Anyul Rivas

Calculate architecture quantum and detect distributed monolith risks by analyzing synchronous service dependencies, shared databases, and IaC. Use when reviewing cross-service calls, shared schemas, or independent deployability concerns.

Evaluate codebases against architectural fitness functions, governance files, and dependency rules to prevent architectural drift. Use when enforcing layering, cyclic dependency, or static metric thresholds in CI/CD or pre-commit checks.

Generate and maintain a living software guidebook by scanning repository code, infrastructure, deployment files, and docs. Use when periodic documentation updates are needed, especially after IaC, deployment script, or major release changes.

Analyze structural complexity, code churn, and static connascence to identify high-risk hotspots. Use when auditing complexity thresholds, refactoring candidates, or CI gating for code health.

Analyze monolithic codebases to identify extraction candidates, shared-kernel entanglement, and tactical forking effort. Use when planning modernization or breaking a monolith into independently deployable domains.

Evaluate ORM configurations, schema changes, and data access layers for shared-table coupling, ORM leakage, and distributed data joins. Use when reviewing schema migrations, repository classes, or modernization work toward decoupled data ownership.

Audit repositories for major technology additions and verify that corresponding ADR or decision-log entries exist. Use when reviewing dependency manifest changes, architecture shifts, or code reviews that may introduce new frameworks, databases, or libraries without documentation.

Map inter-service communication, distributed workflows, Saga patterns, and operational coupling across services. Use when reviewing REST, gRPC, brokers, distributed transactions, or temporal coupling risks.

Enforce DDD bounded contexts, ubiquitous language, anti-corruption layers, and shared-kernel safety. Use when reviewing cross-domain communication, shared libraries, DTO mappings, or domain model leakage.

Analyze asynchronous code, state machines, and temporal dependencies to detect dynamic connascence, race conditions, and fragile execution order requirements. Use when reviewing async workflows, multithreaded code, event handlers, or mutable state.

Evaluate event-driven architectures for payload design, consumer autonomy, broker entanglement, and synchronous callback anti-patterns. Use when reviewing schemas, publishers, consumers, or broker configurations.

Analyze method signatures, shared state, and cross-module interactions for content, common, control, and stamp coupling. Use when reviewing public interfaces, shared state variables, or module boundaries.

Enforce architectural boundaries between platform concerns and stream-aligned business logic. Use when reviewing core domain code for infrastructure bleed, cloud SDK leakage, or excessive deployment/configuration overhead.

Evaluate package- and module-level coupling, instability, abstractness, and distance from the main sequence. Use when monitoring architectural health, refactoring dependency structure, or enforcing coupling thresholds in CI.

Infer Team Topologies signals from repository structure, dependencies, churn, and ownership clues. Use when assessing stream-aligned, platform, complicated-subsystem, or enabling boundaries, cognitive load hotspots, Conway's Law, or boundary friction from code alone.

Evaluate test suite architecture for brittle coupling to implementation details, shared state, and poor seam alignment. Use when reviewing tests, mocking strategies, or integration test isolation.