This skill should be used when the user asks to "bump the Rust SDK", "update sdk-internal", "bump bitwarden-crypto", "update RustSdk dependencies", "align server SDK with clients", or needs to update the bitwarden/sdk-internal git rev pins in util/RustSdk/rust/Cargo.toml. Provides the methodology for mapping client NPM versions to git commit SHAs, analyzing breaking changes, auditing the API surface, and verifying the bump end-to-end.
Local text-to-speech via sherpa-onnx (offline, no cloud). Converts text to speech audio using the sherpa-onnx runtime and Piper VITS voices with no cloud dependency. Use when the user asks to generate speech, read text aloud, produce a voice audio file, perform TTS, speech synthesis, or convert text to WAV output locally.
Interact with GitHub using the `gh` CLI to manage repositories, issues, pull requests, CI/CD workflow runs, and API queries. Use when the user asks to create, list, view, merge, or close pull requests and issues; check CI status or workflow run logs; query the GitHub API for repository data; or perform any GitHub operation from the command line. Covers `gh issue`, `gh pr`, `gh run`, `gh repo`, and `gh api` subcommands.
Submit and manage protocols on Ginkgo Bioworks Cloud Lab (cloud.ginkgo.bio), a web-based interface for autonomous lab execution on Reconfigurable Automation Carts (RACs). Use when the user wants to run cell-free protein expression (validation or optimization), generate fluorescent pixel art, or interact with Ginkgo Cloud Lab services. Covers protocol selection, input preparation, pricing, and ordering workflows.
Cloud computing platform for running Python on GPUs and serverless infrastructure. Use when deploying AI/ML models, running GPU-accelerated workloads, serving web endpoints, scheduling batch jobs, or scaling Python code to the cloud. Use this skill whenever the user mentions Modal, serverless GPU compute, deploying ML models to the cloud, serving inference endpoints, running batch processing in the cloud, or needs to scale Python workloads beyond their local machine. Also use when the user wants to run code on H100s, A100s, or other cloud GPUs, or needs to create a web API for a model.
Analyze CI build and test status from Azure DevOps and Helix for dotnet repository PRs. Use when checking CI status, investigating failures, determining if a PR is ready to merge, or given URLs containing dev.azure.com or helix.dot.net. Also use when asked "why is CI red", "test failures", "retry CI", "rerun tests", "is CI green", "build failed", "checks failing", or "flaky tests".
Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Includes tech debt analyzer, team scaling calculator, engineering metrics frameworks, technology evaluation tools, and ADR templates. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.
Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.
Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.
Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Manage Agent Zero plugins lifecycle: browse the Plugin Hub, scan for security, install from Git/ZIP/Plugin Hub, update, uninstall, enable, disable, debug, and troubleshoot. Use when asked to install, update, uninstall, remove, scan, find, search, enable, disable, debug, or troubleshoot a plugin.
Guide for publishing an Agent Zero plugin to the community Plugin Index (a0-plugins repo). Covers GitHub repo setup, index.yaml creation, CI validation rules, and PR submission. Use when the user wants to share, publish, submit, or contribute a plugin to the Plugin Hub so other Agent Zero users can find and install it.
Use when configuring Jenkins in KubeSphere DevOps, including agent customization, LDAP/OIDC integration, build artifact retrieval, or troubleshooting Jenkins issues
Use when working with KubeSphere DevOps extension, CI/CD pipelines, Jenkins integration, or pipeline troubleshooting
Use when creating, running, or managing CI/CD pipelines in KubeSphere DevOps, including pipeline API operations and run monitoring
Use when configuring ArgoCD in KubeSphere DevOps, including GitOps deployments, application management, SSO setup, or troubleshooting ArgoCD issues
Use when working with WizTelemetry Auditing extension for KubeSphere, including installation, configuration, and audit query API
Use when working with WizTelemetry Events extension for KubeSphere, including installation, configuration, and event query API
Use when working with WizTelemetry Logging extension for KubeSphere, including installation, configuration, and log query API
Use when installing or configuring the WizTelemetry Platform Service extension for KubeSphere, which provides the common APIServer backend services for all WizTelemetry observability extensions
