data-systems-trade-offs

[WHAT] Guides the agent through architectural trade-off analysis for data-intensive systems, covering operational vs analytical workloads, cloud vs self-hosted deployment, distributed vs single-node topology, and regulatory compliance constraints. [WHEN] Activate when the user is evaluating data system architecture, choosing between OLTP and OLAP, deciding on cloud vs on-prem, considering whether to distribute a system, or assessing data privacy and compliance requirements. [KEYWORDS] trade-offs, architecture, OLTP, OLAP, data warehouse, cloud-native, self-hosted, distributed systems, single-node, scalability, reliability, maintainability, GDPR, data compliance.

Safety Notice

This listing is imported from SkillsMP metadata and should be treated as untrusted until upstream source review is completed.

Copy this and send it to your AI assistant to learn

Install skill "data-systems-trade-offs" with this command: npx skills add chrisVillanueva/skillsmp-chrisvillanueva-chrisvillanueva-data-systems-trade-offs

No markdown body

This source entry does not include full markdown content beyond metadata.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Open in GitHub

Related Skills

Related by shared tags or category signals.

Web3

nonfunctional-requirements

[WHAT] Guides the agent through trade-off analysis for data engineering systems using nonfunctional requirements: performance, reliability, scalability, and maintainability. Provides layered decision frameworks for system properties, pipeline design, and data operations. [WHEN] Activate when the user is defining SLOs/SLAs for data systems, evaluating pipeline latency vs throughput, choosing batch vs streaming, assessing fault tolerance strategies, planning capacity, or reasoning about ETL vs ELT, error handling, idempotency, or data quality trade-offs. [KEYWORDS] nonfunctional requirements, performance, reliability, scalability, maintainability, SLO, SLA, latency, throughput, percentiles, fault tolerance, batch, streaming, ETL, ELT, idempotency, data quality, observability, trade-off analysis, pipeline design.

Repository SourceNeeds Review
-0chrisVillanueva
Research

fall-detection-video-analysis

Detects whether anyone has fallen within a target area. Supports video stream analysis and is suitable for real-time safety monitoring of elderly people living alone. | 跌倒检测视频版技能，检测目标区域内是否有人跌倒，支持视频流检测，适用于独居老人居家安全监测

Archived SourceRecently Updated
--18072937735
Research

fall-detection-image-analysis

Detects whether anyone has fallen within a specified target area. Supports both image and short video analysis. Suitable for scenarios such as home care for elderly people living alone and safety monitoring in nursing homes. | 检测目标区域内是否有人跌倒，支持图片和短视频检测，适用于独居老人居家看护、养老院安全监测等场景

Archived SourceRecently Updated
--18072937735
Research

contactless-health-risk-detection-analysis

Combines frontal facial image capture with multimodal physiological feature analysis to provide early risk screening and alerts for chronic and acute conditions such as heart attack, stroke, hypertension, and hyperlipidemia. | 非接触式健康风险识别技能，通过正面人像采集结合多模态生理特征分析，提供心梗、脑梗、高血压、高血脂等慢病急症早期风险筛查预警

Archived SourceRecently Updated
--18072937735
data-systems-trade-offs | V50.AI