A small, flat, square illustration shows a plain file folder with three simple geometric icons rising from it: a rectangle marked ".js," another marked ".ts," and a third icon featuring a basic gear shape. The design uses five bold, contrasting corporate colors and is composed of only clean, flat shapes without any background or decorative effects. There are no people, textures, or dimensional shading. The image is limited to a 128x128 pixel size and is designed to be immediately recognizable and iconic.

Overview

GenAIScript supports multiple file formats for creating AI prompt templates:

JavaScript files named as *.genai.mjs or *.genai.js
TypeScript files named as *.genai.mts
Markdown files named as *.genai.md for simpler, text-based prompts

script({
  title: "Shorten", // displayed in UI and Copilot Chat
  // also displayed but grayed out:
  description:
    "A prompt that shrinks the size of text without losing meaning",
});

// but the variable is appropriately delimited
const file = def("FILE", env.files);

// this appends text to the prompt
$`Shorten ${file}. Limit changes to minimum.`;

The same script can also be written as a markdown file:

---
title: "Shorten"
description: "A prompt that shrinks the size of text without losing meaning"
---
Shorten the provided text. Limit changes to minimum while preserving meaning.

Script files

GenAIScript will detect any file matching *.genai.mjs, *.genai.js, *.genai.mts, or *.genai.md in your workspace.
GenAIScript files can be placed anywhere in your workspace; but the extension will place them in a genaisrc folder by default.
.genai.mjs use module JavaScript syntax and support imports.
.genai.js are eval-ed and do not support imports.
.genai.mts are TypeScript module files and support imports, including dynamic imports of other TypeScript files.
.genai.md are Markdown script files with YAML frontmatter for configuration.

Directory/genaisrc
- jsconfig.json // TypeScript compiler configuration
- genaiscript.d.ts // TypeScript definitions
- myscript.genai.mjs // JavaScript script
- analyze.genai.mts // TypeScript script
- summarize.genai.md // Markdown script
- …

system.*.genai.mjs are considered system prompt templates and are unlisted by default.

Topics

Map-Reduce Learn how to use the map and reduce functions in GenaScript for efficient data processing

Metadata Learn how to configure script metadata to enhance functionality and user experience in GenAIScript.

Prompt ($) Learn how to use the tagged template literal for dynamic prompt generation in GenAI scripts.

Context (env+def) Detailed documentation on the script execution context and environment variables in GenAIScript.

Variables Discover how to utilize and customize script variables for dynamic scripting capabilities with env.vars.

File Output Learn how to declare and manage script-generated file outputs with defFileOutput function.

Tools Learn how to define and use tools within GenAIScript to enhance answer assembly with custom logic and CLI tools.

Model Context Protocol Tools Learn how to configure and securely use Model Context Protocol (MCP) tools and servers, including tool output validation, secret detection, and security best practices for AI scripting.

Model Context Protocol Server Turns scripts into Model Context Protocol Tools

Model Context Protocol Clients MCP Clients

Data Schemas Learn how to define and use data schemas for structured output in JSON/YAML with LLM, including validation and repair techniques.

Agents An Agent is a tool that queries an LLM, equipped with other tools, to accomplish tasks.

DOCX Learn how to parse and extract text from DOCX files for text analysis and processing.

PDF Learn how to extract text from PDF files for prompt generation using GenAIScript's PDF parsing capabilities.

XML Discover how to automatically parse XML files and convert them to JSON objects, enabling efficient data handling, RSS feed parsing, and file processing.

Markdown Enhance your markdown capabilities with MD class helpers for parsing and managing frontmatter efficiently.

Images Learn how to add images to prompts for AI models supporting visual inputs, including image formats and usage.

Inline prompts Learn how to use inline prompts with runPrompt function for inner LLM invocations in scripting.

Retrieval Learn how to use GenAIScript's retrieval utilities for content search and prompt augmentation with RAG techniques.

Secret Scanning Learn how to detect and prevent sensitive information leaks in your codebase using automated secret scanning, customizable patterns, and configuration options.

System Prompts Learn how to utilize system prompts to enhance script execution in GenAIScript.

Vector Search Learn how to use the retrieval.vectorSearch function to index files with embeddings for efficient similarity search in vector databases.

Videos as Inputs How to use the Video in scripts

Annotations Learn how to add annotations such as errors, warnings, or notes to LLM output for integration with VSCode or CI environments.

File Merge Customize file merging in scripts with defFileMerge function to handle different file formats and merging strategies.

Tests / Evals Learn how to execute and evaluate LLM output quality with promptfoo, a tool designed for testing language model outputs.

Red Team Learn how to implement LLM red teaming to identify vulnerabilities in AI systems using PromptFoo, including configuration, plugins like OWASP Top 10, and effective strategies for adversarial testing.

Custom Output Learn how to use the defOutputProcessor function for custom file processing in script generation.

Parsers Comprehensive guide on various data format parsers including JSON5, YAML, TOML, CSV, PDF, DOCX, and token estimation for LLM.

Structured Outputs Utilize structured output in GenAIScript to generate JSON data with schema validation for precise and reliable data structuring.

Files Learn how to perform file system operations using the workspace object in your scripts.

Fetch Learn how to use fetch and fetchText in scripts to make HTTP requests and handle text responses.

Cache Learn how LLM requests are cached in scripts to optimize performance and how to manage cache settings.

Cancel Learn how to immediately stop script execution with the cancel function in your automation scripts.

Diff Learn how to create and interpret file diffs within GenAIScript.

Markdown Scripts Learn how to write GenAIScript templates using Markdown syntax

Output Builder Learn how to build a markdown output for your script execution

TypeScript Learn how to use TypeScript for better tooling and scalability in your GenAIScript projects.

Web Search Execute web searches with the Bing API using retrieval.webSearch in scripts.

Secrets Learn how to securely access and manage environment secrets in your scripts with env.secrets object.

YAML Learn how to use YAML for data serialization, configuration, and parsing in LLM with defData, YAML class, and JSON schema validation.

CSV Learn how to parse and stringify CSV data using the CSV class in scripting.

INI Learn how to parse and stringify INI files in GenAIScript with the INI class, including methods and usage examples.

XLSX Learn how to parse and stringify Excel XLSX files with ease using our tools.

HTML Learn how to use HTML parsing functions in GenAIScript for effective content manipulation and data extraction.

ast-grep Search for patterns in the AST of a script

Choices Specify a list of preferred token choices for a script.

Containers Learn how to use containers for secure and isolated execution of untrusted code with Docker in software development.

Content Safety Learn about the built-in safety features, system prompts, and Azure AI Content Safety services to protect language model applications from harmful content, prompt injections, and prompt leaks.

Imports Learn how to enable module imports in GenAI scripts by converting them to .mjs format and using static or dynamic imports.

Logging Logging mechanism for scripts.

Diagrams Create diagrams and charts within markdown using GenAIScript and the mermaid extension for visual representation of data and processes.

Browser Automation Discover how GenAIScript integrates with Playwright for web scraping and browser automation tasks.

Audio Transcription Describe how to transcribe an audio/video file

Image Generation Use image generation like OpenAI DALL-E Stable Diffusion to generate images from text.

Chat Participants Create multi-turn chats or simulate conversations with multiple chat participants

Concurrency How to run multiple prompts concurrently

GitHub Support for querying GitHub

Import Template Learn how to import prompt templates into GenAIScript using `importTemplate` with support for mustache variable interpolation and file globs.

LogProbs Learn how to use logprobs to diagnose the performance of your scripts

Parameters Schema Parameters schema are used to define signatures of scripts, tools.

Git Git utilities for repository operations

Prompty Learn about the .prompty file format for parameterized prompts and its integration with GenAIScript for AI scripting.

Git Worktrees Git worktree support for managing multiple working directories

Model Aliases Give friendly names to models

Pyodide Run Python code in the JavaScript environment using Pyodide.

Tokenizers Tokenizers are used to split text into tokens.

Prompt Caching Learn how prompt caching can reduce processing time and costs for repetitive LLM prompts, with details on configuration and provider support including OpenAI and Anthropic.

Microsoft Teams Learn how to use the Microsoft Teams integration in your scripts.

User Input How to get user input in a script

Fence Formats Explore various fence formats supported by GenAIScript for optimal LLM input text formatting.

Notebook Explore the features of the Markdown Notebook for authoring documentation with script snippets and inline results.

Reasoning Models Specific information about OpenAI reasoning models.

Response Priming Learn how to prime LLM responses with specific syntax or format using the writeText function in scripts.

Stored Completions Metadata for the script