Signalr logo

Signalr

Organization
managedcode
signalr

Implement or review SignalR hubs, streaming, reconnection, transport, and real-time delivery patterns in ASP.NET Core applications. USE FOR: building chat, notification, collaboration, or live-update features; debugging hub lifetime, connection state, or transport issues; deciding whether SignalR or another. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

Overview

Publishermanagedcode
Repositorydotnet-skills
Skill namesignalr
Stars
492
Forks
38
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by managedcode on GitHub. Read the source before you install it.

Installation

Install the Signalr AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/managedcode/dotnet-skills/tree/main/catalog/Frameworks/SignalR/skills/signalr
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/managedcode/dotnet-skills.git /tmp/dotnet-skills
mkdir -p .claude/skills
cp -r /tmp/dotnet-skills/catalog/Frameworks/SignalR/skills/signalr .claude/skills/signalr
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Signalr in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Signalr on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Signalr is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

SignalR

Trigger On

  • building chat, notification, collaboration, or live-update features
  • debugging hub lifetime, connection state, or transport issues
  • deciding whether SignalR or another transport better fits the scenario
  • implementing real-time broadcasting to groups of connected clients
  • scaling SignalR across multiple servers

Documentation

References

  • patterns.md - Detailed hub patterns, streaming, groups, presence, and advanced messaging techniques
  • anti-patterns.md - Common SignalR mistakes and how to avoid them

Workflow

  1. Use SignalR for broadcast-style or connection-oriented real-time features; do not force gRPC into hub-style fan-out scenarios.
  2. Model hub contracts intentionally and keep hub methods thin, delegating durable work elsewhere.
  3. Plan for reconnection, backpressure, auth, and fan-out costs instead of treating real-time messaging as stateless request/response.
  4. Use groups, presence, and connection metadata deliberately so scale-out behavior is understandable.
  5. If Native AOT or trimming is in play, validate supported protocols and serialization choices explicitly.
  6. Test connection behavior and failure modes, not just happy-path message delivery.

Current Upstream Notes

  • dotnet/aspnetcore v10.0.11 is a servicing release and does not change the SignalR programming model. Keep guidance focused on hub contract design, reconnection, transport, authorization, and scale-out validation.
  • The August 2026 ASP.NET Core overview still positions SignalR for real-time server/client communication. After servicing updates, rerun at least one reconnect and group-broadcast smoke path because dependency updates can expose client/server package mismatches.

Hub Patterns

Strongly-Typed Hub (Recommended)

csharp
// Define the client interface
public interface IChatClient
{
    Task ReceiveMessage(string user, string message);
    Task UserJoined(string user);
    Task UserLeft(string user);
}

// Implement the strongly-typed hub
public class ChatHub : Hub<IChatClient>
{
    public async Task SendMessage(string user, string message)
    {
        // Compiler checks client method calls
        await Clients.All.ReceiveMessage(user, message);
    }

    public override async Task OnConnectedAsync()
    {
        await Clients.Others.UserJoined(Context.User?.Identity?.Name ?? "Anonymous");
        await base.OnConnectedAsync();
    }

    public override async Task OnDisconnectedAsync(Exception? exception)
    {
        await Clients.Others.UserLeft(Context.User?.Identity?.Name ?? "Anonymous");
        await base.OnDisconnectedAsync(exception);
    }
}

Using Groups for Targeted Messaging

csharp
public class NotificationHub : Hub<INotificationClient>
{
    public async Task JoinGroup(string groupName)
    {
        await Groups.AddToGroupAsync(Context.ConnectionId, groupName);
        await Clients.Group(groupName).UserJoined(Context.User?.Identity?.Name);
    }

    public async Task LeaveGroup(string groupName)
    {
        await Groups.RemoveFromGroupAsync(Context.ConnectionId, groupName);
    }

    public async Task SendToGroup(string groupName, string message)
    {
        await Clients.Group(groupName).ReceiveNotification(message);
    }
}

Hub Method with Custom Object Parameters (API Versioning)

csharp
// Use custom objects to avoid breaking changes
public class SendMessageRequest
{
    public string Message { get; set; } = string.Empty;
    public string? Recipient { get; set; }  // Added later without breaking clients
    public int? Priority { get; set; }       // Added later without breaking clients
}

public class ChatHub : Hub<IChatClient>
{
    public async Task SendMessage(SendMessageRequest request)
    {
        // Handle both old and new clients
        if (request.Recipient != null)
        {
            await Clients.User(request.Recipient).ReceiveMessage(request.Message);
        }
        else
        {
            await Clients.All.ReceiveMessage(request.Message);
        }
    }
}

Client Patterns

JavaScript Client with Automatic Reconnection

javascript
const connection = new signalR.HubConnectionBuilder()
    .withUrl("/chatHub")
    .withAutomaticReconnect([0, 2000, 5000, 10000, 30000]) // Retry delays
    .configureLogging(signalR.LogLevel.Information)
    .build();

// Handle reconnection events
connection.onreconnecting(error => {
    console.log("Reconnecting...", error);
    updateUIForReconnecting();
});

connection.onreconnected(connectionId => {
    console.log("Reconnected with ID:", connectionId);
    // Rejoin groups - reconnection does not restore group membership
    rejoinGroups();
    updateUIForConnected();
});

connection.onclose(error => {
    console.log("Connection closed", error);
    updateUIForDisconnected();
});

async function start() {
    try {
        await connection.start();
        console.log("SignalR Connected");
    } catch (err) {
        console.log(err);
        setTimeout(start, 5000);
    }
}

start();

.NET Client with Reconnection

csharp
var connection = new HubConnectionBuilder()
    .WithUrl("https://localhost:5001/chatHub", options =>
    {
        options.AccessTokenProvider = () => Task.FromResult(GetAccessToken());
    })
    .WithAutomaticReconnect()
    .Build();

connection.Reconnecting += error =>
{
    _logger.LogWarning("Connection lost. Reconnecting: {Error}", error?.Message);
    return Task.CompletedTask;
};

connection.Reconnected += connectionId =>
{
    _logger.LogInformation("Reconnected with ID: {ConnectionId}", connectionId);
    // Rejoin groups after reconnection
    return RejoinGroupsAsync();
};

connection.Closed += async error =>
{
    _logger.LogError("Connection closed: {Error}", error?.Message);
    await Task.Delay(Random.Shared.Next(0, 5) * 1000);
    await connection.StartAsync();
};

await connection.StartAsync();

Server Configuration

Hub Registration with Authentication

csharp
var builder = WebApplication.CreateBuilder(args);

builder.Services.AddSignalR(options =>
{
    options.EnableDetailedErrors = builder.Environment.IsDevelopment();
    options.MaximumReceiveMessageSize = 64 * 1024; // 64 KB
    options.StreamBufferCapacity = 10;
    options.KeepAliveInterval = TimeSpan.FromSeconds(15);
    options.ClientTimeoutInterval = TimeSpan.FromSeconds(30);
})
.AddMessagePackProtocol(); // Binary protocol for performance

builder.Services.AddAuthentication(JwtBearerDefaults.AuthenticationScheme)
    .AddJwtBearer(options =>
    {
        options.Events = new JwtBearerEvents
        {
            OnMessageReceived = context =>
            {
                // Read token from query string for WebSocket connections
                var accessToken = context.Request.Query["access_token"];
                var path = context.HttpContext.Request.Path;
                if (!string.IsNullOrEmpty(accessToken) && path.StartsWithSegments("/hubs"))
                {
                    context.Token = accessToken;
                }
                return Task.CompletedTask;
            }
        };
    });

var app = builder.Build();

app.UseAuthentication();
app.UseAuthorization();

app.MapHub<ChatHub>("/hubs/chat");

Sending Messages from Outside a Hub

csharp
public class NotificationService
{
    private readonly IHubContext<NotificationHub, INotificationClient> _hubContext;

    public NotificationService(IHubContext<NotificationHub, INotificationClient> hubContext)
    {
        _hubContext = hubContext;
    }

    public async Task NotifyAllAsync(string message)
    {
        await _hubContext.Clients.All.ReceiveNotification(message);
    }

    public async Task NotifyUserAsync(string userId, string message)
    {
        await _hubContext.Clients.User(userId).ReceiveNotification(message);
    }

    public async Task NotifyGroupAsync(string groupName, string message)
    {
        await _hubContext.Clients.Group(groupName).ReceiveNotification(message);
    }
}

Scaling with Redis Backplane

csharp
builder.Services.AddSignalR()
    .AddStackExchangeRedis(connectionString, options =>
    {
        options.Configuration.ChannelPrefix = RedisChannel.Literal("MyApp");
    });

Anti-Patterns to Avoid

Anti-PatternWhy It's BadBetter Approach
Storing state in Hub propertiesHub instances are created per method callUse IMemoryCache, database, or external store
Instantiating Hub directlyBypasses SignalR infrastructureUse IHubContext<THub> for external messaging
Not awaiting SendAsync callsMessages may not be sent before hub method completesAlways await async hub calls
Adding method parameters without versioningBreaking change for existing clientsUse custom object parameters
Ignoring reconnection group lossClients lose group membership on reconnectRe-add to groups in OnConnectedAsync or client reconnect handler
Large payloads over SignalRMemory pressure, bandwidth issuesUse REST/gRPC for bulk data, SignalR for notifications
Missing backplane in multi-serverMessages only reach clients on same serverUse Redis backplane or Azure SignalR Service
Exposing ORM entities directlyMay serialize sensitive dataUse DTOs with explicit properties
Not validating incoming messagesSecurity risk after initial authValidate every hub method input

Best Practices

Connection Management

  1. Enable automatic reconnection with exponential backoff delays
  2. Handle group rejoining explicitly after reconnection (connection ID changes)
  3. Implement heartbeat monitoring on the client to detect stale connections
  4. Use sticky sessions when scaling across multiple servers (unless using Azure SignalR Service)

Performance

  1. Use MessagePack protocol for smaller message sizes and faster serialization
  2. Throttle high-frequency events like typing indicators or mouse movements
  3. Batch messages when possible instead of many small sends
  4. Set appropriate buffer sizes based on expected message throughput

Security

  1. Authenticate at connection time using JWT tokens via query string
  2. Authorize hub methods using [Authorize] attribute
  3. Validate all incoming messages even after authentication
  4. Use HTTPS for all SignalR connections

API Design

  1. Use strongly-typed hubs to catch client method name typos at compile time
  2. Use custom object parameters to enable backward-compatible API evolution
  3. Version hub names (e.g., ChatHubV2) for breaking changes
  4. Keep hub methods thin and delegate business logic to services

Observability

  1. Log connection events (connect, disconnect, reconnect)
  2. Track transport type used by each connection
  3. Monitor message delivery latency and failure rates
  4. Integrate with Application Insights or other APM tools

Deliver

  • clear hub contracts and connection behavior
  • real-time delivery that matches the product scenario
  • validation for reconnection and authorization flows
  • appropriate scale-out strategy for multi-server deployments

Validate

  • SignalR is the correct transport for the use case
  • hub methods remain orchestration-oriented
  • group and auth behavior are explicit and tested
  • reconnection and group membership are handled correctly
  • backplane is configured for multi-server scenarios
  • message validation is implemented in hub methods

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Signalr AI skill do?

Implement or review SignalR hubs, streaming, reconnection, transport, and real-time delivery patterns in ASP.NET Core applications. USE FOR: building chat, notification, collaboration, or live-update features; debugging hub lifetime, connection state, or transport issues; deciding whether SignalR or another. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

Why use Signalr on TypingMind?

Because you install it once and use it with any model. Signalr is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Signalr in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/managedcode/dotnet-skills/tree/main/catalog/Frameworks/SignalR/skills/signalr. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Signalr?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Signalr?

As many as you like. As long as a model supports skills, you can use Signalr with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Signalr AI skill free?

Yes. It is published on GitHub by managedcode under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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