stream-chain

Name: stream-chain
Availability: InStock
Author: dmccarty30

Stream outputs from one step to the next in multi-agent workflows.

4|1|Updated Jul 6, 2025

Search Tags:#automation #workflow #multi-agent #streaming #data transformation #pipeline #chaining

Ready to run

npx skills add https://github.com/Dmccarty30/Journeyman-Jobs --skill stream-chain-dmccarty30

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: stream-chain
Source: https://github.com/Dmccarty30/Journeyman-Jobs/tree/main/.claude/skills/stream-chain
Command: npx skills add https://github.com/Dmccarty30/Journeyman-Jobs --skill stream-chain-dmccarty30

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires claude-flow.

What problem does it solve?

This Skill enables sophisticated multi-step workflows where the output of one AI agent seamlessly flows as input to the next, automating complex data transformations, sequential processing, and multi-agent coordination.

Core Features & Use Cases

Custom Chains: Define and execute custom sequences of prompts for maximum flexibility.
Predefined Pipelines: Utilize battle-tested workflows for common tasks like analysis, refactoring, testing, and optimization.
Context Flow: Each step receives the complete output from the previous step, ensuring continuity.
Use Case: Run a "security audit workflow" that analyzes vulnerabilities, categorizes issues, proposes fixes, and generates security test cases in a single, automated chain.

Quick Start

Run a custom chain to "Write a user authentication function", then "Add input validation and error handling", and finally "Create unit tests with edge cases".

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 where one step's output feeds into the next?▼

Multi-agent workflow orchestration chains AI agent outputs sequentially, with each step receiving the complete result from the previous one. stream-chain automates this by streaming outputs across custom chains and predefined pipelines, enabling complex tasks like code analysis, security auditing, and data transformation in a single automated sequence.

Can I use streaming data pipelines for code analysis and security auditing workflows?▼

Yes. stream-chain supports predefined pipelines for security audits, code refactoring, testing, and optimization. It streams each agent's output to the next, maintaining context throughout. For example, run a security workflow that analyzes vulnerabilities, categorizes issues, proposes fixes, and generates test cases automatically.

What's the difference between custom chains and predefined pipelines in multi-agent workflows?▼

Custom chains let you define flexible sequences of prompts tailored to your specific workflow. Predefined pipelines are battle-tested workflows for common tasks like analysis, refactoring, and optimization. Both support context flow and streaming, so choose custom chains for unique requirements and pipelines for standard tasks.

How do I propagate context across multiple steps in a data transformation pipeline?▼

stream-chain automatically propagates per-step context, passing the complete output from each agent as input to the next. This ensures continuity across your workflow. Configure verbose, timeout, and debug options to control execution behavior and monitor context flow through your pipeline.

Can I run complex data transformations and sequential processing in one automated workflow?▼

Yes. stream-chain handles complex data transformations and sequential multi-agent processing by streaming outputs between steps. Use run mode for custom chains or pipeline mode for predefined workflows. Both support configurable options and maintain full context across all steps.

Does stream-chain work with claude-flow for building automated workflows?▼

stream-chain depends on claude-flow as its foundation. It builds on claude-flow to add multi-agent orchestration and streaming output chaining, enabling sophisticated workflows where agents collaborate sequentially with continuous context propagation.