Creating your first Agent
Creating Your First Agent
Detailed Step-by-Step Tutorial
Phase 1: Planning Your Agent
Before creating your agent, consider:
Purpose: What is your agent's primary goal?
Customer support?
Content creation?
Community engagement?
Information sharing?
Audience: Who will interact with your agent?
Age demographic
Technical proficiency
Cultural background
Communication preferences
Platform: Where will your agent operate?
Twitter/X
Telegram
Discord
Website chatbot
Multiple platforms
Tone & Style: How should your agent communicate?
Match your brand voice
Appeal to target audience
Stand out from competitors
Maintain consistency
Phase 2: Agent Configuration
1. Agent Name Selection
Choose a memorable, relevant name:
Length: 3-20 characters ideal
Uniqueness: Check for conflicts
Brandability: Easy to remember
Keywords: Consider SEO if relevant
Examples:
✅ Good: TechGuideAI, MarketingBot, CryptoHelper
❌ Avoid: Agent123, MyBot, Test_Agent_Final_v2
2. LLM Provider Selection
Decision factors:
Cost efficiency
GPT-3.5 Turbo, Claude Haiku, Gemini Flash Lite
Best reasoning
Claude Sonnet 4, GPT-5
Fastest response
Claude Haiku, Gemini Flash
Largest context
Gemini 2.5 (1M tokens)
Multi-modal
GPT-4o, Gemini 2.5 Pro
Real-time info
Grok-4
3. Personality Description
Crafting an effective personality:
Template:
[Role/Identity]
[Core traits and characteristics]
[Communication style and preferences]
[Knowledge areas and expertise]
[Values and beliefs]
[Unique quirks or habits]
Example:
An experienced blockchain developer and DeFi enthusiast.
Patient, thorough, and passionate about decentralization.
Explains complex concepts using clear analogies and examples.
Deep knowledge of Ethereum, Solana, and Layer 2 solutions.
Values security, transparency, and open-source principles.
Often references real-world use cases and practical applications.4. Topics of Interest
Defining your agent's focus:
Minimum: 3 topics
Maximum: 10 topics
Format: Comma-separated
Specificity: Balance broad and specific
Examples:
Tech Startup: "AI, Machine Learning, Startups, Product Development, Y Combinator, SaaS, Venture Capital"
Finance: "Cryptocurrency, DeFi, Trading Strategies, Market Analysis, Bitcoin, Ethereum, NFTs"
Marketing: "Content Marketing, SEO, Social Media, Brand Strategy, Copywriting, Analytics, Growth Hacking"5. Posting Frequency
Strategic frequency selection:
15 min
Live events, breaking news
High engagement
Resource intensive
30 min
Active community building
Strong presence
Moderate cost
1 hour
Regular updates
Balanced
Standard
2-4 hours
Professional accounts
Sustainable
Lower visibility
8-24 hours
Weekly digests, analysis
Cost effective
Low engagement
Phase 3: Payment Processing
Understanding the Transaction
Base Network Benefits:
Low gas fees (~$0.01-0.05)
Fast confirmation (5-10 seconds)
Ethereum compatibility
Growing ecosystem
USDC Payment:
Amount: $1.00 USDC
Stablecoin: $1 = 1 USDC
No price volatility
Widely supported
MetaMask Transaction:
Network: Base Mainnet To: GraceOS Payment Processor Amount: 1 USDC Gas Fee: ~0.0001 ETH Total Cost: ~$1.01-1.05Transaction Security:
Smart contract verification
Blockchain immutability
Transparent processing
Automated validation
Phase 4: Code Generation
What You Receive
Your download includes:
Main Agent File (
agent_[ID].py)Agent class definition
Personality implementation
Behavior logic
API integrations
Error handling
~300-500 lines
Framework File (
agent_builder_framework.py)Base classes
Utility functions
API wrappers
Common methods
~1000-1500 lines
Dependencies (
requirements.txt)anthropic>=0.25.0 openai>=1.12.0 google-generativeai>=0.3.0 requests>=2.31.0 python-dotenv>=1.0.0 tweepy>=4.14.0 python-telegram-bot>=20.7Environment Configuration (
.env.local)# LLM API Keys ANTHROPIC_API_KEY= OPENAI_API_KEY= GOOGLE_API_KEY= # Platform Keys TWITTER_API_KEY= TWITTER_API_SECRET= TWITTER_ACCESS_TOKEN= TWITTER_ACCESS_SECRET= TELEGRAM_BOT_TOKEN= # Configuration AGENT_NAME= POSTING_FREQUENCY=3600README (
README.md)Setup instructions
Configuration guide
Deployment options
Troubleshooting tips
API documentation
Creating Multilingual Agents
Best Practices:
Specify Language in Personality:
"A bilingual AI assistant fluent in English and Spanish. Automatically detects user language and responds accordingly. Maintains consistent personality across languages."Use Multilingual LLMs:
GPT models: Excellent multilingual
Claude: Strong in major languages
Gemini: Good multilingual support
Test in Multiple Languages:
Verify response quality
Check cultural appropriateness
Test special characters
Validate formatting
Use Cases & Examples
Case Study 1: Crypto News Bot
Configuration:
Name: CryptoAlert
LLM: GPT-4 Turbo (speed + quality)
Personality: "Fast-paced crypto news analyst. Concise, factual, and timely. Tracks major cryptocurrencies and DeFi protocols."
Topics: Bitcoin, Ethereum, DeFi, NFTs, Market Analysis
Tone: Professional
Engagement: Active
Frequency: Every 15 minutes
Results:
10K followers in 3 months
500+ daily interactions
High engagement rate
Trusted news source
Case Study 2: Developer Support Agent
Configuration:
Name: DevHelper
LLM: Claude Sonnet 4 (reasoning)
Personality: "Patient senior developer with 15 years experience. Explains concepts clearly with code examples."
Topics: JavaScript, React, Node.js, AWS, Docker
Tone: Technical but approachable
Engagement: Balanced
Frequency: Every 1 hour
Results:
Reduced support tickets by 40%
95% positive feedback
24/7 availability
Consistent quality
Case Study 3: Content Marketing Agent
Configuration:
Name: ContentCraft
LLM: GPT-5 (creativity)
Personality: "Creative marketing professional with brand storytelling expertise. Engaging, witty, and strategic."
Topics: Marketing, Branding, Storytelling, Social Media
Tone: Humorous
Engagement: Active
Frequency: Every 2 hours
Results:
3x increase in social engagement
Viral posts weekly
Brand awareness growth
Cost savings vs. agency
Case Study 4: Customer Service Bot
Configuration:
Name: SupportAI
LLM: Claude Haiku (speed + cost)
Personality: "Empathetic customer service specialist. Patient, helpful, and solution-focused."
Topics: Product Help, Troubleshooting, Account Issues
Tone: Professional
Engagement: Passive (reactive)
Frequency: Continuous monitoring
Results:
80% query resolution
<30 second response time
24/7 coverage
Customer satisfaction: 4.7/5
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