Social Media AI Automation
Budget: $100 – $150 USD
CLAUDE AGENTS
A Claude Code Project
Project Overview
When prompted with task:
● The purpose of this system is to have AI Agents fully automated to Post, Comment, &
even reply to people on social media platforms, without replying spam/bot
messages.
● We need the automized agent to respond based on the input its given (etc; if it was
replied too, or got a direct message)
● Agents should be able to invite people to discord groups, subreddits & anything that
has to do with inviting for exclusive purposes
● Agents need to populate our following on (Instagram, twitter, and linkedin, discord)
as well as inviting to our groups and making our network bigger
● We do not want to approve everything it asks, this needs to be set on a campaign
level where we tell it to run a 20 hour campaign… it runs without questions
Core Objectives
• Monitor (Whatever project we’re on) related activity and sentiment across social media
platforms.
• Analyze live token and blockchain data from public market sources.
• Generate context-aware responses and engagement suggestions.
• Produce periodic analytics summaries and reporting dashboards.
• Have fully automized agents that can have full control of social media platforms.
● Each agent created should have 40 - 60 Interactions an hour
● Total of 300 Interactions an hour
● Low Enough to not flag spam
Primary Data Sources
DexScreener — Real-time token price, liquidity, volume, and trading activity.
GeckoTerminal — Pool analytics, charts, and token monitoring.
DexView — DEX aggregation and additional market visibility.
Basescan — On-chain contract analysis, transfers, wallet activity, and holder information.
Platform Integration Goals
These agents needs to have full control (Posting, commenting, inviting, replying,
liking, joining communities/subreddits, & following accounts) Social medias:
● X/Twitter
● Discord
● Reddit
● Telegram
● Bitcointalk
● Seemit
The AI system should be capable of:
● Populating our social media accounts through invites (Subreddits & Discord)
● Messaging/ DM to users about our other social media accounts (Instagram,
Twitter, Linkedin) Once interacted with already.
● Reading contextual conversations
● Understanding sentiment and intent
● Suggesting or generating relevant replies
● Posting scheduled updates
● Producing engagement summaries
AI Interaction Design
The AI interaction engine should focus on generating natural, context-aware communication
rather than repetitive automation. The system should analyze incoming comments or direct
messages and formulate responses using available market data, sentiment analysis, and
previous conversation context.
Key educational concepts explored:
• Conversational AI
• Sentiment analysis
• Multi-agent coordination
• Social media analytics
• Ethical AI deployment
• Human-AI interaction modeling
Infrastructure Requirements
The project may utilize cloud or VPS infrastructure to support persistent uptime for
demonstrations and testing. Suggested infrastructure includes:
• VPS hosting environment
• Multi-session browser automation framework
• Logging and analytics system
• Automated reporting scheduler
• Centralized dashboard for monitoring interactions
Reporting & Analytics
The system should generate automated reports every 10 hours summarizing:
• Posts created
• Community interactions
• Platform engagement metrics
• Sentiment trends
• Data source observations
• General system activity
A Claude Code Project
Project Overview
When prompted with task:
● The purpose of this system is to have AI Agents fully automated to Post, Comment, &
even reply to people on social media platforms, without replying spam/bot
messages.
● We need the automized agent to respond based on the input its given (etc; if it was
replied too, or got a direct message)
● Agents should be able to invite people to discord groups, subreddits & anything that
has to do with inviting for exclusive purposes
● Agents need to populate our following on (Instagram, twitter, and linkedin, discord)
as well as inviting to our groups and making our network bigger
● We do not want to approve everything it asks, this needs to be set on a campaign
level where we tell it to run a 20 hour campaign… it runs without questions
Core Objectives
• Monitor (Whatever project we’re on) related activity and sentiment across social media
platforms.
• Analyze live token and blockchain data from public market sources.
• Generate context-aware responses and engagement suggestions.
• Produce periodic analytics summaries and reporting dashboards.
• Have fully automized agents that can have full control of social media platforms.
● Each agent created should have 40 - 60 Interactions an hour
● Total of 300 Interactions an hour
● Low Enough to not flag spam
Primary Data Sources
DexScreener — Real-time token price, liquidity, volume, and trading activity.
GeckoTerminal — Pool analytics, charts, and token monitoring.
DexView — DEX aggregation and additional market visibility.
Basescan — On-chain contract analysis, transfers, wallet activity, and holder information.
Platform Integration Goals
These agents needs to have full control (Posting, commenting, inviting, replying,
liking, joining communities/subreddits, & following accounts) Social medias:
● X/Twitter
● Discord
● Telegram
● Bitcointalk
● Seemit
The AI system should be capable of:
● Populating our social media accounts through invites (Subreddits & Discord)
● Messaging/ DM to users about our other social media accounts (Instagram,
Twitter, Linkedin) Once interacted with already.
● Reading contextual conversations
● Understanding sentiment and intent
● Suggesting or generating relevant replies
● Posting scheduled updates
● Producing engagement summaries
AI Interaction Design
The AI interaction engine should focus on generating natural, context-aware communication
rather than repetitive automation. The system should analyze incoming comments or direct
messages and formulate responses using available market data, sentiment analysis, and
previous conversation context.
Key educational concepts explored:
• Conversational AI
• Sentiment analysis
• Multi-agent coordination
• Social media analytics
• Ethical AI deployment
• Human-AI interaction modeling
Infrastructure Requirements
The project may utilize cloud or VPS infrastructure to support persistent uptime for
demonstrations and testing. Suggested infrastructure includes:
• VPS hosting environment
• Multi-session browser automation framework
• Logging and analytics system
• Automated reporting scheduler
• Centralized dashboard for monitoring interactions
Reporting & Analytics
The system should generate automated reports every 10 hours summarizing:
• Posts created
• Community interactions
• Platform engagement metrics
• Sentiment trends
• Data source observations
• General system activity