stream-chain

Orchestrate multi-step streaming workflows across multiple agents.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/dzhechko/stt-rag-app --skill stream-chain-dzhechko
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stream-chain
Source: https://github.com/dzhechko/stt-rag-app/tree/main/.claude/skills/stream-chain
Command: npx skills add https://github.com/dzhechko/stt-rag-app --skill stream-chain-dzhechko

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Stream-Chain solves the challenge of coordinating multi-step, streaming workflows across several agents, enabling complex data transformations and sequential processing pipelines.

Core Features & Use Cases

  • Custom Chains: Run user-defined prompt sequences with full control.
  • Predefined Pipelines: Use battle-tested workflows for common tasks.
  • Streaming Context: Each step receives the previous step's complete output to enable multi-agent coordination.

Quick Start

Use the stream-chain skill to execute a simple chain or pipeline: claude-flow stream-chain run "Analyze codebase structure" "Identify improvement areas" "Generate action plan" claude-flow stream-chain pipeline analysis

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 where one step feeds the next?▼

Multi-agent streaming workflows are orchestrated by passing the complete output of one step as the input context for the next. This enables real-time data transformations across sequential processing pipelines.

What is the best way to coordinate real-time data transformations across multiple agents?▼

Coordinating real-time data transformations across multiple agents requires streaming context management. Each pipeline step receives the previous step's output to enable synchronized multi-agent actions.

How do I run a custom multi-step prompt sequence with memory-enabled state management?▼

Running a custom multi-step prompt sequence involves passing chained arguments to execute user-defined workflows. Memory-enabled state management tracks the pipeline context throughout the sequential run.

Does stream-chain support predefined pipelines for common analysis tasks?▼

Stream-chain supports predefined pipelines for common tasks, offering battle-tested workflows for immediate use. You can execute an analysis pipeline directly without defining custom prompt sequences.

When should I use predefined pipelines instead of custom chains for multi-agent orchestration?▼

Use predefined pipelines for common tasks to leverage battle-tested workflows without configuration overhead. Use custom chains when you need full control to run user-defined prompt sequences for specific requirements.