stream-chain

Orchestrate multi-agent workflows with JSON chaining for data transformation.

Updated Jun 5, 2026
One-click install
npx skills add https://github.com/LGugui/cerebro-template --skill stream-chain-lgugui
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stream-chain
Source: https://github.com/LGugui/cerebro-template/tree/main/.claude/skills/stream-chain
Command: npx skills add https://github.com/LGugui/cerebro-template --skill stream-chain-lgugui

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill addresses the complexity of orchestrating multi-agent workflows by providing a streamlined approach to data transformation and sequential processing.

Core Features & Use Cases

  • Custom Chains: Execute custom prompt sequences for maximum flexibility in workflow design.
  • Predefined Pipelines: Utilize battle-tested workflows for common tasks like code analysis, refactoring, testing, and optimization.
  • Multi-Agent Coordination: Facilitates sophisticated multi-agent coordination through streaming data flow.
  • Data Transformation: Enables complex data transformations and sequential processing pipelines.
  • Use Case: For a software development team, this Skill can automate a complex workflow such as analyzing codebase structure, identifying improvement areas, and generating an action plan.

Quick Start

To run a custom chain, use the command: claude-flow stream-chain run "Analyze codebase structure" "Identify improvement areas" "Generate action plan"

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 sequential code analysis?▼

You can orchestrate multi-agent workflows for sequential code analysis by running custom JSON chains that stream transformed data between agents. This allows you to execute prompt sequences like analyzing a codebase, identifying improvements, and generating an action plan in one streamlined process.

What is JSON chaining for data transformation in software engineering?▼

JSON chaining for data transformation is a mechanism that streams data sequentially between multiple agents in a workflow. It enables complex transformations by passing the structured output of one processing step directly as the input context for the next.

Can I run custom prompt sequences for codebase refactoring and optimization?▼

Yes, you can run custom prompt sequences for codebase refactoring and optimization by defining custom chains. This provides maximum flexibility to execute tailored multi-agent workflows for specific development tasks beyond predefined pipelines.

Do I need context management capabilities to use predefined development pipelines?▼

Yes, context management and data streaming capabilities are required to use predefined pipelines. These features are necessary to facilitate the sophisticated multi-agent coordination and sequential data flow that the pipelines rely on.

Best way to automate a workflow from code analysis to generating an action plan?▼

The best way to automate this workflow is using a predefined pipeline or a custom chain command that sequentially processes tasks. You can stream the codebase structure analysis directly into the improvement identification step, and then into the action plan generation.