stream-chain

Stream outputs between agents to orchestrate sequential multi-agent workflows.

Updated Jan 7, 2026
One-click install
npx skills add https://github.com/Aktoh-Cyber/agent-control-plane --skill stream-chain-aktoh-cyber
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: stream-chain
Source: https://github.com/Aktoh-Cyber/agent-control-plane/tree/main/.claude/skills/stream-chain
Command: npx skills add https://github.com/Aktoh-Cyber/agent-control-plane --skill stream-chain-aktoh-cyber

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Stream-JSON chaining enables orchestration of multi-agent workflows by routing and streaming outputs between agents, eliminating manual handoffs in complex pipelines.

Core Features & Use Cases

  • Two operational modes: Custom Chains (run) and Predefined Pipelines (pipeline)
  • Streaming context across steps enables sophisticated multi-agent coordination and data transformation
  • Memory integration and governance hooks for enterprise-grade workflows
  • Use Cases: codebase analysis, data processing, automation orchestrations across organizations

Quick Start

Create a basic two-step chain by running stream-chain run 'Define task' 'Execute with review'.

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 with streaming outputs?

Multi-agent workflows can be orchestrated by streaming outputs between agents to enable sequential data transformation. This eliminates manual handoffs by routing results from one agent directly into the next step of the pipeline.

What is the best way to chain multiple agents for sequential data transformation?

Sequential data transformation is best handled by streaming context across steps, allowing sophisticated multi-agent coordination. You can use custom chains for flexible routing or predefined pipelines for standardized operations.

Can I use predefined pipelines instead of custom chains for automation tasks?

Predefined pipelines are fully supported for automation tasks alongside custom chains. You can use the pipeline operational mode for standardized workflows or the run mode to build custom chains tailored to specific processing needs.

Does multi-agent orchestration preserve context across processing steps?

Multi-agent orchestration preserves context across steps by integrating memory capabilities. This ensures that each agent in the workflow maintains access to previous results, enabling sophisticated data transformation without losing intermediate state.

How do I start building a two-step chain for codebase analysis?

Building a two-step chain for codebase analysis starts by running a command with a defined task and an execution step. This routes the initial output directly into the next agent for review or further processing.

Are there governance hooks for enterprise-grade multi-agent workflows?

Enterprise-grade multi-agent workflows include governance hooks and memory integration. These features provide logging and oversight capabilities essential for complex automation orchestrations across organizations.