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stream-chain

Orchestrate multi-agent streaming workflows by chaining outputs across successive steps.

Updated Jul 2, 2025
Search Tags:#automation#workflow#multi-agent#streaming#orchestration#pipeline#claude-flow
One-click install
npx skills add https://github.com/dug-21/neural-data-platform --skill stream-chain-dug-21
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stream-chain
Source: https://github.com/dug-21/neural-data-platform/tree/main/.claude/skills/stream-chain
Command: npx skills add https://github.com/dug-21/neural-data-platform --skill stream-chain-dug-21

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill enables orchestrating multi-agent, streaming workflows by chaining outputs across successive steps.

Core Features & Use Cases

  • Custom Chains: Run user-defined prompt sequences to connect outputs between steps.
  • Predefined Pipelines: Use ready-made workflows for common tasks like data processing and analysis.
  • Use Case: Build end-to-end pipelines where each step feeds the next, enabling complex AI-assisted automation.

Quick Start

Use the stream-chain to compose a simple chain: claude-flow stream-chain run "Analyze data" "Transform results" "Publish summary"

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 workflows for streaming data pipelines?▼

You orchestrate multi-agent workflows by chaining outputs across successive steps, feeding the result of one prompt directly into the next. This preserves context between stages and enables complex streaming data transformation.

What is the best way to chain outputs across successive AI automation steps?▼

The best way to chain outputs is using predefined pipelines or custom prompt sequences that connect step outputs automatically. This handles data transformation and automated task orchestration across development pipelines.

Do I need the Claude Flow runtime to run multi-agent streaming workflows?▼

Yes, you need the Claude Flow runtime to execute streaming workflows. It provides the environment to support configurable steps and timeouts while preserving context between chain stages.

Can I configure timeouts for individual steps in a data transformation pipeline?▼

Yes, you can configure timeouts for individual steps within your chain. The runtime supports configurable steps, allowing you to manage execution limits for automated task orchestration.

How do I build a custom chain for end-to-end data analysis and transformation?▼

You build a custom chain by running user-defined prompt sequences that connect outputs between steps, such as analyzing data, transforming results, and publishing a summary in a single streamlined command.

Does context get preserved between stages when orchestrating multi-agent tasks?▼

Yes, context is preserved between chain stages during multi-agent orchestration. This ensures that data and intermediate results flow correctly across successive steps without losing prior information.

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