์Šคํ‚ฌ when-chaining-agent-pipelines-use-stream-chain
๐Ÿ”—

when-chaining-agent-pipelines-use-stream-chain

์•ˆ์ „ โšก ์Šคํฌ๋ฆฝํŠธ ํฌํ•จ๐ŸŒ ๋„คํŠธ์›Œํฌ ์ ‘๊ทผ๐Ÿ“ ํŒŒ์ผ ์‹œ์Šคํ…œ ์•ก์„ธ์Šค๐Ÿ”‘ ํ™˜๊ฒฝ ๋ณ€์ˆ˜โš™๏ธ ์™ธ๋ถ€ ๋ช…๋ น์–ด

Chain Agent Pipelines with Stream Processing

Build complex multi-agent workflows where each agents output flows seamlessly to the next. Stream-chain orchestrates sequential and parallel pipelines with real-time data flow monitoring.

์ง€์›: Claude Codex Code(CC)
๐Ÿ“Š 70 ์ ์ ˆํ•จ
1

์Šคํ‚ฌ ZIP ๋‹ค์šด๋กœ๋“œ

2

Claude์—์„œ ์—…๋กœ๋“œ

์„ค์ • โ†’ ๊ธฐ๋Šฅ โ†’ ์Šคํ‚ฌ โ†’ ์Šคํ‚ฌ ์—…๋กœ๋“œ๋กœ ์ด๋™

3

ํ† ๊ธ€์„ ์ผœ๊ณ  ์‚ฌ์šฉ ์‹œ์ž‘

ํ…Œ์ŠคํŠธํ•ด ๋ณด๊ธฐ

"when-chaining-agent-pipelines-use-stream-chain" ์‚ฌ์šฉ ์ค‘์ž…๋‹ˆ๋‹ค. Design a research pipeline for market analysis with 5 stages

์˜ˆ์ƒ ๊ฒฐ๊ณผ:

  • Pipeline Design: research, data-collection, analysis, synthesis, reporting
  • Stage 1 (Research): Defines scope and objectives
  • Stage 2 (Data Collection): Gathers market data via parallel agents
  • Stage 3 (Analysis): Processes data with 3 parallel analyzers
  • Stage 4 (Synthesis): Combines analysis results
  • Stage 5 (Reporting): Creates final market report
  • Throughput: 12 items per minute, Error rate: 1.2 percent, Total latency: 4.2 minutes

"when-chaining-agent-pipelines-use-stream-chain" ์‚ฌ์šฉ ์ค‘์ž…๋‹ˆ๋‹ค. Create a CI/CD pipeline that builds, tests, and deploys in parallel

์˜ˆ์ƒ ๊ฒฐ๊ณผ:

  • Pipeline Structure: build stage with parallel test and deploy branches
  • Build Stage: Compiles code and generates artifacts
  • Parallel Branch A: Runs unit tests, integration tests, security scans
  • Parallel Branch B: Prepares deployment configurations
  • Merge Point: Combines test results with deployment readiness
  • Deploy Stage: Pushes to staging or production environment

๋ณด์•ˆ ๊ฐ์‚ฌ

์•ˆ์ „
v5 โ€ข 1/17/2026

All 79 static findings are false positives. The skill contains only documentation describing Claude Flow pipeline orchestration patterns. No executable code, network calls, or file system access exist. The 'Weak cryptographic algorithm' flags are triggered by documentation text (e.g., 'stage', 'spawn', 'shell'). The 'external_commands' flags are markdown code formatting backticks, not shell execution.

5
์Šค์บ”๋œ ํŒŒ์ผ
629
๋ถ„์„๋œ ์ค„ ์ˆ˜
5
๋ฐœ๊ฒฌ ์‚ฌํ•ญ
5
์ด ๊ฐ์‚ฌ ์ˆ˜

์œ„ํ—˜ ์š”์ธ

โšก ์Šคํฌ๋ฆฝํŠธ ํฌํ•จ
๊ธฐ๋ก๋œ ํŠน์ • ์œ„์น˜๊ฐ€ ์—†์Šต๋‹ˆ๋‹ค
๐ŸŒ ๋„คํŠธ์›Œํฌ ์ ‘๊ทผ
๊ธฐ๋ก๋œ ํŠน์ • ์œ„์น˜๊ฐ€ ์—†์Šต๋‹ˆ๋‹ค
๐Ÿ“ ํŒŒ์ผ ์‹œ์Šคํ…œ ์•ก์„ธ์Šค
๊ธฐ๋ก๋œ ํŠน์ • ์œ„์น˜๊ฐ€ ์—†์Šต๋‹ˆ๋‹ค
๐Ÿ”‘ ํ™˜๊ฒฝ ๋ณ€์ˆ˜
๊ธฐ๋ก๋œ ํŠน์ • ์œ„์น˜๊ฐ€ ์—†์Šต๋‹ˆ๋‹ค
โš™๏ธ ์™ธ๋ถ€ ๋ช…๋ น์–ด
๊ธฐ๋ก๋œ ํŠน์ • ์œ„์น˜๊ฐ€ ์—†์Šต๋‹ˆ๋‹ค

ํ’ˆ์งˆ ์ ์ˆ˜

38
์•„ํ‚คํ…์ฒ˜
100
์œ ์ง€๋ณด์ˆ˜์„ฑ
87
์ฝ˜ํ…์ธ 
30
์ปค๋ฎค๋‹ˆํ‹ฐ
100
๋ณด์•ˆ
83
์‚ฌ์–‘ ์ค€์ˆ˜

๋งŒ๋“ค ์ˆ˜ ์žˆ๋Š” ๊ฒƒ

Multi-Stage Code Review

Chain research, analysis, coding, testing, and review agents for systematic code development with validated outputs at each stage.

Parallel Data Analysis

Process large datasets through parallel analysis stages with streaming results aggregation and real-time monitoring.

Automated Content Pipeline

Orchestrate research, writing, editing, and publishing agents in sequential pipelines for consistent content quality.

์ด ํ”„๋กฌํ”„ํŠธ๋ฅผ ์‚ฌ์šฉํ•ด ๋ณด์„ธ์š”

Basic Sequential Pipeline
Create a 3-stage sequential pipeline. Stage 1 researches a topic, Stage 2 analyzes findings, Stage 3 compiles a report. Use memory coordination for data passing.
Parallel Processing Pipeline
Design a pipeline where initial data splits into 3 parallel analysis branches that converge into a final synthesis stage.
Hybrid Pipeline with Monitoring
Build a hybrid pipeline. Sequential stages 1-2, then parallel stages 3a-3b-3c converging to stage 4. Include throughput monitoring every 30 seconds.
Error-Resilient Pipeline
Create a 4-stage pipeline with error handling. Each stage validates input, retries on failure (max 3 attempts), and stores error metrics.

๋ชจ๋ฒ” ์‚ฌ๋ก€

  • Design clear stage boundaries with single responsibilities and validated data schemas
  • Implement backpressure monitoring to prevent queue overflow at stage boundaries
  • Use memory coordinator for state persistence and enable stage restart on failures

ํ”ผํ•˜๊ธฐ

  • Avoid creating circular dependencies between pipeline stages that can cause infinite loops
  • Do not hardcode stage configurations - use external design files for flexibility
  • Never skip validation between stages - unchecked data corruption propagates through pipeline

์ž์ฃผ ๋ฌป๋Š” ์งˆ๋ฌธ

Which Claude versions support pipeline chaining?
Works with Claude 3.5 Sonnet, Claude 3 Opus, and Claude Code with Claude Flow integration.
What is the maximum number of pipeline stages?
No hard limit exists, but practical maximum is 10 to 15 stages for manageable complexity.
Can I integrate with existing CI/CD systems?
Yes, pipeline results output to JSON formats compatible with Jenkins, GitHub Actions, and GitLab CI.
How is sensitive data handled in pipelines?
Data stays within Claude Flow secure environment. No external transmission occurs during processing.
What happens if a pipeline stage fails?
Pipeline supports retry mechanisms, fallback stages, and error reporting with detailed failure analysis.
How does this compare to traditional workflow engines?
Stream-chain provides AI-native orchestration with intelligent agent coordination and adaptive execution.

๊ฐœ๋ฐœ์ž ์„ธ๋ถ€ ์ •๋ณด

์ž‘์„ฑ์ž

DNYoussef

๋ผ์ด์„ ์Šค

MIT

์ฐธ์กฐ

main

ํŒŒ์ผ ๊ตฌ์กฐ

๐Ÿ“„ process-diagram.gv

๐Ÿ“„ PROCESS.md

๐Ÿ“„ README.md

๐Ÿ“„ SKILL.md