sisu-framework

Build TypeScript AI agent pipelines with middleware, typed tools, and observability.

4|2|Updated Aug 27, 2025
One-click install
npx skills add https://github.com/finger-gun/sisu --skill sisu-framework
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sisu-framework
Source: https://github.com/finger-gun/sisu/tree/main/packages/cli/sisu/assets/skills/installer
Command: npx skills add https://github.com/finger-gun/sisu --skill sisu-framework

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Sisu Framework addresses the complexity of building reliable AI agents by providing a cohesive TypeScript framework with clear middleware, typed tools, deterministic control flow, and built-in observability and safety.

Core Features & Use Cases

  • End-to-end agent pipelines with modular middleware and structured data flow.
  • Tool definitions with Zod schemas, strong type safety, and sandboxed handlers.
  • Multi-provider LLM adapters (OpenAI, Anthropic, Ollama) with tracing and debugging support.
  • Observability and safety features including tracing, error boundaries, and guardrails for production runs.

Quick Start

Install the framework and bootstrap a basic agent pipeline to begin building reliable AI agents quickly.

Frequently Asked Questions about sisu-framework

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build reliable AI agents with deterministic control flow in TypeScript?

You can build reliable AI agents using a structured TypeScript framework that provides modular middleware, typed tool definitions, and deterministic control flow to ensure predictable execution. This approach enforces type safety and structured data flow across your agent pipelines.

Does this AI agent framework support multi-provider LLM adapters for OpenAI and Anthropic?

Yes, the framework supports multi-provider LLM adapters for OpenAI, Anthropic, and Ollama. These adapters include built-in tracing and debugging support, allowing you to switch between providers while maintaining observability across your AI agents.

How do I add type safety and validation to AI agent tool definitions?

You add type safety to AI agent tool definitions by using Zod schemas within your TypeScript framework. This provides strongly typed tool inputs and outputs, paired with sandboxed handlers to ensure structured data flow and safe execution.

What is the best way to add observability and guardrails to production AI agents?

The best way to add observability and guardrails to production AI agents is by using a framework with built-in tracing, error boundaries, and safety features. This ensures transparent monitoring and deterministic flow control during production runs.

Can I use modular middleware to construct end-to-end AI agent pipelines?

Yes, you can construct end-to-end AI agent pipelines using modular middleware. This allows you to define structured data flow, apply error handling, and insert guardrails at specific stages for robust, production-ready agent behavior.