api-design

aaronontheweb/dotnet-skills · updated Apr 8, 2026

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$npx skills add https://github.com/aaronontheweb/dotnet-skills --skill api-design
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summary

Use this skill when:

skill.md

Public API Design and Compatibility

When to Use This Skill

Use this skill when:

  • Designing public APIs for NuGet packages or libraries
  • Making changes to existing public APIs
  • Planning wire format changes for distributed systems
  • Implementing versioning strategies
  • Reviewing pull requests for breaking changes

The Three Types of Compatibility

Type Definition Scope
API/Source Code compiles against newer version Public method signatures, types
Binary Compiled code runs against newer version Assembly layout, method tokens
Wire Serialized data readable by other versions Network protocols, persistence formats

Breaking any of these creates upgrade friction for users.


Extend-Only Design

The foundation of stable APIs: never remove or modify, only extend.

Three Pillars

  1. Previous functionality is immutable - Once released, behavior and signatures are locked
  2. New functionality through new constructs - Add overloads, new types, opt-in features
  3. Removal only after deprecation period - Years, not releases

Benefits

  • Old code continues working in new versions
  • New and old pathways coexist
  • Upgrades are non-breaking by default
  • Users upgrade on their schedule

Resources:


API Change Guidelines

Safe Changes (Any Release)

// ADD new overloads with default parameters
public void Process(Order order, CancellationToken ct = default);

// ADD new optional parameters to existing methods
public void Send(Message msg, Priority priority = Priority.Normal);

// ADD new types, interfaces, enums
public interface IOrderValidator { }
public enum OrderStatus { Pending, Complete, Cancelled }

// ADD new members to existing types
public class Order
{
    public DateTimeOffset? ShippedAt { get; init; }  // NEW
}

Unsafe Changes (Never or Major Version Only)

// REMOVE or RENAME public members
public void ProcessOrder(Order order);  // Was: Process()

// CHANGE parameter types or order
public void Process(int orderId);  // Was: Process(Order order)

// CHANGE return types
public Order? GetOrder(string id);  // Was: public Order GetOrder()

// CHANGE access modifiers
internal class OrderProcessor { }  // Was: public

// ADD required parameters without defaults
public void Process(Order order, ILogger logger);  // Breaks callers!

Deprecation Pattern

// Step 1: Mark as obsolete with version (any release)
[Obsolete("Obsolete since v1.5.0. Use ProcessAsync instead.")]
public void Process(Order order) { }

// Step 2: Add new recommended API (same release)
public Task ProcessAsync(Order order, CancellationToken ct = default);

// Step 3: Remove in next major version (v2.0+)
// Only after users have had time to migrate

API Approval Testing

Prevent accidental breaking changes with automated API surface testing.

Using ApiApprover + Verify

dotnet add package PublicApiGenerator
dotnet add package Verify.Xunit
[Fact]
public Task ApprovePublicApi()
{
    var api = typeof(MyLibrary.PublicClass).Assembly.GeneratePublicApi();
    return Verify(api);
}

Creates ApprovePublicApi.verified.txt:

namespace MyLibrary
{
    public class OrderProcessor
    {
        public OrderProcessor() { }
        public void Process(Order order) { }
        public Task ProcessAsync(Order order, CancellationToken ct = default) { }
    }
}

Any API change fails the test - reviewer must explicitly approve changes.

PR Review Process

  1. PR includes changes to *.verified.txt files
  2. Reviewers see exact API surface changes in diff
  3. Breaking changes are immediately visible
  4. Conscious decision required to approve

Wire Compatibility

For distributed systems, serialized data must be readable across versions.

Requirements

Direction Requirement
Backward Old writers → New readers (current version reads old data)
Forward New writers → Old readers (old version reads new data)

Both are required for zero-downtime rolling upgrades.

Safely Evolving Wire Formats

Phase 1: Add read-side support (opt-in)

// New message type - readers deployed first
public sealed record HeartbeatV2(
    Address From,
    long SequenceNr,
    long CreationTimeMs);  // NEW field

// Deserializer handles both old and new
public object Deserialize(byte[] data, string manifest) => manifest switch
{
    "Heartbeat" => DeserializeHeartbeatV1(data),   // Old format
    "HeartbeatV2" => DeserializeHeartbeatV2(data), // New format
    _ => throw new NotSupportedException()
};

Phase 2: Enable write-side (opt-out, next minor version)

// Config to enable new format (off by default initially)
akka.cluster.use-heartbeat-v2 = on

Phase 3: Make default (future version)

After install base has absorbed read-side code.

Schema-Based Serialization

Prefer schema-based formats over reflection-based:

Format Type Wire Compatibility
Protocol Buffers Schema-based Excellent - explicit field numbers
MessagePack Schema-based Good - with contracts
System.Text.Json Schema-based (with source gen) Good - explicit properties
Newtonsoft.Json Reflection-based Poor - type names in payload
BinaryFormatter Reflection-based Terrible - never use

See dotnet/serialization skill for details.


Encapsulation Patterns

Internal APIs

Mark non-public APIs explicitly:

// Attribute for documentation
[InternalApi]
public class ActorSystemImpl { }

// Namespace convention
namespace MyLibrary.Internal
{
    public class InternalHelper { }  // Public for extensibility, not for users
}

Document clearly:

Types in .Internal namespaces or marked with [InternalApi] may change between any releases without notice.

Sealing Classes

// DO: Seal classes not designed for inheritance
public sealed class OrderProcessor { }

// DON'T: Leave unsealed by accident
public class OrderProcessor { }  // Users might inherit, blocking changes

Interface Segregation

// DO: Small, focused interfaces
public interface IOrderReader
{
    Order? GetById(OrderId id);
}

public interface IOrderWriter
{
    Task SaveAsync(Order order);
}

// DON'T: Monolithic interfaces (can't add methods without breaking)
how to use api-design

How to use api-design on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add api-design
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/aaronontheweb/dotnet-skills --skill api-design

The skills CLI fetches api-design from GitHub repository aaronontheweb/dotnet-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/api-design

Reload or restart Cursor to activate api-design. Access the skill through slash commands (e.g., /api-design) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.544 reviews
  • Carlos Diallo· Dec 24, 2024

    Registry listing for api-design matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Omar Thomas· Dec 16, 2024

    Keeps context tight: api-design is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Omar Haddad· Dec 16, 2024

    We added api-design from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Dhruvi Jain· Dec 12, 2024

    We added api-design from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Hiroshi Patel· Dec 8, 2024

    api-design reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Noah Perez· Nov 27, 2024

    api-design has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Soo Choi· Nov 27, 2024

    api-design is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Noah Mensah· Nov 15, 2024

    Solid pick for teams standardizing on skills: api-design is focused, and the summary matches what you get after install.

  • Noah Sanchez· Nov 7, 2024

    api-design fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Oshnikdeep· Nov 3, 2024

    api-design fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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