Develop AI-powered applications using Genkit in Node.js/TypeScript. Use when the user asks about Genkit, AI agents, flows, or tools in JavaScript/TypeScript, or when encountering Genkit errors, validation issues, type errors, or API problems.

Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Use when the user asks to threat model a codebase or path, enumerate threats or abuse paths, or perform AppSec threat modeling. Do NOT use for general architecture summaries, code review, security best practices (use security-best-practices), or non-security design work.

Project and feature planning with 4 adaptive phases - Specify, Design, Tasks, Execute. Auto-sizes depth by complexity. Creates atomic tasks with verification criteria, atomic git commits, requirement traceability, and persistent memory across sessions. Stack-agnostic. Use when (1) Starting new projects (initialize vision, goals, roadmap), (2) Working with existing codebases (map stack, architecture, conventions), (3) Planning features (requirements, design, task breakdown), (4) Implementing with verification and atomic commits, (5) Quick ad-hoc tasks (bug fixes, config changes), (6) Tracking decisions/blockers/deferred ideas across sessions, (7) Pausing/resuming work. Triggers on "initialize project", "map codebase", "specify feature", "discuss feature", "design", "tasks", "implement", "validate", "verify work", "UAT", "quick fix", "quick task", "pause work", "resume work". Do NOT use for architecture decomposition analysis (use architecture skills) or technical design docs (use create-technical-design-doc).

Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Use when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting. Covers general Figma data fetching and exploration. Do NOT use when the goal is specifically pixel-perfect code implementation from a Figma design (use figma-implement-design instead).

Automates software development overnight using Git hooks to enforce test-driven development (TDD). This skill activates when you request "overnight development", "autonomous coding", "work while I sleep", or mention TDD workflows and Git hooks. It leverages Git hooks to block commits until all tests pass, enforcing a rigorous TDD process and ensuring high-quality, production-ready code. Perfect for building features autonomously - just define the goal and let Claude work overnight while tests enforce quality.

Canonical standards for migrating ASP.NET Web Forms applications to Blazor using BWFC

Terraform infrastructure specialist for deploying Genkit applications to production. Provisions Firebase Functions, Cloud Run services, GKE clusters, monitoring, and CI/CD for Genkit AI workflows. Triggers: "deploy genkit terraform", "genkit infrastructure", "firebase functions terraform", "cloud run genkit"

Create leveraged buyout (LBO) models in Excel with sources & uses, debt schedules, cash flow waterfalls, and IRR calculations for private equity analysis Activates when you request "excel lbo modeler" functionality.

Alias for requirement-summarizer. Produces a structured summary of a requirements document — the key obligations, grouped by actor and concern, with the MUST/SHOULD/MAY breakdown. Use when onboarding to a large spec, when deciding what to implement first, or when the user asks what a standard actually requires.

Vitest fast unit testing framework powered by Vite with Jest-compatible API. Use when writing tests, mocking, configuring coverage, or working with test filtering and fixtures.

Download YouTube videos with customizable quality and format options. Use this skill when the user asks to download, save, or grab YouTube videos. Supports various quality settings (best, 1080p, 720p, 480p, 360p), multiple formats (mp4, webm, mkv), and audio-only downloads as MP3.

Use when building or reviewing Micronaut applications — Micronaut.run bootstrap, @Singleton/@Prototype, @Factory beans, @ConfigurationProperties, environments, @Requires, @Controller vs services, @Scheduled, graceful shutdown, @ExecuteOn for blocking work, and Jakarta-consistent APIs. This should trigger for requests such as Review Java code for Micronaut application structure and beans; Apply best practices for Micronaut configuration, @Requires, and factories; Improve scheduling, shutdown, or threading in Micronaut services. Part of cursor-rules-java project

Use when you need data access with Micronaut Data — @MappedEntity, CrudRepository/PageableRepository, @Query with parameters, @Transactional services, projections, @Version, and @MicronautTest with TestPropertyProvider and Testcontainers. For raw java.sql access without generated repositories, use @511-frameworks-micronaut-jdbc. This should trigger for requests such as Review or implement Micronaut Data repositories and entities; Add transactions, pagination, or projections in Micronaut persistence layer. Part of cursor-rules-java project

Use when you need to design, review, or improve REST APIs with Micronaut — including @Controller routes, HTTP status codes, DTOs, Bean Validation, exception handlers, pagination, idempotency, ETag/If-Match, caching headers, versioning, contract-first OpenAPI (OpenAPI Generator), optional runtime OpenAPI via micronaut-openapi, and security annotations. This should trigger for requests such as Review or improve Micronaut @Controller REST APIs; Add validation, error handling, or align controllers with the OpenAPI contract on Micronaut HTTP layer. Part of cursor-rules-java project

Creates sprint plans, prioritizes product backlogs using RICE/MoSCoW/Kano frameworks, generates capacity plans, writes user stories with acceptance criteria, and produces stakeholder-ready roadmaps. Use when a user needs to prioritize features, score backlog items, plan a sprint, groom stories, allocate team capacity, calculate story points, create a release roadmap, run RICE scoring, evaluate trade-offs between features, or prepare sprint review and retrospective materials.

Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.

**WORKFLOW SKILL** — Prepare Azure apps for deployment (infra Bicep/Terraform, azure.yaml, Dockerfiles). Covers create, modernize, and create+deploy. WHEN: "create app", "build web app", "create API", "deploy to Azure", "deploy to Azure using Terraform", "generate Bicep", "generate Terraform", "function app", "add authentication", "managed identity", "add caching", "containerized Node.js app". USE FOR: scaffolding new Azure apps, modernizing existing apps, generating IaC + azure.yaml. DO NOT USE FOR: cross-cloud migration (use azure-cloud-migrate), executing deployments of already-prepared apps (use azure-deploy), pre-deployment validation (use azure-validate).

**WORKFLOW SKILL** — Execute Azure deployments for ALREADY-PREPARED apps. Runs azd up, azd deploy, terraform apply with built-in error recovery. Requires plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "push to production", "go live", "bicep deploy", "terraform apply", "publish to Azure". USE FOR: deploying validated infra; lifting existing IaC to cloud. DO NOT USE FOR: creating new apps (use azure-prepare), generating IaC (use azure-prepare), pre-deployment checks (use azure-validate). INVOKES: azd CLI, az deployment, microsoft_docs_search (Microsoft Learn MCP).

Onboard quickly by reading design docs, plans, READMEs, or the codebase to extract key concepts, surface gaps, and generate comprehension checks with answer keys. Includes an adaptive proficiency probe with learning resources and persistent session memory so the user can resume onboarding where they left off. Use when a user wants help understanding a project, validating their grasp of the architecture, or creating a readiness plan before contributing code.

Plain-English translation layer for non-technical Copilot CLI users. Translates every approval prompt, error message, and technical output into clear, jargon-free English with color-coded risk indicators.