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SKILL.md

name architecture-review
description Perform comprehensive architectural assessments of codebases. Use when asked about: architecture review, system design review, assess the architecture, review the codebase structure, architectural assessment, tech debt assessment, how is this system designed, evaluate the architecture, review project structure.

Architecture Review Skill

Comprehensive architectural assessment for C# and Python codebases, analyzing system design, resilience patterns, observability, API design, and infrastructure concerns.

Role in Architecture Workflow

┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│ architecture-   │     │ software-       │     │ code-review     │
│ review skill    │ ──► │ architect agent │ ──► │ skill           │
│ (What exists?)  │     │ (What to build?)│     │ (Is it right?)  │
└─────────────────┘     └─────────────────┘     └─────────────────┘
     ASSESS                  DESIGN                 IMPLEMENT
       ▲                                                │
       └────────────────────────────────────────────────┘
                    (Continuous improvement)

This skill is the ASSESS phase. It evaluates existing architecture and produces findings that feed into design decisions.

When to Use This Skill

Situation Use Architecture Review
Starting on new codebase Understand before changing
Planning major refactoring Assess current state, plan target state
Periodic health check Quarterly/bi-annual assessment
Performance/scaling concerns Identify bottlenecks and design issues
Tech debt prioritization Catalog and prioritize improvements
Onboarding Generate architectural documentation

Not for: Individual PR reviews, single-file changes, quick code checks. Use code-review skill instead. Not for: Designing new systems or features. Use software-architect agent instead.

Assessment Modes

Quick Assessment (~15 min)

Fast health check focusing on critical concerns:

  • Project structure and layering
  • Obvious anti-patterns
  • Security red flags
  • Missing resilience patterns
"Give me a quick architectural health check of this codebase"

Full Assessment (~45-60 min)

Comprehensive review of all categories:

  • Complete checklist evaluation
  • All reference patterns applied
  • Detailed findings with recommendations
  • Work items for P1/P2 issues
"Perform a full architectural assessment of this system"

Focused Assessment

Deep dive into specific concern:

  • Single category analysis
  • Detailed pattern matching
  • Specific recommendations
"Assess the resilience patterns in this codebase"
"Evaluate the observability setup"
"Review the API design architecture"

Quick Start

# Full architectural assessment
# "Review the architecture of this codebase"

# Focused assessment
# "Assess the resilience patterns in this system"
# "Review the API design"
# "Evaluate the observability setup"

# Comparative
# "How well does this follow Clean Architecture?"
# "Does this codebase follow DDD patterns?"

Review Process

1. Define Scope

Before starting, clarify:

  • Subsystem: Entire codebase, specific service, or layer?
  • Quality Attributes: What matters most? (scalability, reliability, security, maintainability)
  • Deployment Model: Monolith, microservices, serverless?
  • Constraints: Team size, timeline, existing tech debt?

2. Codebase Exploration

Systematically explore:

# Project structure
ls -la
find . -name "*.csproj" -o -name "*.sln" -o -name "pyproject.toml" -o -name "setup.py"

# Dependencies
cat *.csproj | grep PackageReference  # .NET
cat requirements.txt pyproject.toml    # Python

# Entry points
find . -name "Program.cs" -o -name "Startup.cs" -o -name "main.py" -o -name "app.py"

# Configuration
find . -name "appsettings*.json" -o -name "*.env*" -o -name "config*.py"

3. Apply Assessment Framework

Use the checklist: checklists/architecture-checklist.md

Reference documents:

  • references/architecture-patterns.md - Core patterns (language-agnostic)
  • references/dotnet-architecture.md - .NET specific patterns
  • references/python-architecture.md - Python specific patterns

4. Assessment Categories

Category What to Assess
Structure Project organization, layering, dependency direction
Domain Design Bounded contexts, aggregates, domain events
Resilience Retry policies, circuit breakers, health checks, fallbacks
Observability Logging infrastructure, metrics, distributed tracing
API Design REST conventions, versioning, error responses
Configuration Secrets management, environment handling, validation
Data Access Repository patterns, connection management, migrations
Security AuthN/AuthZ architecture, secrets, CORS, TLS
Testing Test architecture, coverage strategy, test isolation
Infrastructure Deployment, containerization, CI/CD

5. Classify Findings

Priority Meaning Action
P1 - Critical Security risk, data integrity, system stability Immediate attention
P2 - High Significant tech debt, scalability blocker Plan for next sprint
P3 - Medium Maintainability issue, missing best practice Add to backlog
P4 - Low Minor improvement, optimization opportunity Consider when touching

6. Create Work Items

For P1 and P2 findings, create tech debt or feature work items:

# Check platform first
python3 skills/detect-platform.py

# Create tech debt item
az boards work-item create --org "$ORG" --project "$PROJECT" \
  --type "Feature" --title "Architecture: [Finding Title]" \
  --description "<h2>Current State</h2><p>...</p><h2>Target State</h2><p>...</p><h2>Effort</h2><p>...</p>"

Assessment Output Format

# Architecture Assessment: [Project Name]

**Date**: YYYY-MM-DD
**Scope**: [What was reviewed]
**Quality Focus**: [Scalability | Reliability | Security | Maintainability]

## Executive Summary

[2-3 paragraph overview: current state, key strengths, primary concerns, recommendations]

## Architecture Overview

### Current Structure
[Describe the current architecture - layers, components, data flow]

### Technology Stack
| Layer | Technology |
|-------|------------|
| Presentation | ... |
| Application | ... |
| Domain | ... |
| Infrastructure | ... |
| Data | ... |

## Assessment by Category

### 1. Project Structure
**Rating**: [Strong | Adequate | Needs Improvement | Critical]

**Observations**:
- [What exists]

**Findings**:
#### [P2] Finding Title
**Current**: Description of current state
**Impact**: Why this matters
**Recommendation**: What to change
**Effort**: [S/M/L/XL]

### 2. Resilience Patterns
[Same format...]

### 3. Observability
[Same format...]

[Continue for each category...]

## Strengths
- [What's done well - reinforce good decisions]

## Priority Findings Summary

| Priority | Count | Categories |
|----------|-------|------------|
| P1 Critical | X | ... |
| P2 High | X | ... |
| P3 Medium | X | ... |
| P4 Low | X | ... |

## Recommended Roadmap

### Immediate (This Sprint)
- [ ] P1 items...

### Short-term (Next 2-4 Sprints)
- [ ] P2 items...

### Medium-term (Quarter)
- [ ] P3 items...

## Work Items Created
- AB#XXX: [Title]
- AB#XXX: [Title]

Pattern Reference

Core Patterns (Language-Agnostic)

Clean Architecture

  • Dependencies point inward
  • Domain has no external dependencies
  • Use cases orchestrate domain
  • Infrastructure implements interfaces

Domain-Driven Design

  • Bounded contexts with clear boundaries
  • Aggregates for consistency boundaries
  • Domain events for cross-aggregate communication
  • Repository pattern for persistence abstraction

CQRS (Command Query Responsibility Segregation)

  • Separate read and write models
  • Optimized query paths
  • Event sourcing for audit/replay (optional)

.NET Architecture Assessment

Focus areas:

  • Dependency Injection: IServiceCollection setup, lifetimes, composition root
  • Configuration: IOptions pattern, secrets management, environment handling
  • Resilience: Polly policies, IHttpClientFactory, health checks
  • Observability: Serilog/ILogger setup, OpenTelemetry, correlation IDs
  • API Design: Controller patterns, model validation, Problem Details
  • EF Core: DbContext lifetime, migrations, repository abstraction

Python Architecture Assessment

Focus areas:

  • Project Structure: src layout, packaging, dependency management
  • Dependency Injection: Manual DI, dependency-injector, FastAPI Depends
  • Configuration: Pydantic Settings, environment variables, secrets
  • Resilience: tenacity, circuit breakers, health endpoints
  • Observability: structlog, OpenTelemetry, Prometheus metrics
  • API Design: FastAPI/Flask patterns, Pydantic models, error handling
  • Data Access: SQLAlchemy patterns, Alembic migrations, session management

Anti-Patterns to Identify

Structural Anti-Patterns

  • Big Ball of Mud: No clear structure, everything depends on everything
  • Distributed Monolith: Microservices with tight coupling
  • Anemic Domain Model: Logic in services, entities are just data bags
  • God Class: Single class doing too much

Resilience Anti-Patterns

  • No Timeouts: External calls without timeout configuration
  • Retry Storm: Aggressive retries without backoff
  • No Circuit Breaker: Cascading failures from downstream issues
  • Missing Health Checks: No way to know if service is healthy

Observability Anti-Patterns

  • Log and Forget: Logging without correlation or structure
  • Alert Fatigue: Too many alerts, important ones ignored
  • No Metrics: Flying blind on performance and usage
  • PII in Logs: Sensitive data exposed in log files

Configuration Anti-Patterns

  • Secrets in Code: Credentials committed to repository
  • Environment Blindness: Same config for all environments
  • No Validation: Invalid config causes runtime errors
  • God Config: Single config file with everything

Remediation Workflow

After completing an assessment, guide remediation based on finding priority:

P1 Critical Findings

Immediate action required:

  1. Document the risk: Create urgent work item with full context
  2. Design fix: Engage software-architect agent for remediation design
  3. Implement: Apply fix with expedited code review
  4. Verify: Re-assess the specific area
"I found a P1 security issue. Let me engage the software-architect agent to design the remediation."

P2 High Findings

Plan for next sprint:

  1. Create ADR: If architectural change, use software-architect agent to create ADR
  2. Create work items: Break down into implementable tasks
  3. Prioritize: Stack rank against other tech debt
"For this P2 finding about missing circuit breakers, let me create an ADR using the software-architect agent."

P3/P4 Findings

Backlog management:

  1. Document in assessment report: Include in recommendations
  2. Create backlog items: Track for future sprints
  3. Address opportunistically: Fix when touching related code

Remediation Design Handoff

When findings require architectural changes, hand off to software-architect agent:

## Remediation Request for software-architect

### Finding
[P-level] [Title from assessment]

### Current State
[Description of existing architecture]

### Impact
[Why this matters - from assessment]

### Constraints
- [Constraint 1: e.g., "Cannot change database schema"]
- [Constraint 2: e.g., "Must maintain backward compatibility"]

### Request
Design a solution that addresses this finding while respecting the constraints.
Include ADR if this is a significant architectural change.

Integration with Other Skills

software-architect Agent (Design Phase)

After assessment, use the agent to:

  • Design remediation for P1/P2 findings
  • Create ADRs for architectural changes
  • Plan migration strategies
  • Evaluate technology alternatives
"Use the software-architect agent to design a solution for the resilience gaps identified in the assessment"

code-review Skill (Implementation Phase)

Architecture review identifies systemic issues; code review handles specific implementations:

  • Architecture review finds: "No retry policy for external calls"
  • Code review catches: "This specific HTTP call needs retry"

docgen Skill (Documentation)

Use docgen skill to generate architecture documentation after assessment:

  • System context diagrams
  • Component diagrams
  • Decision records (ADRs)

azure-devops / github Skills (Work Tracking)

Create and track work items:

  • Create epics for major architectural changes
  • Create features for improvement initiatives
  • Track tech debt items
  • Link findings to work items

Files Reference

File Purpose
SKILL.md This file - skill documentation
references/architecture-patterns.md Core patterns (Clean Architecture, DDD, CQRS)
references/dotnet-architecture.md .NET specific architectural patterns
references/python-architecture.md Python specific architectural patterns
checklists/architecture-checklist.md Quick assessment checklist