dotnet-backend-patterns

Overview of dotnet-backend-patterns skill

dotnet-backend-patterns is a practical guidance skill for designing and reviewing production-style C# backends. It is best for developers building .NET Web APIs, internal services, MCP servers, or layered enterprise applications who want stronger defaults than a generic “write a backend” prompt.

What dotnet-backend-patterns actually helps with

The real job-to-be-done is not just generating C# code. The skill helps an agent choose sane backend patterns across project structure, dependency injection, async flows, configuration, data access, caching, resilience, and testing so the output looks like maintainable application code instead of isolated snippets.

Best-fit users and projects

This skill fits teams that already know they want a .NET backend and need help with implementation shape:

• New API or service scaffolding
• Refactoring a messy service layer
• Choosing between EF Core and Dapper
• Improving performance on read-heavy endpoints
• Standardizing testing and configuration patterns
• Reviewing architecture before code expands

Why choose this over a normal coding prompt

The main differentiator is pattern guidance with concrete backend concerns, not just syntax generation. The repository includes focused references for Dapper and EF Core, plus template files that help an agent produce code with clearer separation of concerns than a generic prompt usually does.

What matters most before you install

If you want a full runnable framework, CLI, or package, this is not that. dotnet-backend-patterns is most useful when you need architectural guidance and code generation grounded in common backend patterns. It is weaker when your real need is front-end work, deep DevOps automation, or highly opinionated framework-specific conventions outside standard .NET backend practice.

How to Use dotnet-backend-patterns skill

dotnet-backend-patterns install context

Install it through the skills workflow used by the repository:

npx skills add https://github.com/wshobson/agents --skill dotnet-backend-patterns

Because the upstream SKILL.md does not provide its own install command, directory users should treat the command above as the practical dotnet-backend-patterns install path.

Read these files first

For fastest understanding, open these in order:

1. SKILL.md
2. assets/repository-template.cs
3. assets/service-template.cs
4. references/ef-core-best-practices.md
5. references/dapper-patterns.md

This sequence gives you the core architecture first, then concrete coding shape, then the two most decision-heavy data-access references.

What input the skill needs from you

dotnet-backend-patterns works best when you provide:

• App type: API, background worker, MCP server, internal service
• Target .NET version if known
• Data layer choice: EF Core, Dapper, or mixed
• Domain shape: entities, use cases, external dependencies
• Nonfunctional needs: throughput, latency, caching, test depth
• Existing repo constraints: layered monolith, clean architecture, legacy DB
• Output scope: design review, file scaffold, service implementation, refactor plan

Without those inputs, the agent may default to generic clean architecture and miss the practical tradeoffs you actually care about.

Turn a rough goal into a good prompt

Weak prompt:

Build a .NET backend for orders.

Stronger prompt:

Use dotnet-backend-patterns for Backend Development. Design a .NET 8 Web API for order processing with EF Core for writes, Dapper for reporting reads, Redis caching for product lookups, IOptions for configuration, xUnit tests, and clean separation between Domain, Application, and Infrastructure. Show project structure, DI registrations, one service example, one repository example, and explain where async, validation, and error handling live.

The stronger version improves output because it fixes scope, stack, architecture, and success criteria.

Ask for decisions, not just code

The skill is strongest when you request tradeoff-aware output such as:

• “Choose EF Core vs Dapper for these workloads”
• “Refactor this service into cleaner application/infrastructure boundaries”
• “Review this endpoint for async, DI, and query performance issues”
• “Propose caching and test strategy for these read-heavy flows”

That steers the agent toward architecture and maintainability instead of surface-level code completion.

Use the assets as output anchors

The two asset files are valuable because they anchor style and layering:

• assets/repository-template.cs
• assets/service-template.cs

When prompting, explicitly ask the agent to mirror those patterns. That reduces drift into ad hoc repository and service implementations.

How to use dotnet-backend-patterns for data access choices

A major practical benefit of dotnet-backend-patterns usage is deciding when to use EF Core versus Dapper.

Use references/ef-core-best-practices.md when you need:

• Rich models and relationships
• Change tracking
• LINQ-based queries
• Safer defaults for application CRUD

Use references/dapper-patterns.md when you need:

• Hot-path performance
• SQL control
• Read-heavy endpoints
• Complex reporting queries or legacy schemas

If your app has both transactional writes and performance-sensitive reads, ask the agent for a hybrid approach instead of forcing one tool everywhere.

Suggested workflow for real projects

A practical dotnet-backend-patterns guide for real use:

1. Define the service boundary and use cases.
2. Ask the agent for project structure and DI layout.
3. Choose EF Core, Dapper, or mixed based on workload.
4. Generate one vertical slice end to end.
5. Review async patterns, validation, and error handling.
6. Add caching only where read patterns justify it.
7. Add xUnit tests after contracts and service boundaries stabilize.

This order keeps the skill focused on architecture and avoids premature optimization.

What the skill appears to emphasize

Based on the repository content, expect stronger help on:

• Clean layering
• Dependency injection
• Query performance basics
• Configuration via options patterns
• Testing habits
• Production-friendly async usage

Expect less direct help on:

• Deployment pipelines
• Container orchestration
• Advanced cloud-native runtime configuration
• Domain-specific frameworks not shown in the repo

Practical prompt template

Use this template for better dotnet-backend-patterns usage:

Apply dotnet-backend-patterns to this backend task.
Project type: [Web API / MCP server / worker]
Target: [.NET version]
Architecture constraint: [clean architecture / existing layered monolith / minimal API]
Data access: [EF Core / Dapper / both]
Requirements: [entities, endpoints, integrations]
Nonfunctional needs: [performance, caching, tests, resilience]
Output needed: [design review / scaffold / concrete code / refactor plan]
Please follow the repository and service patterns from assets/repository-template.cs and assets/service-template.cs, and explain any tradeoffs.

Common adoption blockers

The biggest blockers are usually not installation issues but ambiguity:

• No target architecture specified
• No workload detail for choosing EF Core or Dapper
• Asking for “best practices” without code context
• Expecting the skill to infer your domain model from a vague feature list

You get better output by giving one realistic slice of your backend rather than requesting the whole system in one pass.

dotnet-backend-patterns skill FAQ

Is dotnet-backend-patterns good for beginners?

Yes, if you already know basic C# and want help structuring backend code. It is not a beginner tutorial for learning the language from scratch. The skill assumes you can read typical .NET project layouts and DI registrations.

When should I use dotnet-backend-patterns instead of a normal prompt?

Use it when structure matters: service boundaries, repository patterns, async behavior, configuration, testing, and data-access tradeoffs. A normal prompt may generate working code, but dotnet-backend-patterns is more likely to produce code that fits a maintainable backend shape.

Is dotnet-backend-patterns only for Web APIs?

No. The repository description also mentions MCP servers and enterprise backends. The patterns are broadly useful anywhere you have application services, infrastructure concerns, and persistent data access in .NET.

Does the skill force clean architecture?

It strongly leans that way, but you do not need to adopt every layer rigidly. If your codebase is a simpler layered API or a constrained monolith, ask the agent to adapt the patterns rather than recreate a textbook structure.

Can dotnet-backend-patterns help me choose between EF Core and Dapper?

Yes, that is one of the clearest strengths of the repository because it includes separate reference material for both. If you describe your query patterns and performance needs, the skill can give a more grounded recommendation than a generic prompt.

Is dotnet-backend-patterns suitable for legacy systems?

Often yes, especially for refactoring service boundaries or improving data-access practices incrementally. It is less suitable if you need exact guidance for a heavily customized legacy framework that does not resemble modern .NET backend conventions.

What is the main limitation of this dotnet-backend-patterns guide?

The repository is guidance-heavy and light on automation. It gives patterns, references, and templates, but not a turnkey generator or end-to-end sample application. You still need to supply repo context and make architectural choices.

How to Improve dotnet-backend-patterns skill

Give the agent your actual backend constraints

The fastest way to improve dotnet-backend-patterns results is to stop asking for “best practice” in the abstract. Include:

• Current project structure
• Existing abstractions you must keep
• DB type and schema realities
• Performance bottlenecks
• Test expectations
• Whether you can add layers or only refactor within current folders

Constraint-rich prompts produce advice that is more adoptable.

Show one representative code path

Instead of pasting ten files, provide one realistic vertical slice:

• Controller or endpoint
• Service
• Repository or query layer
• Relevant entity/DTO
• A problem statement

That is usually enough for the skill to identify async, DI, boundary, and data-access issues without drowning in noise.

Ask for tradeoffs explicitly

To improve dotnet-backend-patterns skill output, request comparisons like:

• “Keep current design but reduce coupling”
• “Refactor with minimal file churn”
• “Optimize read path without rewriting writes”
• “Use Dapper only where EF Core becomes a bottleneck”

This helps the agent avoid overengineering.

Prevent common failure modes

Typical failure modes include:

• Too many layers for a small API
• Generic repository patterns where direct query logic is clearer
• Caching added without invalidation strategy
• Async everywhere without attention to cancellation and real I/O boundaries
• EF Core advice that ignores projection and tracking costs

You can prevent these by asking the agent to justify each pattern it introduces.

Improve outputs with better acceptance criteria

Add success criteria such as:

• “Must be testable with xUnit”
• “Must support cancellation tokens”
• “Read endpoints should be no-tracking”
• “Use DTO projection, not entity overfetching”
• “Keep external API calls behind an interface”

These criteria line up well with the repository’s stronger guidance areas.

Iterate after the first draft

After the first response, do not just ask for “more detail.” Ask for one targeted refinement:

• simplify the architecture
• convert one query to Dapper
• add IOptions configuration binding
• improve test seams
• identify performance hotspots
• add caching only to specific reads

Focused iteration usually gets better results from dotnet-backend-patterns than broad regeneration.

Use repository references to challenge generic answers

If the output feels generic, tell the agent to revise using:

• references/ef-core-best-practices.md for query shape and tracking decisions
• references/dapper-patterns.md for connection handling and SQL-heavy paths
• assets/service-template.cs for service organization
• assets/repository-template.cs for repository shape

This is one of the easiest ways to improve the skill’s output quality without rewriting your whole prompt.