stream-chain

Orchestrate multi-agent streaming workflows connecting outputs between steps.

Updated Apr 23, 2026
One-click install
npx skills add https://github.com/fableindigo-gif/animated-system --skill stream-chain-fableindigo-gif
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stream-chain
Source: https://github.com/fableindigo-gif/animated-system/tree/main/omnianalytix-mirror/.claude/skills/stream-chain
Command: npx skills add https://github.com/fableindigo-gif/animated-system --skill stream-chain-fableindigo-gif

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates multi-agent streaming workflows to connect outputs between steps and enable complex data transformations and coordinated task automation across teams.

Core Features & Use Cases

  • Custom and predefined pipelines for flexible orchestration of multi-step tasks.
  • Memory of chain context, configurable timeouts, verbose/debug modes, and robust error handling for reliability.
  • Use cases include end-to-end data processing, code analysis workflows, and cross-team automation across software ecosystems.

Quick Start

Start a new stream-chain by providing a sequence of prompts to form a custom chain, or run a predefined pipeline for common workflows.

Frequently Asked Questions about stream-chain

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

FAQPage Schema
How do I orchestrate multi-agent pipelines for sequential task automation?▼

You can orchestrate multi-agent pipelines by connecting outputs between sequential steps to enable complex data transformations and coordinated task automation across software teams.

What is a streaming workflow and when do I need it for data transformation?▼

A streaming workflow passes data continuously through connected steps. You need it for end-to-end data processing and code analysis where outputs from one stage feed directly into the next.

How do I build a custom chain for cross-team automation workflows?▼

Build a custom chain by providing a sequence of prompts to form a connected pipeline, or run predefined pipelines for common workflows to automate tasks across software ecosystems.

Can I configure timeouts and debug logging for multi-agent orchestration?▼

Yes, multi-agent orchestration supports configurable timeouts, verbose and debug modes, robust error handling, and context memory to ensure reliable pipeline execution.

Does stream-chain work for code analysis workflows and data processing without external dependencies?▼

Yes, stream-chain operates without external dependencies to orchestrate code analysis workflows and end-to-end data processing pipelines using internal context memory and custom chains.

What are the limitations of using predefined pipelines for complex data transformations?▼

Predefined pipelines handle common workflows but may require custom chains for highly specialized data transformations, relying on configurable timeouts and context memory to manage processing limits.