Awesome ChatGPT prompts

Stores curated AI prompts in a structured CSV format (prompts.csv) with automatic GitHub synchronization via CI/CD workflows. The system uses CSV as the source of truth for the prompt collection, enabling version control, contributor attribution, and programmatic access without requiring a traditional database for the core library. Changes to the CSV trigger automated workflows that rebuild the application state and update contributor records.

Executes prompts against external AI platforms (ChatGPT, Claude, Gemini, etc.) by constructing platform-specific API calls and managing authentication via user-provided API keys. The system abstracts platform differences through a unified execution interface that handles prompt variable substitution, media uploads, and response formatting. Webhooks enable asynchronous execution tracking and result persistence back to the database.

Provides administrative interface for moderating prompts, managing users, and monitoring platform health. Admins can review flagged content, approve/reject change requests, manage user roles, and view analytics. The system includes auto-moderation features (content filtering, spam detection) that flag suspicious prompts for human review. Admin actions are logged for audit purposes.

Exposes the prompt library via the Model Context Protocol (MCP), enabling integration with IDEs, code editors, and AI tools. The MCP server provides tools for searching, retrieving, and executing prompts from within development environments. This allows developers to access the prompt library without leaving their editor, with support for Raycast and other MCP-compatible clients.

Provides a command-line interface (npm package) for accessing, searching, and managing prompts from the terminal. The CLI enables developers to integrate prompts into scripts, automation workflows, and CI/CD pipelines. It supports filtering, formatting output (JSON, markdown), and executing prompts against configured AI platforms.

Extends the prompt library with a dedicated kids learning platform featuring pixel art components, interactive books, and gamified progress tracking. The system uses a level-based progression model with visual rewards and achievements. Educational content is curated separately from the main prompt library with age-appropriate filtering and simplified UI.

Provides a Raycast extension enabling users to search and execute prompts directly from the Raycast launcher. The extension integrates with the MCP server and supports quick actions like copying prompts, executing against AI platforms, and saving to collections. It enables fast, keyboard-driven access to the prompt library without opening a web browser.

Enables prompt creators to define dynamic prompts with variable placeholders ({{variable_name}}) that users fill in at execution time. The system validates variable types, provides UI form generation for user input, and performs substitution before sending to AI platforms. Variables can have constraints (required/optional, type hints, default values) defined in prompt metadata, enabling type-safe prompt execution.

Tracks prompt modifications through a versioning system that stores historical versions in the database and enables community-driven improvements via change requests. Users can propose edits to existing prompts, which are reviewed and voted on by the community before merging into the canonical version. The system maintains a full audit trail of who changed what and when, with rollback capability to previous versions.

Provides internationalization infrastructure for translating prompts and UI into 20+ languages using a message file system (i18n) with automatic locale detection based on browser language preferences. The system supports right-to-left (RTL) languages like Arabic and Hebrew with CSS-based layout flipping. Translations are managed as separate message files per language, enabling community translation contributions without modifying core prompt data.

Implements a multi-faceted search and discovery system that filters prompts by categories, tags, difficulty level, and user ratings. The system uses a browse interface with dynamic filtering, a full-text search capability, and personalized discovery sections (trending, new, recommended). Search results are ranked by relevance and community engagement metrics, with support for saved collections and user feeds.

Enables users to upvote/downvote prompts and comments, with votes aggregated into reputation scores and displayed on a 'Promptmasters' leaderboard. The voting system influences prompt ranking in search results and discovery sections. User reputation is calculated from prompt votes, comment votes, and contribution counts, creating gamification incentives for quality contributions.

Extends single-prompt capabilities to support 'Skills' — multi-file prompt compositions that combine multiple prompts, instructions, and context files into a cohesive workflow. Skills are stored in the database with file relationships and can be executed sequentially or in parallel, with output from one skill feeding into the next. The system supports versioning and change requests for Skills just like individual prompts.

Provides a configuration system enabling organizations to deploy the prompt platform under their own branding with customized colors, logos, domain names, and feature flags. The system uses environment variables and a central config file (prompts.config.ts) to control branding, authentication providers, and feature availability without code changes. Docker deployment support enables self-hosting with minimal infrastructure knowledge.

Implements user authentication using NextAuth.js with support for multiple OAuth providers (GitHub, Google, etc.) and email-based authentication. The system manages user sessions, profiles, and API key storage for external platform integrations. User roles and permissions control access to features like prompt creation, moderation, and admin functions. Authentication state is persisted in the database via Prisma.