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Project Setup

Organization
codewithmukesh
project-setup

Tech-stack selection advisor for .NET projects: recommended defaults for database, auth, caching, messaging, observability, and resilience, with the rationale behind each default. Load when choosing or reviewing a project's tech stack, or when the user says "tech stack", "which database", "pick a stack", "recommended defaults", or "what should I use for". For project initialization use dotnet-init, for codebase assessment use health-check, for upgrades and schema changes use migrate.

Overview

Publishercodewithmukesh
Repositorydotnet-claude-kit
Skill nameproject-setup
Stars
721
Forks
170
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Project Setup 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.
  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/codewithmukesh/dotnet-claude-kit.git /tmp/dotnet-claude-kit
mkdir -p .claude/skills
cp -r /tmp/dotnet-claude-kit/skills/project-setup .claude/skills/project-setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Project Setup 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 Project Setup 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 Project Setup 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.

Project Setup — Tech-Stack Advisor

This skill owns one thing: the kit's recommended tech-stack defaults and why. The workflows that consume it live elsewhere:

  • Initializing a project / generating CLAUDE.mddotnet-init (interactive flow, architecture questionnaire, CLAUDE.md generation)
  • Assessing an existing codebasehealth-check (the canonical 8-dimension graded assessment)
  • EF Core schema, NuGet, or .NET version migrationsmigrate
  • Choosing an architecturearchitecture-advisor (always ask before recommending)

Core Principles

  1. Recommend a default, explain the why, let the user choose — Every dimension has a kit default, but defaults are starting points, not mandates. State the trade-off in one line so the choice is informed.
  2. Prefer built-in .NET over third-partyHybridCache over Redis-client wrappers, built-in rate limiting over packages, built-in OpenAPI over Swashbuckle. Fewer dependencies means fewer licensing surprises and upgrade breaks.
  3. License-aware picks — MediatR (v13+), MassTransit (v9+), and FluentAssertions (v8+) went commercial. The kit defaults to MIT alternatives: Mediator, Wolverine, plain xUnit asserts.
  4. Add messaging later, not never — Most projects don't need a message bus on day one. Default to "None (add later)" and reach for Wolverine when async workflows actually appear.

Patterns

Tech-Stack Dimensions and Defaults

DimensionOptionsDefaultWhy
DatabasePostgreSQL, SQL Server, SQLitePostgreSQLOpen source, best EF Core provider outside SQL Server, first-class Testcontainers support
AuthJWT Bearer, OIDC (Keycloak/Auth0), NoneJWT BearerSimplest secure default for APIs; move to OIDC when an external IdP exists
CachingHybridCache, Redis, NoneHybridCacheBuilt-in, stampede protection, L1+L2 — add Redis only as its L2 backend
MessagingWolverine (RabbitMQ), MassTransit, NoneNone (add later)Premature messaging adds ops burden; Wolverine (MIT) when needed
ObservabilitySerilog + OpenTelemetry, Basic loggingSerilog + OTELStructured logs + traces from day one are cheap; retrofitting is not
ResiliencePolly v8 pipelines, Basic retryPolly v8AddStandardResilienceHandler() is one line for production-grade defaults
API docsBuilt-in OpenAPI + ScalarOpenAPI + ScalarFramework-maintained spec generation; Scalar replaces Swagger UI
TestingxUnit v3 + TestcontainersxUnit v3 + TestcontainersReal databases in tests; in-memory providers hide real bugs

Once dimensions are chosen, dotnet-init bakes them into the generated CLAUDE.md, and each choice maps to a skill to load when working in that area (ef-core, authentication, caching, messaging, serilog, opentelemetry, resilience, openapi, scalar, testing).

Anti-patterns

Prescribing a Stack Without Asking

# BAD — assuming the kit defaults apply everywhere
"You should use PostgreSQL and Wolverine."
# The team runs SQL Server enterprise-wide and has zero async workflows.

# GOOD — default + trade-off + question
"Kit default is PostgreSQL (best OSS EF provider). Any organizational
constraint — existing SQL Server licenses, DBA support — that should
override it?"

Re-Running Workflows This Skill Doesn't Own

# BAD — improvising a health grading or init flow from this skill
"Let me grade your codebase across 5 categories..."
# That grading conflicts with the canonical one.

# GOOD — route to the owner
Init/CLAUDE.md → dotnet-init | Assessment → health-check | Upgrades → migrate

Decision Guide

ScenarioRoute to
"Set up this project for Claude Code"dotnet-init
"Which database/auth/caching should I use?"This skill — table above
"How healthy is this codebase?"health-check
"Upgrade to .NET 10" / "update packages"migrate
"Which architecture fits?"architecture-advisor
Stack chosen, ready to buildscaffold for the first feature

Frequently asked questions

What does the Project Setup AI skill do?

Tech-stack selection advisor for .NET projects: recommended defaults for database, auth, caching, messaging, observability, and resilience, with the rationale behind each default. Load when choosing or reviewing a project's tech stack, or when the user says "tech stack", "which database", "pick a stack", "recommended defaults", or "what should I use for". For project initialization use dotnet-init, for codebase assessment use health-check, for upgrades and schema changes use migrate.

Why use Project Setup on TypingMind?

Because you install it once and use it with any model. Project Setup 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 Project Setup in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/codewithmukesh/dotnet-claude-kit/tree/main/skills/project-setup. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Project Setup?

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 Project Setup?

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

Is the Project Setup AI skill free?

Yes. It is published on GitHub by codewithmukesh 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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