Question 1

How do I pass results between tasks in KaibanJS?

Accepted Answer

Use the `{taskResult:taskN}` syntax in task descriptions, where N is the task's position. For example, `{taskResult:task1}` references the output of the first task, enabling chained workflows. Detailed guides are in the documentation.

Question 2

KaibanJS vs LangChain.js: which should I use for AI agents?

Accepted Answer

KaibanJS is better for visual, Kanban-based orchestration of multi-agent systems with real-time monitoring, while LangChain.js offers broader tool integration and is more established. Choose KaibanJS if you prioritize workflow visualization and JavaScript-native development over ecosystem maturity.

Question 3

Can I use KaibanJS without the Kanban board UI?

Accepted Answer

Yes, KaibanJS can run headlessly via its API, allowing integration into custom UIs or backend Node.js projects. The README provides tutorials for React and Node.js integration without relying on the board.

Question 4

What AI models does KaibanJS support?

Accepted Answer

It supports multiple providers including OpenAI (e.g., GPT-4o), Anthropic (e.g., Claude 3.5 Sonnet), and Google (e.g., Gemini 1.5 Pro). You can configure different models per agent for cost and performance optimization.

Question 5

How to monitor token usage and costs in KaibanJS?

Accepted Answer

Built-in observability features track token usage, costs, and state changes through detailed logs and stats. You can subscribe to workflow logs to access metadata like `llmUsageStats` and `costDetails` for real-time insights.

Question 6

Is KaibanJS suitable for production use?

Accepted Answer

As a beta framework, it may not be fully stable for production. Consider testing thoroughly and monitoring community updates on Discord. The stability badge indicates it's still evolving, so use with caution in critical environments.

KaibanJS

What is KaibanJS?

Overview

Use Cases

Best For

Found a gem we're missing?

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions