AIVibe - AI Agent Training Package

AIVibe is the comprehensive AI agent training package for VibeKaro.ai - the AI-powered full-stack development platform. This package contains complete knowledge modules for training AI agents with production-grade coding standards.

Features

• Complete Flutter/Dart Knowledge - Latest Flutter 3.24+, Dart 3.5+ standards
• Multi-Platform Support - iOS SDK 26+, Android API 36, Web hybrid
• Backend Expertise - Kotlin, Python, JavaScript, PostgreSQL
• Cloud Services - AWS, Google Cloud, Firebase integration patterns
• SDLC Framework - 10-phase waterfall model with agent roles
• Coding Standards - Zero-tolerance, production-ready patterns
• Auto-Training - Daily scheduled training with evaluation
• Scorecard System - Training effectiveness tracking

Installation

pip install aivibe

Quick Start

Train AI Agent

from aivibe import AIVibeTrainer

trainer = AIVibeTrainer()
result = trainer.train_agent("aikutty")
print(f"Training Score: {result.score}%")

Schedule Daily Training

aivibe-schedule --agent aikutty --time 02:00

Evaluate Agent Knowledge

aivibe-evaluate --agent aikutty --output scorecard.json

Knowledge Modules

Agent Roles by SDLC Phase

Coding Standards

Zero-Tolerance Policy

• No lint errors or warnings
• No type mismatches
• No deprecated dependencies
• No duplicate code
• Complete error handling
• Full documentation

Naming Conventions

• camelCase for variables and functions
• PascalCase for classes and types
• snake_case for file names
• SCREAMING_SNAKE_CASE for constants

Training Evaluation

Training sessions are evaluated on:

1. Syntax Correctness (25%) - Code compiles without errors
2. Best Practices (25%) - Follows recommended patterns
3. Security Compliance (20%) - No vulnerabilities
4. Performance (15%) - Optimized code
5. Documentation (15%) - Complete dartdocs

Configuration

Create aivibe.yaml in your project:

agent: aikutty
schedule:
  enabled: true
  time: "02:00"
  timezone: "UTC"
evaluation:
  min_score: 85
  report_path: ./reports/
training:
  modules:
    - flutter
    - dart
    - aws
    - sdlc

API Reference

AIVibeTrainer

class AIVibeTrainer:
    def train_agent(self, agent_name: str, modules: list = None) -> TrainingResult
    def evaluate_agent(self, agent_name: str) -> EvaluationResult
    def get_scorecard(self, agent_name: str) -> Scorecard
    def schedule_training(self, agent_name: str, cron: str) -> None

TrainingResult

@dataclass
class TrainingResult:
    agent: str
    score: float
    modules_trained: list[str]
    duration_seconds: float
    timestamp: datetime
    details: dict

License

MIT License - See LICENSE for details.

Support

• Documentation: https://docs.vibekaro.ai
• Issues: https://github.com/aicippy/aivibe/issues
• Email: support@vibekaro.ai

Built with excellence by AICippy Technologies for VibeKaro.ai