stream-chain

Orchestrate multi-agent workflows by streaming each step's output into the next.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Stream-JSON chaining enables coordinating multi-step, interdependent tasks by passing outputs from one step to the next, unlocking complex automation and collaboration patterns.

Core Features & Use Cases

  • Custom Chains (run): Execute user-defined, sequential prompt chains where each step uses the previous output as context.
  • Predefined Pipelines (pipeline): Use battle-tested workflows for common tasks with structured steps and results.
  • Memory & Context Propagation: Preserve outputs across steps and sessions to enable continuity and traceability.
  • Use cases: Data processing pipelines, code analysis with staged prompts, and multi-step automation tasks.

Quick Start

Run a simple stream chain with two prompts to see the output flow between steps and produce a final result.

Frequently Asked Questions about stream-chain

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I coordinate multi-agent workflows by passing outputs between steps?

You can orchestrate multi-agent workflows by streaming each step's output into the next step as context. This enables complex data transformations and coordinated actions across sequential prompt chains.

What is streaming-based pipeline orchestration for automation tasks?

Streaming-based pipeline orchestration connects interdependent automation tasks by passing outputs sequentially. It allows modular definitions and contextual memory to preserve continuity and traceability across multi-step workflows.

How do I build a custom sequential prompt chain for staged code analysis?

Build a custom sequential chain by defining modular steps where each stage uses the previous output as context. This approach supports staged prompts for code analysis and structured data processing pipelines.

Can I configure timeouts and debugging options for multi-agent pipelines?

Multi-agent pipelines support configurable options for timeouts, verbosity, and debugging. These settings help manage execution flow and monitor complex data transformations across coordinated workflow steps.

Does multi-agent orchestration preserve memory and context across sessions?

Multi-agent orchestration preserves outputs across steps and sessions to enable continuity and traceability. Contextual memory propagation ensures that previous step results remain accessible throughout the workflow.

What's the best way to run predefined pipelines for common automation tasks?

Use predefined pipelines to execute battle-tested workflows for common tasks with structured steps and results. This simplifies multi-step automation by providing configured sequential chains out of the box.