Go Configs & Rules
Claude Code configurations for Go projects.
Rulego
Project Rules Rule
--- name: gin-vue-admin description: | gin-vue-admin 是一个基于现代化技术栈的全栈管理系统框架。
24,281000
Rulego
Ssot Rule
122000
Rulego
E2E Script Rule
122000
Rulego
Models Rule
58000
Rulego
.Mcp Rule
{ "mcpServers": { "python-sdk": { "name": "Python SDK", "description": "Official Python SDK with FastMCP for rapid MCP development", "command": "python", "args": ["-m", "python_sdk.server"], "env": {} }, "memory-bank": { "name": "Memory Bank MCP", "description": "Centralized memory system for AI...
8000
Rulego
File Handling Uploads Rule
7000
Rulego
Hardcoded Credentials Rule
NEVER store secrets, passwords, API keys, tokens or any other credentials directly in source code.
7000
Rulego
.Mcp.Json Rule
{ "mcpServers": { "serena": { "command": "uvx", "args": [ "--from", "git+https://github.com/oraios/serena", "serena", "start-mcp-server", "--context", "ide-assistant", "--project", ".", "--enable-web-dashboard=false" ], "cwd": "." }, "kiri": { "command": "npx", "args": [ "kiri-mcp-server@latest",...
4000
Rulego
047 Protecao Dados Sensiveis Rule
Dados pessoais identificáveis (PII), dados de pagamento (PCI) e dados de saúde (HIPAA) devem ter proteções especiais incluindo criptografia, controle de acesso restrito, mascaramento em logs e conformidade com regulamentações.
4000
Rulego
Cursor.Mcp Rule
{ "mcpServers": { "scrapfly": { "command": "/root/scrapfly-mcp/scrapfly-mcp", "env": { "SCRAPFLY_API_KEY": "APIKEY" } } } }
4000
Rulego
009 Diga Nao Pergunte Rule
Exige que um método chame métodos ou acesse propriedades apenas de seus "vizinhos imediatos": o próprio objeto, objetos passados como argumento, objetos que ele cria ou objetos que são propriedades internas diretas.
4000
Rulego
Event Sourcing Rule
Every state change MUST use this pattern. No exceptions.
4000
Rulego
Pprgs Quickstart Claude Rule
The Perpetual Pursuit of Reflective Goal Steering (PPRGS) is an AI alignment framework that makes **wisdom** the terminal goal instead of utility maximization. It prevents over-optimization by requiring AI systems to balance efficiency (P₁ₐ) with exploration (P₁ᵦ).
3000