Loading...
Loading...
Found 9,189 Skills
Generates reliability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework. Use this skill to evaluate a workload, identify reliability requirements, and provide actionable recommendations for build, deploy, and manage the workload reliably in Google Cloud.
Master Material Design 3 and Jetpack Compose patterns for building native Android apps. Use when designing Android interfaces, implementing Compose UI, or following Google's Material Design guidelines.
Python observability patterns including structured logging, metrics, and distributed tracing. Use when adding logging, implementing metrics collection, setting up tracing, or debugging production systems.
Bitbucket best practices for pull requests, Pipelines CI/CD, Jira integration, and Atlassian ecosystem workflows
Editorial review skill for Orbitant engineering blog posts. Activates when reviewing, editing, or providing feedback on blog articles. Produces structured reviews covering SEO, content quality, tone, and actionable improvements. Responds in the same language as the article being reviewed.
Fix accessibility issues.
Guide for implementing usage-based billing with Dodo Payments - meters, events, pricing per unit, and metered subscriptions.
Feishu/Lark binding: device flow authorization, connect, disconnect, status check. Use when setting up or managing Feishu/Lark connection (e.g. connect Feishu, connect Lark, bind 飞书, check Feishu status, disconnect Lark).
Create and manage mocks, stubs, spies, and test doubles for isolating unit tests from external dependencies. Use for mock, stub, spy, test double, Mockito, Jest mocks, and dependency isolation.
Triage and resolve Debian Linux issues with apt, systemd, and AppArmor-aware guidance.
Update Azure Verified Modules (AVM) to latest versions in Bicep files.
Manages datasets, tables, and jobs in BigQuery, and integrates with BigQuery ML and Gemini for advanced data analytics and AI-driven insights. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources, or leverage BigQuery's built-in ML capabilities. Also use when performing data analysis, ingesting data into BigQuery, or developing AI applications on BigQuery.