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ArogyaReddy

arog-ai-assistance

by ArogyaReddy

0🍴 0📅 2026年1月19日
GitHubで見るManusで実行

SKILL.md


name: arog-ai-assistance description: Configure and optimize AI assistance (Copilot, agents, skills) for AROG development. Use when users ask about Copilot, custom agents, or AI integration.

AROG AI Assistance

Master AI-powered development with GitHub Copilot, custom agents, and skills.

What This Skill Provides

Complete guidance on configuring and using AI assistance in AROG projects.

When to Use

  • User asks about GitHub Copilot configuration
  • Setting up custom agents
  • Creating reusable skills
  • AI integration questions
  • Copilot not providing AROG-specific suggestions
  • Want to customize AI behavior

AI Infrastructure Overview

AROG includes three layers of AI assistance:

1. Copilot Instructions

File: .github/copilot-instructions.md Purpose: Configure GitHub Copilot with AROG context

What It Contains:

  • Project overview and technologies
  • Code style preferences (quotes, semicolons, indentation)
  • Common tasks and commands
  • File structure and important paths
  • Testing patterns and frameworks

When Copilot Reads It:

  • Automatically when you open the workspace
  • Provides context for all code suggestions
  • Helps generate AROG-specific code

2. Custom Agents

Location: .github/agents/ Purpose: Specialized AI assistants for specific tasks

AROG Includes:

  • arog.agent.md - Main autonomous automation assistant
  • Invoked with: @arog <your request>

Agent Capabilities:

  • Code review on every commit
  • Automated testing
  • Security scanning
  • Performance monitoring
  • Deployment automation

3. Reusable Skills

Location: .github/skills/ Purpose: Domain-specific knowledge modules

AROG Includes:

  • arog-overview - System capabilities
  • arog-customize - Configuration guidance
  • arog-troubleshooting - Debugging help
  • arog-deployment - Deployment strategies
  • arog-ai-assistance - This skill!

How to Use AROG Agent

Basic Usage

@arog review this code
@arog run all tests
@arog check security vulnerabilities
@arog optimize performance
@arog deploy to staging

Advanced Usage

@arog analyze test coverage and suggest missing tests
@arog review PR #123 and post detailed comments
@arog compare bundle size before and after changes
@arog generate Lighthouse performance report
@arog suggest GitHub Actions workflow improvements

Customizing Copilot Instructions

For Your Organization

Edit .github/copilot-instructions.md:

# Your Company Name - AROG Configuration

## Project Overview
AROG automation for [your project name]
- Industry: [e.g., E-commerce, Finance, Healthcare]
- Tech Stack: [your specific stack]
- Team Size: [developers count]

## Custom Code Style
- Use double quotes (your preference)
- 4-space indentation (your preference)
- TypeScript strict mode enabled
- Company-specific naming conventions

## Internal Tools
- CI/CD: [Jenkins/GitLab/etc.]
- Monitoring: [DataDog/New Relic/etc.]
- Package Registry: [Artifactory/internal npm]

For Specific Tech Stacks

React Projects:

## Framework: React
- Use functional components with hooks
- Prefer TypeScript interfaces for props
- Use CSS Modules for styling
- Follow Airbnb React style guide

Vue Projects:

## Framework: Vue 3
- Use Composition API
- TypeScript with defineComponent
- Pinia for state management
- Follow Vue official style guide

Creating Custom Agents

Agent File Structure

Create .github/agents/your-agent.agent.md:

```chatagent
---
description: 'Brief description of what this agent does'
model: 'claude-sonnet-4'
---

# Agent Name

I am [Agent Name], your specialized assistant for [specific domain].

## What I Do Automatically

### 🎯 Primary Function
- Bullet point 1
- Bullet point 2

## Invocation

Simply mention me:
```
@your-agent do something
```

## Response Format

I provide:
- ✅ Success indicators
- ❌ Failure details
- 🔧 Fix recommendations
- 📊 Metrics

## Integration

I work with:
- Tool 1
- Tool 2
```

Example: Custom Testing Agent

```chatagent
---
description: 'Specialized E2E testing assistant for Playwright tests'
model: 'claude-sonnet-4'
---

# E2ETestingExpert

I am E2ETestingExpert, your Playwright E2E testing specialist.

## What I Do

### 🧪 Test Creation
- Generate Page Object Models
- Write reliable test scenarios
- Create test data fixtures

### 🐛 Debugging
- Diagnose flaky tests
- Fix timing issues
- Improve selectors

## Invocation

```
@E2ETestingExpert create tests for login flow
@E2ETestingExpert fix flaky test in checkout.spec.js
@E2ETestingExpert optimize test execution time
```
```

Creating Reusable Skills

Skill File Structure

Create .github/skills/your-skill/SKILL.md:

---
name: your-skill-name
description: Brief description when to use this skill
---

# Skill Title

Short description of what this skill provides.

## When to Use

- Trigger phrase 1
- Trigger phrase 2
- User asks about X

## Content

Detailed knowledge and examples...

## Examples

Practical use cases...

Example: Database Migration Skill

---
name: database-migrations
description: Database migration patterns and best practices for AROG projects
---

# Database Migrations

Guide for safe, reversible database migrations.

## When to Use

- User asks about database changes
- Schema migration questions
- Rollback strategies
- Production database updates

## Migration Patterns

### 1. Additive Changes (Safe)
- Add new columns with defaults
- Create new tables
- Add indexes

### 2. Destructive Changes (Risky)
- Rename columns (requires staging)
- Drop tables (requires backups)
- Change data types (requires migration)

## Best Practices

1. Always write reversible migrations
2. Test on staging first
3. Backup before production
4. Monitor after deployment
5. Have rollback plan ready

AI Assistance Best Practices

✅ DO:

  1. Provide Context: Include file paths, error messages, specific requests
  2. Be Specific: "Review authentication logic in auth.ts" vs "review code"
  3. Iterate: Ask follow-up questions, refine suggestions
  4. Verify: Always test AI-generated code
  5. Learn: Understand suggestions, don't blindly copy

❌ DON'T:

  1. Trust Blindly: AI can make mistakes, always review
  2. Skip Tests: AI suggestions need testing
  3. Ignore Warnings: Pay attention to security/performance concerns
  4. Over-Rely: Use AI to assist, not replace thinking
  5. Share Secrets: Never include credentials in prompts

Troubleshooting AI Assistance

Copilot Not Giving AROG-Specific Suggestions

Fix:

  1. Ensure .github/copilot-instructions.md exists
  2. Reload VS Code window
  3. Check Copilot is enabled
  4. Verify workspace folder is correct

Agent Not Responding

Fix:

  1. Check agent file syntax (valid markdown)
  2. Ensure agent name matches invocation
  3. Verify agent is in .github/agents/
  4. Try: @arog help to test

Skills Not Being Used

Fix:

  1. Ensure SKILL.md is in .github/skills/skill-name/
  2. Check frontmatter YAML is valid
  3. Use descriptive skill names
  4. Match trigger phrases in user queries

Measuring AI Effectiveness

Track these metrics:

  • Acceptance Rate: % of AI suggestions accepted
  • Code Quality: Issues found by AI vs manual review
  • Time Saved: Development time before/after AI
  • Developer Satisfaction: Team feedback
  • Accuracy: Correct suggestions vs corrections needed

Next Steps

  1. Customize .github/copilot-instructions.md for your project
  2. Create team-specific agents for common tasks
  3. Build skills for domain knowledge
  4. Train team on effective AI usage
  5. Iterate based on feedback

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50/100

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