sheng-jie

sheng-jie / learn-cc-csharp

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这个仓库是 https://github.com/shareAI-lab/learn-claude-code 的 .NET 移植版。原仓库以 Python 语言深入浅出地剖析了 Claude Code 的核心原理。为了方便 .NET 开发者学习掌握 Agent 的构建精髓，我们将其核心代码使用 C# 的最新特性进行了完整重写。

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Found Feb 02, 2026 at 12 stars 4x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
C#
AI Summary

A progressive series of simple programs that create AI assistants for helping with everyday coding tasks like editing files, running commands, planning work, delegating subtasks, and applying specialized know-how.

How It Works

1
🔍 Discover the coding helper

You find this handy set of tools on a sharing site that promises to make coding easier with a smart assistant right in your project folder.

2
📥 Bring it home

You copy the files into the folder where your own project lives, so it's ready to help with your code.

3
🔗 Connect the smart brain

You link it to a thinking service by adding a simple private note, letting the assistant understand and act on your ideas.

4
🚀 Wake up the assistant

You start the latest helper version, and it greets you in your folder, ready for chatting.

5
💬 Ask for coding magic

You type a task like 'fix this bug' or 'add a new feature', and watch it plan steps, explore files, team up helpers, grab expert tips, and make changes automatically.

6
✅ Review the results

Your files update perfectly, todos check off, and everything works better, feeling like having a pro coder on your team.

🎉 Mission accomplished

Your project levels up effortlessly, saving hours of work, and you're excited to tackle bigger ideas next.

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AI-Generated Review

What is learn-cc-csharp?

This C# repo ports the Python project https://github.com/shareai-lab/learn-claude-code to teach .NET developers core agent principles using Claude models. Drop a single-file script into your repo, set an Anthropic API key via dotenv, and run "dotnet run" for a CLI agent that reads/edits files, runs bash commands, tracks todos, spawns subagents for focused tasks, and loads skills for domain expertise like PDF handling—all in your local directory.

Why is it gaining traction?

It distills agent building into progressive, runnable examples—from bash-only loops to full planning and subagent isolation—using modern C# features like top-level statements. .NET devs get a lightweight alternative to Python agent libs, with user-facing wins like clean REPL mode, process-isolated subagents keeping contexts fresh, and skill injection for specialized workflows without retraining.

Who should use this?

.NET backend engineers automating code refactors or repo explorations via Claude-powered CLI. C# learners experimenting with agentic patterns for tasks like "plan a migration then implement," or teams prototyping local AI tools before full apps.

Verdict

Solid learning resource for C# agent builders—run it today despite 24 stars and 1.0% credibility signaling early maturity. No tests or deep docs yet, but zero-setup execution makes it worth forking for custom .NET agents.

(178 words)

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