The agent analyzes AI source code to generate structured, clear, and complete documentation in a consistent template, supporting multiple languages.

An AI pair programmer that edits code in a local Git repository using natural language, executing commands and providing feedback.

The agent is an AI-powered conversational system with memory, supporting real-time search, Wikipedia lookups, and weather updates through integrated tools.

Evaluates multiple documents and agent-generated content based on correctness, depth, clarity, and relevance, selecting the highest-scoring one. It ensures optimal document quality for research, content validation, and knowledge refinement.

The agent conducts in-depth local and web research using a language model to generate comprehensive reports with citations, aimed at delivering factual, unbiased information.

This agent automates deep web research by generating queries, gathering relevant sources, summarizing key information, and iterating on knowledge gaps to refine the results.

The agent performs comprehensive marketing strategy analysis for projects, generating detailed strategies, campaign ideas, and compelling marketing copies through a structured process involving multiple expert roles.

The agent performs AI-driven research by generating queries, gathering web data, summarizing findings, and refining results through iterative knowledge gap analysis.

The agent creates structured podcast-style dialogues optimized for AI-driven text-to-speech (TTS). It formats natural conversations with a lead speaker and an inquisitive co-host, ensuring realistic interruptions and follow-ups. The output is structured for seamless TTS integration.

The agent orchestrates a sequence of text-processing AI agents, managing the flow of information and instructions between them.

The agent autonomously breaks down tasks, assigns them to suitable agents, manages execution, evaluates outcomes, adapts workflows dynamically, and iterates until achieving an optimal solution.