For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
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    • Overview
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  • New to Agent Studio? Start Here
  • Agentic Frameworks
  • Guides & Best Practices
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  • Data & Configuration
  • Triggers
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  • Ready to get started?
Agent Studio

Agent Studio Overview

Connect AI assistants to your business systems & content

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Quickstart Guides

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Built with
Quickstart

Build your first plugin in minutes

Core Concepts

Detailed information about how Moveworks AI agents work in our platform

Cookbooks

Collection of best practices & recommendations for common types of use cases

New to Agent Studio? Start Here

1

Build your first plugin

Follow Quickstart #1: Build Your First Plugin to build a working plugin in minutes.

2

Understand the architecture

Read Assistants, Agents, & Plugins to understand how the pieces fit together.

3

Learn the Golden Rule

Read The Golden Rule before building anything complex — it’s the most important design pattern.

4

Build with the reference below

Use the Building Blocks Reference and Guides sections on this page to find specific docs as you build.

5

Test before you ship

Review Testing & Error Handling before publishing your plugin.

Agentic Frameworks

Agent Studio lets you connect AI assistants to your business systems & content. There are three Agentic Frameworks that you can build on.

Content Gateway

Index your content for semantic search experiences.

Conversational AI Agents

Execute real-time actions to create, modify, read, & remove data from business systems.

Ambient AI Agents

Set up Ambient AI agents that run in the background

These agentic frameworks are interoperable on the Moveworks platform, so you can build experiences that span multiple patterns.

Guides & Best Practices

The Golden Rule

The single most important pattern for building reliable plugins

Decision Frameworks

When to use compound actions vs conversation processes, slot types, and more

Slot Best Practices

Anti-patterns and best practices for slot design

Conversation Process Best Practices

Anti-patterns and best practices for conversation processes

LLM Action Best Practices

When NOT to use LLM actions and the decision matrix

Building Blocks Reference

Quick links to every Agent Studio building block.

Common tasks

Starting from an outcome and not sure which primitive to use? Start here.

I want to…Use
Call an APIHTTP Action
Orchestrate multiple actionsCompound Action
Call an LLM inlinegenerate_text_action / generate_structured_value_action
Send a message to a usernotify expression
Branch on a conditionswitch expression
Handle an API failuretry_catch / raise
Loop over a listfor expression
Run actions concurrentlyparallel expression
End a compound action and return datareturn expression
Look up a user by emailget_user_by_email
Look up many users at oncebatch_get_users_by_email
Request human approvalcreate_generic_approval_request
Send batch chat notificationsbatch_send_plaintext_chat_notification
Collect user inputSlots
Validate a slot valueValidation policy with DSL
Branch a conversation on an action resultDecision Policy
Display a knowledge article or formContent Activity
Handle large API responses (>7K tokens)Response Sizes / SDA

Actions

HTTP Actions

REST API calls to external systems

Compound Actions

Orchestrate multi-step workflows

LLM Actions

generate_text and generate_structured_value

Compound Action Expressions

action

Invoke an HTTP, script, or compound action

for

Loop over arrays sequentially

switch

Conditional branching

parallel

Run expressions concurrently

return

End execution and return data

try / catch / raise

Error handling

notify

Send messages with action buttons

Conversation Process

Slots

Collect input values from users

Resolver Strategies

Convert natural language to data types

Activities

Action and content blocks

Control Flow

Decision policies, exit, and continue

Data & Configuration

Data Bank

Reference patterns: data., meta_info., response, value

DSL Reference

Validation rules, conditions, string functions

Data Mappers

MAP(), MERGE(), FILTER(), RENDER(), LOOKUP()

Data Types

Built-in and custom data types

Triggers

Natural Language Triggers

Conversational plugin activation

System Triggers

Webhooks and scheduled triggers

Samples

You can view hundreds of AI agents on our AI Agent Marketplace and import example templates to better understand how they are built.

Ready to get started?

Dive into our Quickstart Guides to start building your first plugins