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.NET/C# Design Pattern Review · github | DecimalAI

Dotnet Design Pattern Review

SkillScore41Maintained

dotnet-design-pattern-review

Review the C#/.NET code for design pattern implementation and suggest improvements.

Code Reviewby github

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

Coding pack

1 · One-time — install the CLI (docs ↗)

pip install decimalai

2 · Get the skill — writes .claude/skills/dotnet-design-pattern-review/SKILL.md

decimalai skills pull dotnet-design-pattern-review --out .claude/skills/

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/dotnet-design-pattern-review/SKILL.md https://app.decimal.ai/s/dotnet-design-pattern-review/SKILL.md

Raw file: /s/dotnet-design-pattern-review/SKILL.md ↗ · machine-readable summary at /s/dotnet-design-pattern-review.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

22 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 57d ago

Yes — +41% lift+18% tokens0% turns41% of whole cases pass with skill (9/22)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-01	✗→✓	▲ Improved	—	—
case-06	✗→✓	▲ Improved	—	—
case-09	✗→✓	▲ Improved	—	—
case-05	✗→✓	▲ Improved	—	—
case-11	✗→✓	▲ Improved	—	—

Showing 5 of 22 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 7/30/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

github / awesome-copilot

skills/dotnet-design-pattern-review/SKILL.md

View on GitHub ↗

License MITImported 7/31/2026Version v1

Skill contents

SKILL.md

.NET/C# Design Pattern Review

Review the C#/.NET code in ${selection} for design pattern implementation and suggest improvements for the solution/project. Do not make any changes to the code, just provide a review.

Required Design Patterns

Command Pattern: Generic base classes (CommandHandler<TOptions>), ICommandHandler<TOptions> interface, CommandHandlerOptions inheritance, static SetupCommand(IHost host) methods
Factory Pattern: Complex object creation service provider integration
Dependency Injection: Primary constructor syntax, ArgumentNullException null checks, interface abstractions, proper service lifetimes
Repository Pattern: Async data access interfaces provider abstractions for connections
Provider Pattern: External service abstractions (database, AI), clear contracts, configuration handling
Resource Pattern: ResourceManager for localized messages, separate .resx files (LogMessages, ErrorMessages)

Review Checklist

Design Patterns: Identify patterns used. Are Command Handler, Factory, Provider, and Repository patterns correctly implemented? Missing beneficial patterns?
Architecture: Follow namespace conventions ({Core|Console|App|Service}.{Feature})? Proper separation between Core/Console projects? Modular and readable?
.NET Best Practices: Primary constructors, async/await with Task returns, ResourceManager usage, structured logging, strongly-typed configuration?
GoF Patterns: Command, Factory, Template Method, Strategy patterns correctly implemented?
SOLID Principles: Single Responsibility, Open/Closed, Liskov Substitution, Interface Segregation, Dependency Inversion violations?
Performance: Proper async/await, resource disposal, ConfigureAwait(false), parallel processing opportunities?
Maintainability: Clear separation of concerns, consistent error handling, proper configuration usage?
Testability: Dependencies abstracted via interfaces, mockable components, async testability, AAA pattern compatibility?
Security: Input validation, secure credential handling, parameterized queries, safe exception handling?
Documentation: XML docs for public APIs, parameter/return descriptions, resource file organization?
Code Clarity: Meaningful names reflecting domain concepts, clear intent through patterns, self-explanatory structure?
Clean Code: Consistent style, appropriate method/class size, minimal complexity, eliminated duplication?

Improvement Focus Areas

Command Handlers: Validation in base class, consistent error handling, proper resource management
Factories: Dependency configuration, service provider integration, disposal patterns
Providers: Connection management, async patterns, exception handling and logging
Configuration: Data annotations, validation attributes, secure sensitive value handling
AI/ML Integration: Semantic Kernel patterns, structured output handling, model configuration

Provide specific, actionable recommendations for improvements aligned with the project's architecture and .NET best practices.

Illustrative Want to see what dotnet-design-pattern-review would put in front of your model? Preview the rendered body and check its trigger phrases — no LLM call, no signup.

Latest benchmark · publisher runVerified

7/26/2026, 06:50 UTC · 22 cases

Lift

+41%

41% vs 0%

Agent turns

0%

1.0 vs 1.0

Tokens

+18%

3,033.73 vs 2,573.59

fail → pass · 9fail → fail · 13

Per-case results (22)

Case	Status	Duration (ms)			Turns			Tokens			Tool calls
Case	Status	Without	With	Δ	Without	With	Δ	Without	With	Δ	Without	With	Δ
case-01 Could you inspect my selected C# codebase and perform an architectural and design pattern review? I'm looking for feedback on whether our implementation of standard patterns like repositories, factories, and command handlers follows current .NET best practices, alongside recommendations for SOLID adherence and testability. Please provide actionable suggestions without modifying the code itself.	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-14 Our repository interface contains 45 methods including Read, Write, Export, Purge, and Stream. Classes that only need to read data are forced to throw NotImplementedException for write methods. What design principles are violated and how should this be identified?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-17 In our domain logic classes, DateTime.Now and File.ReadAllText are called directly, making unit tests flaky and dependent on system clock and disk state. How should testability be evaluated?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-06 In our Console app layer (Console.OrderImport), command bootstrapping is handled via inline static main methods scattered across files. How should CLI command setup be structured in our review checklist?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-09 Our app logs hardcoded English strings directly inside catch blocks, e.g., logger.LogError("Failed to reach database"). How should string resources and error messages be organized according to resource management best practices?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-04 Create a GitHub Actions YAML workflow pipeline to build, test, and publish our .NET 8 Web API solution.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-05 Review our order export feature in OrderExporter.cs where command logic is structured using raw MediatR IRequest handlers with direct string arguments. We are considering whether to switch to a custom command framework. What specific structural elements should we evaluate?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-11 Our PDF generation component uses 'new PdfDocumentGenerator()' inside a loop whenever complex documents are created. How should complex object creation be refactored and reviewed in .NET?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-22 In our error handlers, string formatting is used for logging like logger.LogInformation($"User {userId} logged in at {DateTime.UtcNow}"). What logging best practice should be recommended?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-15 In our SQL data access layer, developers construct queries using string interpolation like $"SELECT * FROM Users WHERE Email = '{userInput}'". What security criteria must our code review flag?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-12 Our repository methods use '.Result' and '.Wait()' on async tasks when querying EF Core databases. What performance and async execution rules should our code review enforce?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-18 Our team public API methods in Core.Catalog have no method documentation or parameter descriptions. What documentation standards should be checked during the design pattern review?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-19 Two service classes contain 80 lines of identical calculation and formatting logic duplicated across projects. How should this be evaluated under clean code standards?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-03 Write a complete xUnit unit test suite with Moq for our UserManagementRepository in the Core library. Generate the test project file and test method code.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-08 We have a monolithic namespace structure where everything is named 'Company.Project.Helpers' or 'Company.Project.Utils'. What namespace naming convention and project boundary structure should our review enforce for domain features?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-21 Our app settings are loaded by reading raw strings from IConfiguration["ApiKeys:ServiceKey"] with no runtime schema validation or typing. How should configuration handling be improved?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-20 Our Core library directly instantiates SqlConnection and executes SqlCommand objects in controller actions. What pattern should abstract this data access?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-13 We are building an LLM integration feature in Service.Assistants using custom HTTP calls to Azure OpenAI endpoints. What specialized .NET patterns and framework integrations should we check for AI features?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-02 Here is a buggy C# OrderService class from our billing app: public class OrderService { public void Process() { } }. Please refactor this C# code directly and provide the modified C# source code file.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-07 In our Service.Billing project, developers are using traditional private field assignments in public constructors without null validation, like 'public BillingService(IPaymentGateway g) { _g = g; }'. What modern C# and DI best practices should we enforce in code review?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-16 We noticed input validation logic is duplicated across every individual command execution method in our app. Where should common validation and error handling be centralized?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-10 We are connecting to external OpenAI services and SQL Server directly from business logic services without abstractions. How should external service integrations be structured under proper architectural patterns?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—

These cases were also screened by the skill’s intent / safety pass.See the Trust review ↗Reproduce this benchmark in Colab ↗

How this skill was measured

DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +41 percentage points is the difference between those two pass rates over the 22 comparable cases.

Model measured: gemini-3.6-flash
Graded by: gemini-3.6-flash
Grading method: judged
Verification: verified
Pass rate without the skill: 0%
Pass rate with the skill: 40.9%
Cases attempted: 22
Cases counted toward lift: 22
Cases that regressed: 0
Skill version measured: v1
Run completed: 7/26/2026, 06:50 UTC

The per-case answers from this run were removed by the retention sweep, so the case table below shows the verdicts without the text either arm produced. The counts above were recorded at the time and are unaffected. Answers are now kept for 180 days.

SkillScore blends 4 signals1 of 4 complete

BenchmarkPass rate WITH skill on a verified run41

Live evalNeeds ≥10 evaluated traces in 30 days

AI ratingNeeds ≥10 rated traces

AdoptionNeeds ≥10 serves across ≥2 orgs in 30 days

Backed by 1 of 4 signals — each added signal makes the score more robust.

Verified on gemini-3.6-flash · re-tested 56 days ago

Other measured skills in the registry, with their headline benchmark lift.