Github Actions

Create and manage GitLab issues, merge requests, pipelines, and repositories using the glab CLI. Use when asked to open an MR, review a merge request, check CI/CD pipelines, list issues, or manage code review on GitLab.

Vercel observability for Web Analytics, Speed Insights, logs, tracing, alerts, and observability tooling. Use when monitoring performance or debugging production behavior on Vercel.

DataWorks Infrastructure Management: Create and query operations for Data Sources (50 types), Compute Resources, and Serverless Resource Groups, plus connectivity testing and resource group binding/unbinding. Uses aliyun CLI to call dataworks-public OpenAPI (2024-05-18). Trigger keywords: DataWorks data source, compute resource, resource group, datasource, data source, compute resource, resource group, mysql/hologres/maxcompute data source, holo/mc/flink resource, Serverless resource group, DataWorks infra, create/list datasource, DW environment config, infrastructure initialization, connect database to DataWorks, database connection failure, configure holo/mc resource. Not triggered: data development tasks, scheduling configuration, MaxCompute table management, data integration tasks, ECS/RDS/OSS operations, workspace member management, data quality monitoring, data lineage, data preview.

Creates SLO-based alerts and operational dashboards with key charts, alert thresholds, and runbook links. Use for "alerting", "dashboards", "SLO", or "monitoring".

Use this skill whenever the user wants to monitor, watch, or track Polymarket prediction market prices over time. This includes setting up price alerts, watching for significant price movements, tracking spread changes, monitoring volume spikes, or getting notified about market activity. Trigger on: monitor prices, price alert, watch market, track prices, notify me, price change, polymarket alerts, market watch, price movement, volume spike, spread monitoring, track odds, prediction market alerts, continuous monitoring, price tracker, market surveillance.

Analyzes Kubernetes resource usage metrics and historical data to suggest optimal CPU and Memory requests and limits. Use to reduce cloud costs, prevent OOMKills, and improve overall cluster reliability by right-sizing your deployments.