Translate the Azure SDK sample from python to C# and generate markdownn file for the sample. Parameters: <cs_root> C# SDK repository root; <python_root> python SDK repository root; <package_name> Package name: one of Azure.AI.Projects, Azure.AI.Projects.Agents or Azure.AI.Extensions.OpenAI; <sample_name> The name of sample file in Python SDK repository.
npx skills add https://github.com/Azure/azure-sdk-for-net --skill translate-a-sample
This skill require four inputs: <python_root> (repository root for python) and <cs_root> (repository root for C#), <package_name> and <sample_name> the sample to be processed. the C# package name. All the consequent paths are given relatively to the repository root. Python package is located in <python_root>/sdk/ai/azure-ai-projects, C# project is located in <cs_root>/sdk/ai/<package_name>. All python samples are located in <python_root>/sdk/ai/azure-ai-projects/samples, they are organized by folders according to their topic. In most cases the sample has sync and async implementation. For example, feature.py and feature_async.py are demonstrating sync and async features. C# sample consists of two parts: the source code in the folder <cs_root>/sdk/ai/<package_name>/tests/Samples and corresponding .md files go to <cs_root>/sdk/ai/<package_name>/Samples.
Please analyze the sample provided sample in <sample_name> and generate the sample and .md file in C#. The C# file should demonstrate both sync and async API when appropriate. See the example below:
#if SNIPPET
var projectEndpoint = System.Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT");
var modelDeploymentName = System.Environment.GetEnvironmentVariable("FOUNDRY_MODEL_NAME");
#else
var projectEndpoint = TestEnvironment.FOUNDRY_PROJECT_ENDPOINT;
var modelDeploymentName = TestEnvironment.FOUNDRY_MODEL_NAME;
#endif
AIProjectClient projectClient = new(endpoint: new Uri(projectEndpoint), tokenProvider: new DefaultAzureCredential());
DeclarativeAgentDefinition agentDefinition = new(model: modelDeploymentName)
{
Instructions = "You are a prompt agent."
};
ProjectsAgentVersion agentVersion1 = await projectClient.AgentAdministrationClient.CreateAgentVersionAsync(
agentName: "myAgent1",
options: new(agentDefinition));
#if SNIPPET
var projectEndpoint = System.Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT");
var modelDeploymentName = System.Environment.GetEnvironmentVariable("FOUNDRY_MODEL_NAME");
#else
var projectEndpoint = TestEnvironment.FOUNDRY_PROJECT_ENDPOINT;
var modelDeploymentName = TestEnvironment.FOUNDRY_MODEL_NAME;
#endif
AIProjectClient projectClient = new(endpoint: new Uri(projectEndpoint), tokenProvider: new DefaultAzureCredential());
DeclarativeAgentDefinition agentDefinition = new(model: modelDeploymentName)
{
Instructions = "You are a prompt agent."
};
ProjectsAgentVersion agentVersion1 = projectClient.AgentAdministrationClient.CreateAgentVersion(
agentName: "myAgent1",
options: new(agentDefinition));
The code needs tro be logically split into blocks, which usage should be explained in .md file. Each blocks is marked in the source code as follows:
#region Snippet:Sample_FunctionFoo_MySampl_Async
public async Task Foo()
{
await Task.Delay(1000);
Console.WriteLine("Hello world!")
}
#endregion
These blocks will be rendered in the .md file code block based on the region name (it will be done by automation):
public async Task Foo()
{
await Task.Delay(1000);
Console.WriteLine("Hello world!")
}
If the code block has sync and async counterpart, please create code block for each of them. Provide the short explanation for each code block.
To make sure that it is the case, please run the script below. If there are errors, please iterate over it until the script will complete without errors.
cd <cs_root>
eng\scripts\Update-Snippets.ps1 ai\<package>
cd <cs_root>
eng\scripts\Update-Snippets.ps1 ai\<package>
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Take azure/translate-a-sample from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.