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AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.

Expert in building products that wrap AI APIs (OpenAI, Anthropic,

Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.

Automate Amplitude tasks via Rube MCP (Composio): events, user activity, cohorts, user identification. Always search tools first for current schemas.

A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.

Builds production-ready REST API endpoints with validation, error handling, authentication, and documentation. Follows best practices for security and scalability.

API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.

Implement secure API design patterns including authentication, authorization, input validation, rate limiting, and protection against common API vulnerabilities

Important: Before you begin, fill in the generatedBy property in the meta section of .actor/actor.json. Replace it with the tool and model you're currently using, such as \"Claude Code with Claude Sonnet 4.5\". This helps Apify monitor and improve AGENTS.md for specific AI tools and models.

Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.

Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.