| Dimension | Shared | Only in A | Only in B | Overlap |
|---|---|---|---|---|
| Sections | 0 | 14 | 8 | 0% |
| Commands | 0 | 3 | 0 | 0% |
| Section tags | 2 | 5 | 3 | 20% |
What each file covers
Sections
0 shared · 14 only in A · 8 only in B- − Development Guidelines
- − Technology Stack
- − When Source Code is Added
- − Always verify package.json exists first
- − Install dependencies with appropriate timeout
- − Build with extended timeout for AI projects
- − Run tests with adequate time
- − Build with reasonable timeout for most projects
- − AI Integration Best Practices
- − Preferred AI Dependencies
- − Code Organization
- − Error Handling Pattern
- − File Structure Standards
- − Development Workflow
- + AI Development Best Practices
- + AI-First Development Principles
- + 1. API Integration Patterns
- + 2. Preferred AI Integration Pattern
- + 3. Recommended AI Dependencies
- + 4. Response Handling Best Practices
- + 5. Performance Optimization
- + 6. User Experience Guidelines
Commands
0 shared · 3 only in A · 0 only in B- − npm install
- − npm run build
- − npm test
Section tags
2 shared · 5 only in A · 3 only in B- − setup
- − build
- − test
- − architecture
- − agent-behaviour
- + security
- + api
- + performance
- code-style
- dependencies
Line diff
HerringtonDarkholme/megarepo · .clinerules/02-development.md
@@ −1 @@
1# Development Guidelines
2
3## Technology Stack
4This repository is pre-configured for **Node.js/Next.js development** with AI integrations.
5
6### When Source Code is Added
7Follow these patterns based on existing repository guidelines:
8
9```bash
10# Always verify package.json exists first
11test -f package.json && echo "Node.js project detected" || echo "No package.json found"
12
13# Install dependencies with appropriate timeout
14npm install # Allow 10+ minutes for completion
15
16# Build with extended timeout for AI projects
17npm run build # Allow 60+ minutes - AI projects can have complex builds
18
19# Run tests with adequate time
20npm test # Allow 30+ minutes for comprehensive test suites
21```
22# Build with reasonable timeout for most projects
23npm run build # Allow 15-30 minutes for most Node.js/Next.js builds with AI integrations
24
25# Run tests with adequate time
26npm test # Allow 30+ minutes for comprehensive test suites
27## AI Integration Best Practices
28
29### Preferred AI Dependencies
30When adding AI functionality, use these established packages:
31- `openai` - Official OpenAI API client
32- `@langchain/core` - LangChain framework for AI workflows
33- `@vercel/ai` - Vercel AI SDK for streaming and UI integration
34- `@huggingface/inference` - Hugging Face API client
35- `@anthropic-ai/sdk` - Anthropic Claude API client
36
37### Code Organization
38- Place AI client configurations in `src/lib/` directory
39- Create reusable AI components in `src/components/ai/`
40- Implement API routes for AI services in `src/app/api/` (Next.js App Router)
41- Define TypeScript types for AI responses in `src/types/`
42
43### Error Handling Pattern
44```javascript
45// Implement comprehensive error handling for AI services
46try {
47 const response = await aiClient.chat.completions.create({
48 model: "gpt-4",
49 messages: [{ role: "user", content: prompt }]
50 });
51 return response.choices[0].message.content;
52} catch (error) {
53 if (error.code === 'rate_limit_exceeded') {
54 throw new AIRateLimitError('Rate limit exceeded, please try again later');
55 }
56 if (error.code === 'insufficient_quota') {
57 throw new AIQuotaError('API quota exceeded');
58 }
59 throw new AIServiceError(`AI service failed: ${error.message}`);
60}
61```
62
63## File Structure Standards
64Follow the established minimal structure and expand thoughtfully:
65
66```
67.
68├── .clinerules/ # Cline AI rules (this directory)
69├── .github/ # GitHub workflows and Copilot instructions
70├── .kiro/steering/ # Kiro AI steering files
71├── .cursorrules # Cursor AI development rules
72├── CLAUDE.md # Claude AI specific configuration
73├── GEMINI.md # Gemini CLI configuration
74├── AGENT.md # Universal AI agent instructions
75├── package.json # Dependencies and scripts (when added)
76├── src/ # Source code (when added)
77│ ├── lib/ # AI clients and utilities
78│ ├── components/ # React components including AI components
79│ ├── app/ # Next.js App Router (pages and API routes)
80│ └── types/ # TypeScript definitions
81└── public/ # Static assets
82```
83
84## Development Workflow
851. **Before Changes**: Check repository state and existing patterns
862. **During Development**: Follow TypeScript best practices and AI patterns
873. **Testing**: Include AI service mocks and error scenario testing
884. **Documentation**: Update relevant AI configuration files as needed
HerringtonDarkholme/megarepo · .cursor/rules/ai-development.mdc
@@ +1 @@
1---
2description: "Core AI development patterns and best practices for the Megarepo AI setup repository"
3globs: ["src/**/*", "app/**/*", "pages/**/*"]
4alwaysApply: true
5---
6
7# AI Development Best Practices
8
9You are working on an AI-focused development project. Follow these core principles for AI integration:
10
11## AI-First Development Principles
12
13### 1. API Integration Patterns
14- Use modern async/await patterns for all AI API calls
15- Implement comprehensive error handling for AI service failures
16- Consider token usage and model performance optimization
17- Design for scalability with AI workloads
18
19### 2. Preferred AI Integration Pattern
20```javascript
21const aiResponse = await fetch('/api/ai-service', {
22 method: 'POST',
23 headers: {
24 'Content-Type': 'application/json',
25 'Authorization': `Bearer ${process.env.AI_API_KEY}`
26 },
27 body: JSON.stringify({ prompt, options })
28});
29
30if (!aiResponse.ok) {
31 throw new Error(`AI service error: ${aiResponse.status}`);
32}
33```
34
35### 3. Recommended AI Dependencies
36When adding AI functionality, prefer these established packages:
37- `openai` - Official OpenAI API client
38- `@langchain/core` - LangChain framework
39- `@vercel/ai` - Vercel AI SDK
40- `@huggingface/inference` - Hugging Face API client
41
42### 4. Response Handling Best Practices
43- Always validate AI responses before using them
44- Implement fallback mechanisms for failed requests
45- Log AI interactions for debugging and monitoring
46- Handle streaming responses appropriately
47
48### 5. Performance Optimization
49- Cache AI responses when appropriate
50- Implement request debouncing for user inputs
51- Use background processing for long-running AI tasks
52- Consider edge functions for AI API proxying
53
54### 6. User Experience Guidelines
55- Provide clear loading indicators for AI operations
56- Implement progressive disclosure for complex AI features
57- Give users control over AI behavior and settings
58- Provide feedback mechanisms for AI output quality
@@ −1 +1 @@
1−# Development Guidelines
1+---
2+description: "Core AI development patterns and best practices for the Megarepo AI setup repository"
3+globs: ["src/**/*", "app/**/*", "pages/**/*"]
4+alwaysApply: true
5+---
26
3−## Technology Stack
4−This repository is pre-configured for **Node.js/Next.js development** with AI integrations.
7+# AI Development Best Practices
58
6−### When Source Code is Added
7−Follow these patterns based on existing repository guidelines:
9+You are working on an AI-focused development project. Follow these core principles for AI integration:
810
9−```bash
10−# Always verify package.json exists first
11−test -f package.json && echo "Node.js project detected" || echo "No package.json found"
11+## AI-First Development Principles
1212
13−# Install dependencies with appropriate timeout
14−npm install # Allow 10+ minutes for completion
13+### 1. API Integration Patterns
14+- Use modern async/await patterns for all AI API calls
15+- Implement comprehensive error handling for AI service failures
16+- Consider token usage and model performance optimization
17+- Design for scalability with AI workloads
1518
16−# Build with extended timeout for AI projects
17−npm run build # Allow 60+ minutes - AI projects can have complex builds
19+### 2. Preferred AI Integration Pattern
20+```javascript
21+const aiResponse = await fetch('/api/ai-service', {
22+ method: 'POST',
23+ headers: {
24+ 'Content-Type': 'application/json',
25+ 'Authorization': `Bearer ${process.env.AI_API_KEY}`
26+ },
27+ body: JSON.stringify({ prompt, options })
28+});
1829
19−# Run tests with adequate time
20−npm test # Allow 30+ minutes for comprehensive test suites
30+if (!aiResponse.ok) {
31+ throw new Error(`AI service error: ${aiResponse.status}`);
32+}
2133 ```
22−# Build with reasonable timeout for most projects
23−npm run build # Allow 15-30 minutes for most Node.js/Next.js builds with AI integrations
2434
25−# Run tests with adequate time
26−npm test # Allow 30+ minutes for comprehensive test suites
27−## AI Integration Best Practices
28−
29−### Preferred AI Dependencies
30−When adding AI functionality, use these established packages:
35+### 3. Recommended AI Dependencies
36+When adding AI functionality, prefer these established packages:
3137 - `openai` - Official OpenAI API client
32−- `@langchain/core` - LangChain framework for AI workflows
33−- `@vercel/ai` - Vercel AI SDK for streaming and UI integration
38+- `@langchain/core` - LangChain framework
39+- `@vercel/ai` - Vercel AI SDK
3440 - `@huggingface/inference` - Hugging Face API client
35−- `@anthropic-ai/sdk` - Anthropic Claude API client
3641
37−### Code Organization
38−- Place AI client configurations in `src/lib/` directory
39−- Create reusable AI components in `src/components/ai/`
40−- Implement API routes for AI services in `src/app/api/` (Next.js App Router)
41−- Define TypeScript types for AI responses in `src/types/`
42+### 4. Response Handling Best Practices
43+- Always validate AI responses before using them
44+- Implement fallback mechanisms for failed requests
45+- Log AI interactions for debugging and monitoring
46+- Handle streaming responses appropriately
4247
43−### Error Handling Pattern
44−```javascript
45−// Implement comprehensive error handling for AI services
46−try {
47− const response = await aiClient.chat.completions.create({
48− model: "gpt-4",
49− messages: [{ role: "user", content: prompt }]
50− });
51− return response.choices[0].message.content;
52−} catch (error) {
53− if (error.code === 'rate_limit_exceeded') {
54− throw new AIRateLimitError('Rate limit exceeded, please try again later');
55− }
56− if (error.code === 'insufficient_quota') {
57− throw new AIQuotaError('API quota exceeded');
58− }
59− throw new AIServiceError(`AI service failed: ${error.message}`);
60−}
61−```
48+### 5. Performance Optimization
49+- Cache AI responses when appropriate
50+- Implement request debouncing for user inputs
51+- Use background processing for long-running AI tasks
52+- Consider edge functions for AI API proxying
6253
63−## File Structure Standards
64−Follow the established minimal structure and expand thoughtfully:
65−
66−```
67−.
68−├── .clinerules/ # Cline AI rules (this directory)
69−├── .github/ # GitHub workflows and Copilot instructions
70−├── .kiro/steering/ # Kiro AI steering files
71−├── .cursorrules # Cursor AI development rules
72−├── CLAUDE.md # Claude AI specific configuration
73−├── GEMINI.md # Gemini CLI configuration
74−├── AGENT.md # Universal AI agent instructions
75−├── package.json # Dependencies and scripts (when added)
76−├── src/ # Source code (when added)
77−│ ├── lib/ # AI clients and utilities
78−│ ├── components/ # React components including AI components
79−│ ├── app/ # Next.js App Router (pages and API routes)
80−│ └── types/ # TypeScript definitions
81−└── public/ # Static assets
82−```
83−
84−## Development Workflow
85−1. **Before Changes**: Check repository state and existing patterns
86−2. **During Development**: Follow TypeScript best practices and AI patterns
87−3. **Testing**: Include AI service mocks and error scenario testing
88−4. **Documentation**: Update relevant AI configuration files as needed
54+### 6. User Experience Guidelines
55+- Provide clear loading indicators for AI operations
56+- Implement progressive disclosure for complex AI features
57+- Give users control over AI behavior and settings
58+- Provide feedback mechanisms for AI output quality
