Essential command-line tools and system utilities.
This skill should be used when the user asks to "set up submodules", "migrate branches to submodules", "automate submodule sync", "create submodule architecture", "convert branches to repos", or mentions setting up git submodules with GitHub Actions automation for multi-repo synchronization.
Comprehensive stack health audit for codebase and infrastructure. Runs 10 health checks covering frontend, backend, migrations, Docker, API integrity, and backup status. Use routinely to prevent "time loops" from accumulated issues.
Guides the creation of high-quality Pull Requests that adhere to repository standards, covering template discovery, drafting descriptions, and executing PR creation commands.
Enforces automated quality checks before every deploy. Prevents production failures through a 5-stage Quality Gate System (Pre-Commit, PR-Check, Preview, E2E, Production). Activate on code changes, deployments, PR reviews, build failures.
CI/CD pipelines with Git, GitHub Actions, GitLab CI, Jenkins, and deployment strategies.
Generate or update .NET MAUI workload release notes documentation. Creates well-formatted markdown documents showing workload versions, platform dependencies, and installation instructions for .NET MAUI development environments. Maintains a release history with dated snapshots.
Prepare your codebase for security review using Trail of Bits' checklist. Helps set review goals, runs static analysis tools, increases test coverage, removes dead code, ensures accessibility, and generates comprehensive documentation (flowcharts, user stories, inline comments). (project, gitignored)
Use the gemini-cli-integration skill PROACTIVELY when analyzing large codebases, multiple files, or directories. Leverages Google Gemini's massive context window with @ syntax for file inclusion to handle comprehensive codebase analysis, implementation verification, and architectural understanding.
Utility tool to create new git worktrees with proper setup for development environments. Automates creation, copying, symlinking, and ownership management for smooth developer onboarding or isolated task/feature work.
Code hygiene, quality gates, and pre-commit workflows. Use for linting, type checking, testing, and fixing errors.
Discover and identify any technology, framework, or system without prior knowledge. Analyzes files, configurations, dependencies, and usage patterns to understand project technology stack from C source files to Kubernetes manifests.
Code quality standards for reviewing code changes. Automatically provides quality checklist when reviewing PRs, implementing features, or discussing code quality.
Security scanning with dependency audits, secret detection, static analysis, and vulnerability management. Use when checking for vulnerabilities, scanning dependencies, or enforcing security gates.
Jujutsu (jj) version control for AI-assisted development. Use when: - Repo has `.jj/` directory (check with `jj root`) - Need undo/recovery after breaking changes - Curating messy history before PR
Comprehensive Maven build strategies for mixed Java/Scala projects with parallel execution, intelligent test running, and targeted debugging workflows. Use this skill when user asks to build the project, run tests, compile code, clean build, run Maven commands, fix compilation errors, or analyze test failures. Automatically invoked for requests like "make a fresh build", "run all tests", "build and test", "clean and compile", or any Maven-related build tasks.
Generate and analyze test coverage reports. Use to identify coverage gaps, track coverage trends, and ensure quality thresholds are met.
Reviews the git changes, identifies critical and high-priority issues, generates review summaries, and collects metrics data for local use. Use this when users need to code review or analyzing code changes for quality issues.
Generate comprehensive test suites, identify coverage gaps, and accelerate progress toward 70% test coverage goal with intelligent test recommendations
Docker development and container orchestration expertise. Use when creating Dockerfiles, docker-compose configurations, debugging container issues, optimizing images, or setting up isolated development environments. Integrates with CI/CD workflows and security scanning.
List Terraform Cloud runs for a workspace with filtering by status, operation type, and date. Use when reviewing run history, finding failed runs, or auditing infrastructure changes. Requires TFE_TOKEN environment variable.
Provides comprehensive IBM Cloud platform guidance including compute services (VPC, Virtual Servers, IKS, OpenShift, Code Engine, Cloud Functions), storage (Object Storage, Block Storage, File Storage), databases (Db2, Cloudant, PostgreSQL, MySQL, MongoDB, Redis), IAM security (access groups, service IDs, Key Protect, Secrets Manager), networking (VPC, load balancers, Direct Link), CLI automation, Terraform/Schematics infrastructure as code, monitoring, and cost optimization. Covers infrastructure provisioning, application deployment, security configuration, multi-zone high availability, and operational best practices. Use when working with IBM Cloud services, deploying cloud infrastructure, managing cloud resources, configuring security and networking, or when users mention "IBM Cloud", "IKS", "Code Engine", "Db2", "Cloudant", "VPC", "cloud provisioning", "IBM Kubernetes", "OpenShift", "Terraform IBM", "Schematics", or "IBM cloud platform".
Provides comprehensive Google Cloud Platform (GCP) guidance including Compute Engine, Cloud Storage, Cloud SQL, BigQuery, GKE (Google Kubernetes Engine), Cloud Functions, Cloud Run, VPC networking, load balancing, IAM, Cloud Build, infrastructure as code (Terraform, Deployment Manager), security configuration, cost optimization, and multi-region deployment. Produces infrastructure code, deployment scripts, configuration guides, and architecture designs. Use when deploying to Google Cloud, designing GCP infrastructure, migrating to GCP, configuring GCE instances, setting up Cloud Storage, managing Cloud SQL databases, working with BigQuery, deploying to GKE, or when users mention "Google Cloud", "GCP", "Compute Engine", "Cloud Storage", "BigQuery", "GKE", "Cloud Run", "Cloud Functions", "VPC", "Cloud SQL", or "Google Cloud Platform".
