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stream-chain

Stream outputs between sequential steps in multi-agent workflows.

Updated Aug 23, 2026
Search Tags:#workflow#multi-agent#orchestration#prompts#pipelines#data-flow#stream
One-click install
npx skills add https://github.com/JLMA-Agentic-Ai/ruv_downloads --skill stream-chain-jlma-agentic-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stream-chain
Source: https://github.com/JLMA-Agentic-Ai/ruv_downloads/tree/main/.claude/skills/stream-chain
Command: npx skills add https://github.com/JLMA-Agentic-Ai/ruv_downloads --skill stream-chain-jlma-agentic-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates complex, multi-step workflows by streaming outputs between sequential steps, reducing manual hand-offs and orchestration overhead.

Core Features & Use Cases

  • Two-Mode Orchestration: run custom chains with user-defined prompts and predefined pipelines for common tasks.
  • Contextful Coordination: propagates complete outputs between steps to enable dependent transformations.
  • Flexible Configuration: supports memory integration, optional tools, and collaborative agent coordination for scalable automation.

Quick Start

Run a two-step chain to see streaming 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 coordinate multi-agent workflows with streaming data between steps?▼

Multi-agent workflow coordination streams sequential outputs between steps to automate complex tasks. It propagates complete context between dependent transformations, reducing manual hand-offs and orchestration overhead for data processing pipelines.

What is the best way to build automated task pipelines that share dynamic context?▼

Automated task pipelines use custom chains with user-defined prompts to share dynamic context. This approach propagates complete outputs between sequential steps, enabling dependent transformations for scalable automation without manual intervention.

Can I use predefined pipelines for common code analysis and data processing tasks?▼

Predefined pipelines support common code analysis and data processing tasks directly. The orchestration operates in two modes, allowing you to run predefined pipelines or configure custom chains with user-defined prompts for specific automation needs.

Does multi-agent orchestration support configurable timeouts and memory integration?▼

Multi-agent orchestration supports configurable timeouts, verbosity settings, and optional memory integration. These flexible configuration options allow collaborative agent coordination and scalable automation for complex, multi-step task pipelines.

When do I need streaming outputs for multi-step automation tasks?▼

Streaming outputs are needed for multi-step automation tasks requiring coordinated prompts and dynamic context sharing. This mechanism applies to complex workflows like code analysis and data processing where sequential steps depend on previous outputs.

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