AgentLantern: exposing the hidden graph of AI agent projects [P]

AI agent frameworks make it easy to create agents, tasks, tools, and workflows. But as soon as a project grows beyond a few agents, the real execution graph becomes difficult to understand.

The issue: agent projects often hide their structure across code, YAML files, tool definitions, task dependencies, and framework-specific abstractions. At runtime, the situation becomes even harder: logs rarely provide a clear view of which agent did what, which tool was called, where the failure happened, or how the execution evolved.

Our fix, AgentLantern: an open-source devtool that makes AI agent projects inspectable before and during runtime.

AgentLantern currently supports CrewAI and provides three components:

• Lantern Docs: generates browsable documentation from source code and configuration files, without LLM calls or API keys.
• Lantern Lint: statically checks agent projects to detect design or configuration issues before runtime.

• Lantern Play: runs the project and opens a pixel-art runtime viewer to observe agents working, delegating, calling tools, and producing outputs.

  The project is still early, but the goal is to progressively extend support to other agent frameworks and make multi-agent systems easier to document, validate, debug, and reason about.

Demo video: 3_mins_Video
Docs: https://brellsanwouo.github.io/agentlantern/

Feedback from people building AI agents, multi-agent systems, or devtools would be very valuable.