---
title: Conversational Plugins
deprecated: false
hidden: false
metadata:
  robots: index
---
Conversational plugins are tools that enable the [Agentic Reasoning Engine](/docs/agentic-reasoning-engine) to search for information, analyze data, and take action across enterprise systems.

# Context is King

When you're building conversational plugins, you should thoughtfully design the context for your agentic system.

Imagine you had a conversational plugin to help find calendar availability for two attendees:

1. **Tool 1: Obfuscated Context**
   ```json
   {
     "users": {
       "bob@example.com": [
         {
           "title": "BUSY",
           "start": "2026-12-18T03:05:00Z",
           "end": "2026-12-18T03:35:00Z",
           "meta": "e_9f2a"
         },
         {
           "title": "BUSY",
           "start": "2026-12-18T16:00:00Z",
           "end": "2026-12-18T17:00:00Z",
           "meta": "e_1c77"
         }
       ],
       "janet@example.com": [
         {
           "title": "BUSY",
           "start": "2026-12-18T03:20:00Z",
           "end": "2026-12-18T04:00:00Z",
           "meta": "e_aa10"
         }
       ]
     }
   }
   ```
   This tool forces your Assistant to...
   1. compute windows
   2. intersect across people
   3. count conflicts
   4. infer what’s conflicting (it can’t, really)
2. **Tool 2: Clear Context**
   ```json
   {
     "time_range": {
       "start": "2026-12-18T00:00:00Z",
       "end": "2026-12-19T00:00:00Z"
     },
     "meeting_duration_minutes": 30,
     "windows": [
       {
         "start": "2026-12-18T03:00:00Z",
         "end": "2026-12-18T03:30:00Z",
         "conflict_count": 2,
         "conflicts": [
           {
             "email": "bob@example.com",
             "conflict": {
               "type": "calendar_event",
               "title": "Q4 Marketing All Hands Dry-Run",
               "start": "2026-12-18T03:05:00Z",
               "end": "2026-12-18T03:35:00Z"
             }
           },
           ...
         ]
       },
       ...
     ]
   }
   ```
   This tool is much more "agent-friendly"
   1. The context is clear & easy to understand
   2. The work of calculating periods is already done for the AI agent

<br />

Creating tools that are well-designed for LLMs is your job as an agent engineer. When you make these design decisions, you impact...

1. **Functionality**: What operations are possible?
2. **ML Performance**: How accurately does the Reasoning Engine use your plugin?
3. **User Clarity**: How easy is it for users to understand what happened?
4. **Latency**: How fast does the plugin execute?
5. **Maintainability**: How easy is it to modify or extend?

<br />

We discuss best practices for [designing tools for agents here.](https://help.moveworks.com/docs/designing-conversation-processes)

# Conversational Plugin Architecture

Conversational plugins consist of two core components:

## Triggers

**[Natural Language Triggers](/docs/natural-language-triggers)** define how the plugin starts. They help the Reasoning Engine select your tool when users express certain intents.

**Example:** A plugin named "Check PTO Balance" with description "View remaining PTO days for employees" triggers on utterances like:

* "How much PTO do I have left?"
* "Check my vacation balance"
* "Do I have enough time off for next month?"

## Conversation Processes

**[Conversation Processes](/docs/conversation-processes)** define the execution flow. This is great for designing standard operating procedures you want your users to follow.

They're made up of a few pieces:

<Image border={false} src="https://files.readme.io/edb40fb11444b9ca964ec0ed6f2138dd4fe994486a8c406093c27c7a0bbcf9c4-CleanShot_2026-02-05_at_00.07.092x.png" />

<br />

1. **Slots**: Information collected from the user (dates, names, filters)
2. **Activities**: Operations that the plugin executes
   1. Content Activities - display information to users (e.g. show a legal disclaimer with PTO balances)
   2. Action Activities - perform work (fetch, transform, or update data)
3. **Decision Policies** - fork the interaction based on business rules (e.g. contractors get one experience, FTEs get another; event owners gets a different experience from event attendees, etc.)

# Example Use Cases

Conversational plugins enable users to interact with enterprise systems through natural language.

Here are some real-world examples:

* **PTO Balance Checker**: Employees ask "Do I have enough PTO for a week in November?" and instantly get their balance, remaining days, and availability confirmation.
* **Salesforce Account Management**: Account executives update account owners, territories, or status through natural language like "Change the owner of Acme Corp to Sarah Johnson."
* **Meeting Scheduler**: Users find meeting times across attendees' calendars and create meetings through "Schedule a team sync next week with John and Sarah."
* **IT Access Request**: Employees request access like "Give me access to the Marketing Slack channel"—the plugin checks permissions, gets approvals if needed, and grants access automatically.
* **Jira Ticket Creation**: Users create tickets conversationally: "Create a ticket for the login bug in production"—the plugin collects priority, component, and description through natural dialogue.