The Agent Development Kit (ADK) Framework

ADK is a Python framework designed to abstract the boilerplate code required to build LLM-based agents. An agent is defined as an LLM running in a loop with access to tools. ADK provides a consistent interface for defining agents, equipping them with tools, and managing their execution flow. Key features include a CLI for local testing and a built-in web interface that provides a visual stack trace, which is critical for debugging agent reasoning and tool usage.

Equipping Agents with Tools

Agents are inherently limited by their training data cutoff. ADK allows developers to extend these capabilities by passing Python functions as tools.

  • Deterministic Tools: Simple functions, such as a get_current_time utility, allow the model to access real-time data.
  • Built-in Tools: ADK includes pre-built tools like Google Search. When using search, developers can set bypass_multiple_tools_limit to true, enabling the agent to perform multiple sequential searches to compile comprehensive answers.

Architecting Multi-Agent Systems

To improve accuracy and reduce hallucinations, developers can move beyond single-agent setups to multi-agent orchestrations. This involves using an "LLM as a judge" pattern:

  • Specialization: Create single-purpose agents (e.g., a URLVerifier agent equipped with a fetch_url tool) to validate outputs from other agents.
  • Orchestration: Equip a primary "Researcher" agent with other agents as tools. The orchestrator delegates tasks to the search agent, then passes the results to the verifier agent to confirm accuracy.
  • Strategic Advantages: This modular approach allows for better performance management. Developers can assign cheaper, faster models to simple tasks and more advanced, reasoning-heavy models to complex orchestration tasks, optimizing both latency and cost.