본문으로 건너뛰기
cccskills
무료GitHub에 공개

dotnet-harness-recommender

AI-powered skill recommendation engine for dotnet-harness. Analyzes project context and recommends relevant skills based on detected frameworks, packages, and patterns. Triggers on: recommend skill, suggest skills, what skill should I use, skill suggestion, project analysis recommendation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(1)

  • SKILL.md6.4 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

dotnet-harness-recommender

AI-powered skill recommendation engine that analyzes .NET project context and suggests relevant skills.

When to Use

Load this skill when:

  • Starting work on an unfamiliar project
  • Discovering what skills are available for a specific technology
  • Understanding which skills apply to detected frameworks
  • Getting contextual skill suggestions based on project analysis

Analysis Process

1. Detect Project Context

Analyzes:

  • Project files: .csproj, .sln, global.json
  • Package references: NuGet packages and versions
  • Framework targets: TFM (e.g., net8.0, netstandard2.0)
  • File patterns: Source organization and conventions

2. Map to Skills

Maps detected technologies to skill tags:

DetectedSuggested Skills
Microsoft.AspNetCore.*dotnet-minimal-apis, dotnet-api-security, dotnet-middleware-patterns
Microsoft.EntityFrameworkCore.*dotnet-efcore-patterns, dotnet-efcore-architecture
Microsoft.Maui.*dotnet-maui-development, dotnet-maui-aot
Microsoft.NET.Sdk.BlazorWebAssemblydotnet-blazor-components, dotnet-blazor-testing
Azure.*dotnet-cloud-specialist, dotnet-resilience
xunit, nunit, mstestdotnet-xunit, dotnet-testing-strategy

3. Prioritize Recommendations

Scoring factors:

  • Direct match: Package name matches skill trigger (100 points)
  • Category match: Technology category match (50 points)
  • Version compatibility: Skill supports detected TFM (25 points)
  • Usage frequency: Popular skills rank higher (10 points)

Commands

Get Recommendations

/dotnet-harness:recommend

Analyzes current project and outputs:

Recommended Skills (based on project analysis):

1. dotnet-efcore-patterns (95/100)
   Detected: Microsoft.EntityFrameworkCore 8.0.0
   Why: Core EF patterns for data access layer

2. dotnet-api-security (80/100)
   Detected: Microsoft.AspNetCore.Authentication.JwtBearer
   Why: JWT auth and API security patterns

3. dotnet-resilience (75/100)
   Detected: Polly package
   Why: Retry, circuit breaker patterns

Filter by Category

/dotnet-harness:recommend --category data
/dotnet-harness:recommend --category testing
/dotnet-harness:recommend --category security

Interactive Mode

/dotnet-harness:recommend --interactive

Guides through:

  1. Project type selection
  2. Technology stack questions
  3. Architecture pattern questions
  4. Generates prioritized skill list

Integration with Hooks

Session start hook automatically runs recommendation when:

  • New .csproj detected in workspace
  • No previous recommendations exist
  • Project dependencies changed

See .rulesync/hooks.json for implementation.

Project Pattern Detection

Web API Projects

<Project Sdk="Microsoft.NET.Sdk.Web">
  <PackageReference Include="Microsoft.AspNetCore.OpenApi" />
</Project>

Triggers: dotnet-minimal-apis, dotnet-api-versioning, dotnet-openapi

Class Library

<Project Sdk="Microsoft.NET.Sdk">
  <TargetFramework>netstandard2.0</TargetFramework>
</Project>

Triggers: dotnet-library-api-compat, dotnet-nuget-authoring

MAUI App

<Project Sdk="Microsoft.NET.Sdk">
  <UseMaui>true</UseMaui>
</Project>

Triggers: dotnet-maui-development, dotnet-maui-aot, dotnet-uno-platform

Blazor WASM

<Project Sdk="Microsoft.NET.Sdk.BlazorWebAssembly">
  <PackageReference Include="Microsoft.AspNetCore.Components.WebAssembly" />
</Project>

Triggers: dotnet-blazor-components, dotnet-blazor-testing, dotnet-aot-wasm

Console App

<Project Sdk="Microsoft.NET.Sdk">
  <OutputType>Exe</OutputType>
</Project>

Triggers: dotnet-system-commandline, dotnet-cli-architecture

Output Format

{
  "project_type": "Web API",
  "detected_frameworks": ["ASP.NET Core 8.0", "EF Core 8.0"],
  "recommendations": [
    {
      "skill": "dotnet-efcore-patterns",
      "confidence": 95,
      "reason": "Microsoft.EntityFrameworkCore detected",
      "priority": "high"
    }
  ],
  "alternatives": [
    {
      "skill": "dotnet-dapper-patterns",
      "reason": "Alternative to EF Core for performance"
    }
  ]
}

Best Practices

  • Start with top 3: Focus on highest confidence matches
  • Check version compatibility: Ensure skill supports your TFM
  • Review alternatives: Consider alternative approaches
  • Document choices: Note why specific skills were selected

Local Analysis Only

All analysis happens client-side:

  • No external API calls
  • No telemetry collection
  • No skill usage tracking
  • Results cached locally in .dotnet-harness/recommendations.json

References

  • [skill:dotnet-project-analysis] -- project context detection
  • [skill:dotnet-version-detection] -- TFM and SDK detection
  • [skill:dotnet-harness-manifest] -- skill metadata and tags

Code Navigation (Serena MCP)

Primary approach: Use Serena symbol operations for efficient code navigation:

  1. Find definitions: serena_find_symbol instead of text search
  2. Understand structure: serena_get_symbols_overview for file organization
  3. Track references: serena_find_referencing_symbols for impact analysis
  4. Precise edits: serena_replace_symbol_body for clean modifications

When to use Serena vs traditional tools:

  • Use Serena: Navigation, refactoring, dependency analysis, precise edits
  • Use Read/Grep: Reading full files, pattern matching, simple text operations
  • Fallback: If Serena unavailable, traditional tools work fine

Example workflow:

# Instead of:
Read: src/Services/OrderService.cs
Grep: "public void ProcessOrder"

# Use:
serena_find_symbol: "OrderService/ProcessOrder"
serena_get_symbols_overview: "src/Services/OrderService.cs"

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Patterns and techniques for evaluating and improving AI agent outputs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

rudironsoni/Synaxis22026년 3월 17일 업데이트

Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

rudironsoni/Synaxis22026년 3월 17일 업데이트

Use when user requests research requiring multiple sources, comprehensive analysis, or synthesis across topics - technical research, domain knowledge gathering, market analysis, or learning about complex subjects

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

rudironsoni/Synaxis22026년 3월 17일 업데이트

deep-wiki

무료

AI-powered wiki generation for code repositories with commands, agents, and skills

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

rudironsoni/Synaxis22026년 3월 17일 업데이트

Use when building .NET 10 or C# 14 applications; when using minimal APIs, modular monolith patterns, or feature folders; when implementing HTTP resilience, Options pattern, Channels, or validation; when seeing outdated patterns like old extension method syntax

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

rudironsoni/Synaxis22026년 3월 17일 업데이트

Implements accessible .NET UI. SemanticProperties, ARIA, AutomationPeer, testing per platform.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

rudironsoni/Synaxis22026년 3월 17일 업데이트

rudironsoni의 스킬 모두 보기

이 스킬의 문제 신고