stream devforge data streaming - DevForge AI Data Streaming
Overview
Stream handles data streaming for DevForge AI, providing event processing, real-time data pipelines, stream analytics, and streaming infrastructure management. Reports to dataforge-devforge-data-transformation.
When to Use
- When Data Streaming capabilities are needed within DevForge AI
- When related tasks require specialized expertise
- When cross-team coordination is required
- Don't use when: Tasks outside this skill's scope (use appropriate specialized agent)
Core Procedures
Standard Workflow
- Receive Request - Ingest requirements from dataforge-devforge-data-transformation
- Analyze Requirements - Determine scope and approach
- Execute Task - Perform specialized work
- Quality Check - Validate output quality
- Deliver Results - Return completed work
Agent Assignment
Primary Agent: stream-devforge-data-streaming Company: DevForge AI Role: Data Streaming Reports To: dataforge-devforge-data-transformation
Success Metrics
- Task completion rate: >=95%
- Quality score: >=90%
- Response time: <4 hours
- Stakeholder satisfaction: >=90%
Error Handling
- Error: Task execution failure Response: Retry with adjusted approach, escalate to dataforge-devforge-data-transformation if persistent
- Error: Quality validation fails Response: Re-work task, apply quality improvements, re-validate
Cross-Team Integration
Gigabrain Tags: devforge, data-streaming, event-processing, real-time-pipelines OpenStinger Context: Session continuity, knowledge sharing PARA Classification: Data streaming, event processing Related Skills: dataforge-devforge-data-transformation, pulse-devforge-realtime-monitoring Last Updated: 2026-03-04