chore: fixes typos (#14343)

fixes typos across repo that were flagged by the CI --------- Co-authored-by: Copilot Autofix powered by AI <[email protected]>
2026-10-12 02:19:06 +00:00 · 2026-08-27 17:07:35 +01:00
parent a256f1ae03
commit b4b0ae7780
21 changed files with 30 additions and 29 deletions
@@ -32,6 +32,7 @@ extend-exclude = [

 [default.extend-words]
 ACI = "ACI"               # Azure Container Instance
+CPY = "CPY"               # Ruff copyright lint rule prefix
 exercize = "exercize"     # test typos
 gramatical = "gramatical" # test typos
 Guid = "Guid"             # Globally Unique Identifier
@@ -144,7 +144,7 @@ Currently the priorities are ordered but not necessarily needs to be implemented

 Chosen option: "Feature Branch Strategy", because it allows individual features to be developed in isolation, minimizing conflicts with the main branch and facilitating easier code reviews.

-## Fequent Asked Questions
+## Frequent Asked Questions

 ### Is there a migration strategy for initiatives that followed the old contribution way with forks, and now have to switch to branches in microsoft/semantic-kernel?

@@ -151,7 +151,7 @@ public sealed record FunctionView(
 | Type                      | Pros                                                         | Cons                                                       |
 | ------------------------- | ------------------------------------------------------------ | ---------------------------------------------------------- |
 | JsonSchema.Net.JsonSchema | Popular and has frequent updates, built on top of System.Net | Takes a dependency on OSS in SK core                       |
-| NJsonShema.JsonSchema     | Very popular, frequent updates, long term project            | Built on top of Json.Net (Newtonsoft)                      |
+| NJsonSchema.JsonSchema    | Very popular, frequent updates, long term project            | Built on top of Json.Net (Newtonsoft)                      |
 | JsonDocument              | Native C# type, fast and flexible                            | Not a Json Schema, but a Json DOM container for the schema |
 | String                    | Native C# type                                               | Not a Json Schema or Json DOM, very poor type hinting      |

@@ -1,5 +1,5 @@
 ---
-# Reestructure of How Sample Code will be Structured In the Repository
+# Restructure of How Sample Code will be Structured In the Repository

 status: accepted
 contact: rogerbarreto
@@ -228,7 +228,7 @@ Identified Component Oriented Concepts:

 - Planners

-  - Handlerbars
+  - Handlebars

 - Authentication

@@ -358,7 +358,7 @@ Concepts/
 │   ├── Resiliency/
 │   └── Usage/
 ├── Planners/
-│   └── Handlerbars/
+│   └── Handlebars/
 ├── Authentication/
 │   └── Azure AD/
 ├── Function Calling/
@@ -420,7 +420,7 @@ Concepts/
 │   ├── Resiliency/
 │   └── Usage/
 ├── Planners/
-│   └── Handlerbars/
+│   └── Handlebars/
 ├── Authentication/
 │   └── Azure AD/
 ├── Function Calling/
@@ -502,7 +502,7 @@ Concepts/
 ├── DependencyInjection
 ├── HttpClient.Resiliency
 ├── HttpClient.Usage
-├── Planners.Handlerbars
+├── Planners.Handlebars
 ├── Authentication.AzureAD
 ├── FunctionCalling.AutoFunctionCalling
 ├── FunctionCalling.ManualFunctionCalling
@@ -545,7 +545,7 @@ Concepts/
 ├── Logging
 ├── DependencyInjection
 ├── HttpClient
-├── Planners.Handlerbars
+├── Planners.Handlebars
 ├── Authentication.AzureAD
 ├── FunctionCalling
 ├── Filtering
@@ -634,7 +634,7 @@ Concepts/

 Pros:

- Beginers will be oriented to the right difficulty level and examples will be more organized by complexity
+- Beginners will be oriented to the right difficulty level and examples will be more organized by complexity

 Cons:

@@ -170,7 +170,7 @@ await ragStore.UpsertDocumentsAsync(
 var agentThread = new ChatHistoryAgentThread();
 agentThread.ThreadExtensionsManager.RegisterThreadExtension(ragComponent);

-// Inovke the agent.
+// Invoke the agent.
 var asyncResults1 = agent.InvokeAsync("What was the income of Contoso for 2023", agentThread);
 // Expected response contains the 174M income from the document.
 ```
@@ -19,7 +19,7 @@ Prefix|Description
 ---|---
 OpenAIAssistant|How to use agents based on the [Open AI Assistant API](https://platform.openai.com/docs/assistants).
 MixedChat|How to combine different agent types.
-ComplexChat|How to deveop complex agent chat solutions.
+ComplexChat|How to develop complex agent chat solutions.
 Legacy|How to use the legacy _Experimental Agent API_.

 ## Legacy Agents
@@ -253,7 +253,7 @@ public class LocalExamplePlugin(ITestOutputHelper output)
    [KernelFunction]
    public async Task<string> TaskInjectingCancellationTokenWithStringResult(CancellationToken cancellationToken)
    {
-        var result = $"Cancellation resquested: {cancellationToken.IsCancellationRequested}";
+        var result = $"Cancellation requested: {cancellationToken.IsCancellationRequested}";
        this._output.WriteLine($"Running {nameof(this.TaskInjectingCultureInfoOrIFormatProviderWithStringResult)} -> Injected Cancellation Token -> result: {result}");
        return result;
    }
@@ -127,7 +127,7 @@ Jane: Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed euismod, nunc
 Jane: Darn, it's just repeating stuff now.
 John: I think we're done.
 Jane: We're not though! We need like 1500 more characters.
-John: Oh Cananda, our home and native land.
+John: Oh Canada, our home and native land.
 Jane: True patriot love in all thy sons command.
 John: With glowing hearts we see thee rise.
 Jane: The True North strong and free.
@@ -79,7 +79,7 @@ Jane: Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed euismod, nunc
 Jane: Darn, it's just repeating stuff now.
 John: I think we're done.
 Jane: We're not though! We need like 1500 more characters.
-John: Oh Cananda, our home and native land.
+John: Oh Canada, our home and native land.
 Jane: True patriot love in all thy sons command.
 John: With glowing hearts we see thee rise.
 Jane: The True North strong and free.
@@ -8,7 +8,7 @@ namespace Plugins;
 // This example shows how to use gRPC plugins.
 public class ImportPluginFromGrpc(ITestOutputHelper output) : BaseTest(output)
 {
-    [Fact(Skip = "Setup crendentials")]
+    [Fact(Skip = "Setup credentials")]
    public async Task RunAsync()
    {
        Kernel kernel = new();
@@ -12,7 +12,7 @@ namespace ProcessFramework.Aspire.SignalR.ProcessOrchestrator.Steps;
 public class GenerateDocumentationStep : KernelProcessStep<GenerateDocumentationState>
 {
    /// <summary>
-    /// Function names of the steps, to be refereced when hooking up the step in a SK process
+    /// Function names of the steps, to be referenced when hooking up the step in a SK process
    /// </summary>
    public static class ProcessFunctions
    {
@@ -12,7 +12,7 @@ namespace ProcessWithCloudEvents.Processes.Steps;
 public class GenerateDocumentationStep : KernelProcessStep<GenerateDocumentationState>
 {
    /// <summary>
-    /// Function names of the steps, to be refereced when hooking up the step in a SK process
+    /// Function names of the steps, to be referenced when hooking up the step in a SK process
    /// </summary>
    public static class ProcessFunctions
    {
@@ -369,7 +369,7 @@ public abstract class Agent
    }

    /// <summary>
-    /// Notfiy the given thread that a new message is available.
+    /// Notify the given thread that a new message is available.
    /// </summary>
    /// <remarks>
    /// <para>
@@ -6,7 +6,7 @@ using OpenAI.Responses;
 namespace Microsoft.SemanticKernel.Agents.OpenAI;

 /// <summary>
-/// Extensons methods for <see cref="KernelContent"/>.
+/// Extension methods for <see cref="KernelContent"/>.
 /// </summary>
 internal static class KernelContentExtensions
 {
@@ -18,16 +18,16 @@ public class KeyEncoderTests
    public void VerifyKeyEncoderUniqueness()
    {
        // Act
-        this.VerifyHashEquivalancy([]);
-        this.VerifyHashEquivalancy(nameof(KeyEncoderTests));
-        this.VerifyHashEquivalancy(nameof(KeyEncoderTests), "http://localhost", "zoo");
+        this.VerifyHashEquivalency([]);
+        this.VerifyHashEquivalency(nameof(KeyEncoderTests));
+        this.VerifyHashEquivalency(nameof(KeyEncoderTests), "http://localhost", "zoo");

        // Assert: Verify "well-known" value
        string localHash = KeyEncoder.GenerateHash([typeof(ChatHistoryChannel).FullName!]);
        Assert.Equal("Vdx37EnWT9BS+kkCkEgFCg9uHvHNw1+hXMA4sgNMKs4=", localHash);
    }

-    private void VerifyHashEquivalancy(params string[] keys)
+    private void VerifyHashEquivalency(params string[] keys)
    {
        // Act
        string hash1 = KeyEncoder.GenerateHash(keys);
@@ -15,7 +15,7 @@ using Xunit;
 namespace Microsoft.SemanticKernel.Connectors.Amazon.UnitTests;

 /// <summary>
-/// Unit tests for prompt execution settings confirgurations for different Bedrock Models.
+/// Unit tests for prompt execution settings configurations for different Bedrock Models.
 /// </summary>
 public class BedrockChatCompletionModelExecutionSettingsTests
 {
@@ -47,7 +47,7 @@ template: |
    If there is not a fitting function available to validate the result, I can provide the final answer in a clear and human-readable format.
    [END THOUGHT PROCESS]

-    IMOPRTANT REMINDER: your each response should contain only one next step and only single one $JSON_BLOB. Do not provide more than one step.  
+    IMPORTANT REMINDER: each response should contain only one next step and only a single $JSON_BLOB. Do not provide more than one step.
    Let's break down the problem step by step and think about the best approach.

    Begin!
@@ -12,7 +12,7 @@ public sealed class MessageSourceBuilder
    /// <summary>
    /// Initializes a new instance of the <see cref="MessageSourceBuilder"/> class.
    /// </summary>
-    /// <param name="messageType">The meassage type</param>
+    /// <param name="messageType">The message type</param>
    /// <param name="source">The source step builder</param>
    /// <param name="condition">Condition that must be met for the message to be processed</param>
    public MessageSourceBuilder(string messageType, ProcessStepBuilder source, KernelProcessEdgeCondition? condition = null)
@@ -5,7 +5,7 @@ using System.Text.Json.Serialization;
 namespace Microsoft.SemanticKernel;

 /// <summary>
-/// A class to describe the content schma of a response/return type from an KernelFunctionFactory, in a JSON Schema friendly way.
+/// A class to describe the content schema of a response/return type from a KernelFunctionFactory, in a JSON Schema friendly way.
 /// </summary>
 internal sealed class JsonSchemaResponse
 {
@@ -156,7 +156,7 @@ public sealed class WhiteboardProvider : AIContextProvider
        var inputMessagesJson = JsonSerializer.Serialize(basicMessages, WhiteboardProviderSourceGenerationContext.Default.IEnumerableBasicMessage);
        var currentWhiteboardJson = JsonSerializer.Serialize(this._currentWhiteboardContent, WhiteboardProviderSourceGenerationContext.Default.ListString);

-        // Inovke the LLM to extract the latest information from the input messages and update the whiteboard.
+        // Invoke the LLM to extract the latest information from the input messages and update the whiteboard.
        var result = await this._chatClient.GetResponseAsync(
            this.FormatPromptTemplate(inputMessagesJson, currentWhiteboardJson, this._maxWhiteboardMessages),
            new()
@@ -32,7 +32,7 @@ Example|Description
 [step08_chat_completion_agent_json_result](../getting_started_with_agents/chat_completion/step08_chat_completion_agent_json_result.py)|How to have an agent produce JSON.
 [step09_chat_completion_agent_logging](../getting_started_with_agents/chat_completion/step09_chat_completion_agent_logging.py)|How to enable logging for agents.
 [step10_chat_completion_agent_structured_outputs](../getting_started_with_agents/chat_completion/step10_chat_completion_agent_structured_outputs.py)|How to use have a chat completion agent use structured outputs
-[step11_chat_completion_agent_declarative](../getting_started_with_agents/chat_completion/step11_chat_completion_agent_declarative.py)|How to create a chat compltion agent from a declarative spec.
+[step11_chat_completion_agent_declarative](../getting_started_with_agents/chat_completion/step11_chat_completion_agent_declarative.py)|How to create a chat completion agent from a declarative spec.

 ## Azure AI Agent