge cases the prior round rationalized away
• Regressions introduced by the fixes themselves

Loop termination: After each full re-review, repeat the same decision: clean → END; issues → validate findings → fix → restart from the first review phase. Continue until a complete review pass finds zero issues, capped at 5 rounds. Escalate via AskUserQuestion at whichever comes first: the same validated finding repeats for 3 full invocations with no progress · a fix requires product/owner input · round 5 completes with validated findings still open. NEVER loop past 5 rounds, and NEVER convert cap exhaustion into a PASS.

Rules:

• A clean Round 1 ENDS the review — no mandatory Round 2
• NEVER fix unvalidated findings; validate first using the caller's validation gate
• Every surviving finding must additionally clear the finding-survival bar defined in why-review's Findings Validation Routine (a deliberately higher bar than the generic act-gate — "keep this finding?" is a stricter question than "act on this evidence?"); a finding below the bar is demoted or dropped, not kept
• NEVER skip the full re-review after a fix cycle (every fix invalidates the prior verdict)
• NEVER reuse a sub-agent across rounds — every iteration that uses sub-agents spawns NEW Agent calls
• Main agent READS sub-agent reports but MUST NOT filter, reinterpret, or override findings
• The 5-round cap NEVER replaces the clean-review requirement — it bounds runaway looping, it does not authorize shipping an un-clean review; a clean pass ends the loop early at any round, and cap exhaustion escalates rather than passes
• Enforce the round cap of 5 alongside the 3 repeated-no-progress blocker rule; both are escalation triggers, neither is a completion criterion
• Track recursive invocation count and repeated blockers in conversation context (session-scoped)
• Final verdict must incorporate ALL rounds executed

Report must include ## Round N Findings (Fresh Sub-Agent) for every round N≥2 that was executed.

Fresh Context Re-Review — Eliminate orchestrator confirmation bias after fixes by restarting the full review with isolated sub-agents where applicable.

Why: The main agent knows what it (or /feature-implement) just fixed and rationalizes findings accordingly. A fresh sub-agent has ZERO memory, re-reads from scratch, and catches what the main agent dismissed. Sub-agent bias is mitigated by (1) fresh context, (2) verbatim protocol injection, (3) main agent not filtering the report.

When: ONLY after a validated-finding fix cycle. A review round that finds zero issues ENDS the loop — do NOT spawn a confirmation sub-agent. A review round that finds issues triggers: validate findings → fix → full review restart from the first phase.

How:

1. Start a NEW full review invocation/task breakdown; when that protocol calls for agents, spawn NEW Agent tool calls — use code-reviewer subagent_type for code reviews, general-purpose for plan/doc/artifact reviews
2. Inject ALL required review protocols VERBATIM into the prompt — see SYNC:review-protocol-injection for the full list and template. Never reference protocols by file path; AI compliance drops behind file-read indirection (see SYNC:shared-protocol-duplication-policy)
3. Sub-agent re-reads ALL target files from scratch via its own tool calls — never pass file contents inline in the prompt
4. Sub-agent writes structured report to plans/reports/{review-type}-round{N}-{date}.md
5. Main agent reads the report, integrates findings into its own report, DOES NOT override or filter

Rules:

• SKIP fresh sub-agent when the prior full review found zero issues (no fixes = nothing new to verify)
• NEVER skip the full review restart after a fix cycle — every fix invalidates the prior verdict
• NEVER reuse a sub-agent across rounds — every fresh round spawns a NEW Agent call
• Continue until a complete full review pass has zero findings; if the same blocker repeats 3 times with no progress, escalate via AskUserQuestion
• Track iteration count and repeated blockers in conversation context (session-scoped, no persistent files)

Review Protocol Injection — Every fresh sub-agent review prompt MUST embed 11 protocol blocks VERBATIM. The template below has ALL 11 bodies already expanded inline. Copy the template wholesale into the Agent call's prompt field at runtime, replacing only the {placeholders} in Task / Round / Reference Docs / Target Files / Output sections with context-specific values. Do NOT touch the embedded protocol sections.

Why inline expansion: Placeholder markers would force file-read indirection at runtime. AI compliance drops significantly behind indirection (see SYNC:shared-protocol-duplication-policy). Therefore the template carries all 11 protocol bodies pre-embedded.

Subagent Type Selection

• code-reviewer — for code reviews (reviewing source files, git diffs, implementation)
• general-purpose — for plan / doc / artifact reviews (reviewing markdown plans, docs, specs)

Canonical Agent Call Template (Copy Verbatim)

Agent({
  description: "Fresh Round {N} review",
  subagent_type: "code-reviewer",
  prompt: `
## Task
{review-specific task — e.g., "Review all uncommitted changes for code quality" | "Review plan files under {plan-dir}" | "Review integration tests in {path}"}

## Round
Round {N}. You have ZERO memory of prior rounds. Re-read all target files from scratch via your own tool calls. Do NOT trust anything from the main agent beyond this prompt.

## Protocols (follow VERBATIM — these are non-negotiable)

### Spec ↔ Tests ↔ Code Triangulation
DO THIS FIRST — before any per-protocol check below. The review target is the WHOLE PACKAGE, not the diff alone: load the behavior's spec (§3 ACs / §4 BRs / §8 TCs), its tests, and the changed code TOGETHER, and reason about their mutual consistency BEFORE judging any one in isolation.
1. Locate all three faces: the Feature Spec section(s) governing the changed behavior, the tests that guard it, and the production code that implements it. A missing face is itself a finding (SPEC-GAP / TEST-GAP / DEAD-SPEC).
2. Triangulate pairwise — every disagreement is a finding; classify which face is wrong:
   - code vs spec: behavior the code does that no §3/§4/§8 rule describes → CODE-EXTRA or SPEC-STALE; a [HARD] §4 rule or §5 invariant with no enforcing code path → CODE-WRONG.
   - tests vs spec: a §8 TC with no test, or a test asserting behavior no TC/rule names → TEST-GAP or SPEC-SILENT.
   - tests vs code: a changed code path with no covering test → TEST-GAP; a test that still passes against a deliberately broken invariant → WEAK-TEST (apply the mutation thinking in Bug Detection).
3. Hidden-rule capture: any invariant the code enforces but the spec never states (SPEC-SILENT) MUST be surfaced as a finding to add into §3/§4/§8 AND guarded with a test — the enrichment loop, never a silent pass.
4. Only after the three faces agree — or every disagreement is logged as a finding — proceed to the per-protocol checks below; when enrichment adds spec/test content, re-review the package against the enriched spec.
NEVER mark review PASS while any spec/test/code face disagrees without a logged finding. The diff is the entry point; the package is the unit of judgment.

### Evidence-Based Reasoning
Speculation is FORBIDDEN. Every claim needs proof.
1. Cite file:line, grep results, or framework docs for EVERY claim
2. Declare confidence: >80% act freely, 60-80% verify first, <60% DO NOT recommend
3. Cross-service validation required for architectural changes
4. "I don't have enough evidence" is valid and expected output
BLOCKED until: Evidence file path (file:line) provided; Grep search performed; 3+ similar patterns found; Confidence level stated.
Forbidden without proof: "obviously", "I think", "should be", "probably", "this is because".
If incomplete → output: "Insufficient evidence. Verified: [...]. Not verified: [...]."

### Bug Detection
MUST check categories 1-4 for EVERY review. Never skip.
1. Null Safety: Can params/returns be null? Are they guarded? Optional chaining gaps? .find() returns checked?
2. Boundary Conditions: Off-by-one (< vs <=)? Empty collections handled? Zero/negative values? Max limits?