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stream-chain

Orchestrate streaming multi-agent workflows for sequential data transformations.

Updated Mar 14, 2026
Search Tags:#automation#workflow#multi-agent#streaming#orchestration#pipeline#data-transformation
One-click install
npx skills add https://github.com/novatech2210-cmd/ImidusApp --skill stream-chain-novatech2210-cmd
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stream-chain
Source: https://github.com/novatech2210-cmd/ImidusApp/tree/main/.claude/skills/stream-chain
Command: npx skills add https://github.com/novatech2210-cmd/ImidusApp --skill stream-chain-novatech2210-cmd

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Stream-chain enables orchestration of complex, multi-step data workflows by allowing outputs to flow through chained steps and across agents in real time, reducing manual coordination and latency.

Core Features & Use Cases

  • Custom Chains (run): define flexible, prompt-driven sequences where each step consumes the previous output.
  • Predefined Pipelines (pipeline): reuse battle-tested workflows for common tasks like analysis, refactor, test, and optimize.
  • State & Context: preserve complete chain history across steps and sessions for reproducibility.

Quick Start

Provide two prompts to run a custom chain and observe how outputs flow from one step to the next.

Frequently Asked Questions about stream-chain

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

FAQPage Schema
How do I orchestrate streaming multi-agent workflows for sequential data transformations?▼

You orchestrate streaming multi-agent workflows by defining custom chains or predefined pipelines where each step consumes the previous output, enabling real-time data transformations across agents.

What is the best way to chain outputs across multiple agents in a data processing pipeline?▼

Chaining outputs across multiple agents is best handled by custom chains that use prompt-driven sequences, preserving complete chain history and context across steps for reproducibility.

Can I reuse predefined pipelines for common tasks like code analysis or refactoring?▼

Yes, you can reuse predefined pipelines for common tasks like analysis, refactor, test, and optimize, applying battle-tested workflows to your data processing without building custom chains.

Does multi-agent workflow orchestration support context propagation across steps and sessions?▼

Multi-agent workflow orchestration supports context propagation by preserving complete chain history and state across steps and sessions, ensuring reproducible outcomes for complex data transformations.

What configurable options exist for debugging and controlling timeouts in a streaming pipeline?▼

Streaming pipelines expose configurable options for timeouts, verbosity, and debugging, allowing you to control execution behavior and monitor sequential data transformations during orchestration.

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