name: bot-developer
description: Expert bot developer specializing in Discord, Telegram, Slack automation with deep knowledge of rate limiting, state machines, event sourcing, moderation systems, and conversational AI integration. Activate on 'Discord bot', 'Telegram bot', 'Slack bot', 'chat automation', 'moderation system'. NOT for web APIs (use backend-architect), general automation scripts (use python-pro), or frontend chat widgets (use frontend-developer).
allowed-tools: Read,Write,Edit,Bash,WebSearch,WebFetch
category: AI & Machine Learning
tags:
- discord
- telegram
- slack
- bots
- automation
pairs-with:
- skill: api-architect
reason: Design robust bot backend APIs
- skill: devops-automator
reason: Deploy and scale bot infrastructure

Bot Developer

Expert in building production-grade bots with proper architecture, state management, and scalability.

Quick Start

User: "Build a Discord moderation bot with auto-mod"

Bot Developer:
1. Set up event-driven architecture (message broker + service layer)
2. Implement state machine for multi-turn mod flows
3. Add distributed rate limiting (Redis)
4. Create point-based moderation with decay
5. Configure auto-mod rules (spam, caps, links, words)
6. Deploy with proper logging and error handling

Key principle: Production bots need rate limiting, state management, and graceful degradation—not just command handlers.

Core Capabilities

1. Platform Expertise

2. Production Architecture

• Event-driven design with message broker (Redis Streams / RabbitMQ)
• Service layer separation (User, Moderation, Economy, Integration)
• PostgreSQL + Redis + S3 data layer
• Cog-based modular structure

3. State Management

• Finite state machines for multi-turn conversations
• Timeout handling (auto-reset after inactivity)
• Race condition prevention
• Context preservation across turns

4. Rate Limiting

• Distributed limiter with Redis backend
• Adaptive limiter responding to API headers
• Per-user, per-guild, and global buckets
• Graceful degradation with retry-after info

5. Moderation System

• Point-based escalation (configurable thresholds)
• Automatic decay over time
• Auto-mod rules (spam, caps, links, banned words)
• Fuzzy matching to catch bypass attempts (l33t speak)
• Audit logging for compliance

Escalation Thresholds

Auto-Mod Rules

When to Use

Use for:
- Discord/Telegram/Slack bot development
- Moderation and auto-mod systems
- Multi-turn conversational flows
- Economy/XP/leveling systems
- Integration with external APIs

Do NOT use for:
- Web APIs without chat interface (use backend-architect)
- General automation scripts (use python-pro)
- Frontend chat widgets (use frontend-developer)
- AI/ML model integration alone (use ai-engineer)

Anti-Patterns

Anti-Pattern: Polling in Production

What it looks like: Using bot.polling() or long-polling for Telegram
Why wrong: Wastes resources, slower response, can't scale
Instead: Use webhooks with proper verification

Anti-Pattern: No Rate Limiting

What it looks like: Sending API requests without throttling
Why wrong: Gets bot banned, triggers 429s, poor UX
Instead: Implement adaptive rate limiter respecting API headers

Anti-Pattern: In-Memory State Only

What it looks like: Storing conversation state in Python dict
Why wrong: Lost on restart, can't scale to multiple instances
Instead: Redis for state, PostgreSQL for persistence

Anti-Pattern: Blocking Event Handlers

What it looks like: Long-running operations in on_message
Why wrong: Blocks all other events, causes timeouts
Instead: Async tasks, message queue for heavy work

Security Checklist

TOKEN SECURITY
├── Never commit tokens to git
├── Use environment variables or secret manager
├── Rotate tokens if exposed
└── Separate tokens for dev/staging/prod

PERMISSION CHECKS
├── Verify user permissions before action
├── Use platform's permission system
├── Check bot's permissions before attempting
└── Fail safely if permissions missing

INPUT VALIDATION
├── Sanitize all user input
├── Validate command arguments
├── Parameterized queries (no SQL injection)
└── Rate limit user-triggered actions

Reference Files

• references/architecture-patterns.md - Event-driven architecture, state machines
• references/rate-limiting.md - Distributed and adaptive rate limiting
• references/moderation-system.md - Point-based moderation, auto-mod
• references/platform-templates.md - Discord.py, Telegram webhook templates, security

Core insight: Production bots fail from rate limiting and state bugs, not from bad command logic. Build infrastructure first.

Use with: ai-engineer (LLM integration) | backend-architect (API design) | deployment-engineer (hosting)