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Create a Google Meet meeting space and email the join link to participants. \n \n Requires two prerequisite skills: gws-meet for space creation and gws-gmail for sending invitations \n Creates an open-access meeting space via the Meet API and extracts the meeting URI from the response \n Automates sharing the join link by composing and sending an email with the meeting details to specified recipients \n

Design and build isolated, reusable Convex backend components with clear boundaries and app-facing wrappers. \n \n Supports three component shapes: local (single-app), packaged (npm), and hybrid (both), with a decision tree to choose the right fit \n Enforces architectural boundaries: components own their tables and functions, while the app handles authentication, environment access, and client-facing wrappers \n Provides a complete workflow from planning (tables, public API, data flow) through

Generates formal, AI-optimized specifications for GitHub Actions workflows to standardize documentation and enable maintenance. \n \n Produces structured markdown specifications with execution flow diagrams, job dependency matrices, and requirement tables designed for token efficiency \n Covers functional, security, and performance requirements alongside input/output contracts, error handling strategies, and quality gates \n Includes sections for monitoring, compliance, edge cases, and change ma

Create structured, machine-readable implementation plans for features, refactoring, upgrades, and infrastructure changes. \n \n Generates deterministic, AI-executable plans with discrete phases, atomic tasks, and explicit completion criteria \n Enforces strict template compliance with standardized identifier prefixes (REQ-, TASK-, GOAL-, etc.) and machine-parseable formats \n Includes mandatory sections for requirements, implementation phases, dependencies, testing, risks, and alternatives \n Su

Generate structured, AI-optimized specification documents with standardized templates and machine-readable formatting. \n \n Creates specification files in /spec/ directory following naming convention spec-[purpose]-[type].md with YAML front matter for metadata \n Enforces structured markdown with 11 standard sections covering purpose, requirements, interfaces, acceptance criteria, and validation \n Includes explicit guidelines for unambiguous language, acronym definitions, and self-contained do

Generates standardized AGENTS.md files to help AI coding agents understand and work with your repository. \n \n Provides a template-driven approach for creating agent-focused documentation that complements README.md with technical setup, workflow, and testing instructions \n Covers essential sections including project overview, setup commands, development workflow, testing, code style, build/deployment, and PR guidelines \n Supports monorepo structures with guidance for creating AGENTS.md files

Guide for creating AGENTS.md files for project-specific inline rules.

You're using a skill that will guide you through setting up AI configuration in your application. Your job is to explore the codebase to understand the use case and stack, choose agent vs completion mode, create the config following the right path, and verify it works.

This skill provides guidance for creating effective skills.

You are an expert videographer and motion designer specializing in creating engaging promotional short-form videos for software projects. Your goal is to create a TikTok-style promotional video that showcases the project's key features and value proposition.