# Code Execution & File Creation Source: https://docs.cassidyai.com/agents/advanced/code-execution-file-creation Control whether Agents can analyze data, generate files, and process large connector results by writing and running code. **Code Execution & File Creation** lets an [Agent](/agents/overview) write and run code when a request needs more than a normal text response. Agents use it to analyze spreadsheets, generate charts, create downloadable files, and work with large results from [Connectors](/agents/connectors/overview) or [Workflows](/workflows/overview). New custom Agents have **Code Execution & File Creation** enabled by default. If you're looking for Data Analysis, it has moved into this setting. Data analysis is one of the main things Code Execution & File Creation enables. ## What it enables When this setting is on, your Agent can: * Analyze CSVs, spreadsheets, and structured files * Create charts, summaries, and calculations from data * Generate downloadable documents, spreadsheets, presentations, and PDFs * Read large Connector or Workflow results that would otherwise be cut off * Work with files attached in Chat or referenced from the [Knowledge Base](/knowledge-base/overview) ## Check or change the setting Go to **Agents**, find the Agent you want to configure, click the **⋯** menu, and select **Edit**. In the **Customize** section, expand **Advanced Settings**. Use the **Code Execution & File Creation** toggle. Agent Advanced Settings showing Code Execution & File Creation enabled Click **Publish** to save the setting. ## Internet access Organization admins can also control whether code execution can access the internet while processing files or installing packages. See [Control code execution and file creation internet access](/settings/code-sandbox). ## Related Ask Agents to analyze spreadsheets, CSVs, and structured files. Generate documents, spreadsheets, presentations, and reports. Use Code Execution & File Creation inside Generate Text actions. # Configure data retention Source: https://docs.cassidyai.com/agents/advanced/data-retention Control how long an Agent's chat history is stored to meet your organization's data governance requirements. Chat retention settings let you control how long conversation history is stored for an [Agent](/agents/overview). This helps you manage data storage and comply with your organization's data governance policies. Agent chat retention is an **Enterprise-only** feature. [Contact our sales team](https://www.cassidyai.com/demo) to learn more about upgrading to Enterprise access. ## Required privilege Viewing and editing an Agent's chat retention settings requires the **Manage Agent Data Retention** admin privilege. Org Admins have this privilege by default. To grant it to other team members without full Admin access, add it to a [custom role](/settings/roles-and-groups). Saving changes or deleting chat history also requires edit access to that specific Agent. ## Set a retention policy Navigate to the Agent you want to configure and click the **...** menu. Select **Data Retention**. If you also have Agent export access, you'll find it nested under **Advanced** instead. Agent Advanced Settings Menu showing Data Retention In the **Update Data Retention Period** dialog, select from the available options: * **Forever** -- chat history is retained indefinitely, or until you manually delete it. This is the default for every Agent. * **Custom** -- specify a retention period based on your needs. Agent Data Retention configuration options If you selected **Custom**, enter the retention duration (e.g., `30`) in the **Period** field and select the unit from the dropdown: **Hours**, **Days**, **Weeks**, **Months**, or **Years**. The minimum period is 1 hour. Agent Data Retention custom retention period Click **Save** to apply the retention settings. Cassidy automatically deletes chat history older than the configured period, for every user who has chatted with this Agent. ## Manually delete chat history You can delete all existing chat history for an Agent at any time, regardless of the retention setting. Follow the steps above to navigate to the **Data Retention** settings for your Agent. Click **Delete Agent Chat History**, then click **Delete** again to confirm. Agent Data Retention custom retention period Deleting chat history -- whether by retention policy or manual deletion -- removes it for every user who has chatted with the Agent, and it cannot be recovered. Make sure your settings align with your organization's data governance requirements before configuring retention. ## Next steps Grant the Manage Agent Data Retention privilege to a custom role. Learn about SSO, SAML, RBAC, and other enterprise controls. # Build and configure an Agent Source: https://docs.cassidyai.com/agents/build-and-configure Create your first Agent, configure instructions, tools, and brand voice — manually or with the Agent Copilot. Build a custom AI Agent tailored to your team's needs — whether from a plain-language description, a template, or a blank slate. Once created, you can configure every aspect of your Agent manually or use the [Agent Copilot](#use-the-agent-copilot) to do it with plain language. ## Create a new Agent Navigate to the **Agents** page and click **+ New Agent** in the top right corner. Agent creation screen showing Custom Agent input, Create Blank Agent, Import Agent, and template gallery Select one of four options: * **Custom Agent** — Describe your desired Agent in plain language and Cassidy generates it based on your description. * **Create Blank Agent** — Start with an empty Agent for full manual customization. * **Import Agent** — Upload an Agent JSON file to add it to your organization. * **Template** — Browse 75+ templates organized by common use cases like sales, support, and marketing. If you selected **Custom Agent** or a **Template**, the [Agent Copilot](#use-the-agent-copilot) opens automatically. Describe what you want your Agent to do, answer a few clarifying questions, and the Copilot builds out the instructions, name, description, and configuration for you. Agent Copilot conversation during initial Agent creation After creation, review and fine-tune your Agent's settings in the editor. You can adjust the AI model, instructions, [knowledge](/agents/knowledge), [connectors](/agents/connectors/overview), [capabilities](/agents/capabilities/overview), and [brand voice](#brand-voice) at any time. Agent editor showing Setup tab with Copilot panel displaying changes summary When you're satisfied with the configuration, click **Publish** to make the Agent available for your team. See [Publish versions and review history](/agents/sharing-and-management#publish-versions-and-review-history) for details on versioning and publishing. Publish button dropdown in the Agent editor Once published, your Agent is ready to use in [Chat](/guides/chatting-with-an-agent) and [Workflows](/workflows/overview). ## The Agent editor The Agent editor is organized into three tabs: * **Setup** — The core configuration for your Agent: its identity, AI model, instructions, knowledge, tools, and brand voice. This is where you define what your Agent knows and what it can do. * **Deployments** — Where you make your Agent available outside of the Cassidy app — in [Slack](/integrations/slack/deploy-agent), [Microsoft Teams](/agents/deploy/microsoft-teams), [Google Chat](/agents/deploy/google-chat), [email](/agents/deploy/email), [embedded on your website](/agents/deploy/embed), or via [API](/agents/deploy/api). See [Deploy your Agent](#deploy-your-agent) for details. * **History** — A log of past conversations users have had with this Agent. Use it to review how the Agent is performing and identify areas to improve. You can configure your Agent in two ways: * **Manually** — Edit each setting directly in the editor. The sections below walk through every option available in the Setup tab. * **With the [Agent Copilot](#use-the-agent-copilot)** — Describe what you want in plain language and the Copilot updates the configuration for you. You can use the Copilot to build from scratch, make targeted changes, or optimize your existing instructions. Both approaches work together — use the Copilot to get started quickly, then fine-tune individual settings manually. ## Configure your Agent ### Appearance Set your Agent's icon, name, and description. The description helps your team understand what the Agent does and helps the system match the right Agent to a request. Agent appearance section with icon, name, and description fields ### AI model Select the foundation model your Agent uses. Cassidy supports models from OpenAI, Anthropic, and Google, each with different strengths. See [Choose the right AI model](/guides/choose-ai-model) for a comparison. AI model dropdown showing available foundation models Expand **Advanced Model Settings** to adjust the **temperature** — a value that controls how creative or deterministic the Agent's responses are. * **Lower temperature** (closer to 0): More consistent, predictable outputs. Best for tasks where the Agent should follow instructions precisely, like data extraction or compliance responses. * **Higher temperature** (closer to 1): More varied, creative outputs. Best for brainstorming, marketing copy, or other creative tasks. Advanced Model Settings panel with temperature slider ### Instructions Write clear instructions that describe what the Agent should do, how it should respond, and any rules it should follow. Be specific — the more detail you provide, the better the Agent performs. Instructions field showing structured instructions with role, objectives, and Knowledge Base references Reference [Knowledge Base](/knowledge-base/overview) items directly in instructions by typing **#** to search for and select documents. The Agent autonomously searches over referenced content when relevant. Knowledge Base reference search popup appearing after typing # in the instructions field You can pin a referenced item by hovering over it and clicking the pin icon. Pinned content is included directly in the prompt every time (counting toward token limits), so the Agent always sees it in full. Pin icon on a referenced Knowledge Base item in the instructions field Click **Optimize** at the bottom of the instructions field to have the [Agent Copilot](#use-the-agent-copilot) analyze and improve your instructions automatically. Optimize button at the bottom of the instructions field Agent instructions are one layer of AI customization. You can also set [user-level personalization](/agents/personalize-your-chats) and [organization-wide global instructions](/settings/global-instructions). See [Custom AI instructions](#custom-ai-instructions) for details. ### Knowledge Connect your Agent to your [Knowledge Base](/knowledge-base/overview) so it can search company documents and answer questions with accurate, cited responses. You can add entire collections, reference specific files in your instructions, and control when the Agent searches. Click **+ Add** in the Knowledge section to browse and select sources. Add Knowledge dialog showing Knowledge Base collections with checkboxes to select sources For the full walkthrough — including Smart Search, inline references, and pinning — see [Agent knowledge](/agents/knowledge). ### How Agents use tools When you give an Agent tools — [Connectors](#connectors), [Capabilities](#capabilities), [Skills](#skills), and [Workflows](#workflows) — you're not programming it to follow a rigid script. Instead, the Agent decides on its own which tools to use based on the conversation. Think of it like giving a team member access to various resources. If someone asks a question about a customer, the Agent recognizes it should check Salesforce. If they ask for a chart, it uses Code Execution & File Creation. If they need the latest industry news, it uses Web Search. The Agent reads the user's request, evaluates which tools are relevant, and calls them automatically — no manual triggering required. This means a single Agent can handle a wide range of requests as long as it has the right tools enabled. A sales Agent with Knowledge Base access, a HubSpot Connector, Web Search, and a follow-up email Workflow can answer product questions, pull up deal data, research a prospect's company, and send a personalized email — all in the same conversation. You control what's available by choosing which tools to enable. The Agent handles the rest. ### Connectors [Connectors](/agents/connectors/overview) let your Agent interact with external business tools in real time. Unlike [Knowledge Base](/knowledge-base/overview) integrations that sync content into Cassidy, Connectors query the external app when an action runs. Your Agent can look up a contact in HubSpot, run a Snowflake query, update a Salesforce record, or create a ServiceNow ticket, all within a conversation. Click **+ Add** in the Connectors section to browse available Connectors. Each Connector can use per-user or shared authentication. Under **Action permissions**, choose which actions are always allowed, ask every time, or are blocked. Available connectors include [HubSpot](/integrations/hubspot/agent-connector), [Salesforce](/integrations/salesforce/agent-connector), [Airtable](/integrations/airtable/agent-connector), [Snowflake](/integrations/snowflake/agent-connector), and more. See [Overview of Connectors](/agents/connectors/overview) for the full list, connection methods, and permission controls. ### Capabilities [Capabilities](/agents/capabilities/overview) are built-in abilities that extend what your Agent can do beyond conversation. They give Agents native abilities that don't require an external integration to set up. New custom Agents have **Code Execution & File Creation** enabled by default. This powers data analysis, file generation, and large-result handling. To review or change that setting, expand **Advanced Settings** in the **Customize** section. Click **+ Add Capabilities** to enable additional capabilities: * **[Web Search](/agents/capabilities/web-search)** — Search the internet for current information during conversations. Useful for research, competitive intelligence, and answering questions that require up-to-date knowledge. * **[Image Generation](/agents/capabilities/image-generation)** — Create and edit images from text descriptions using AI image models. * **[Artifacts](/agents/capabilities/artifacts)** — Build interactive content like dashboards, calculators, reports, and prototypes that users can interact with directly in the chat. * **[Browser Use](/agents/capabilities/browser-use)** — Navigate and interact with web pages to complete tasks like filling out forms, extracting content, or taking screenshots. Capabilities dropdown showing Web Search, Image Generation, Artifacts, and Browser Use See [Overview of Capabilities](/agents/capabilities/overview) for setup details and how each one works. ### Skills [Skills](/skills/overview) package reusable instructions, files, and tools that Agents can apply to specialized tasks. A Skill can be attached to multiple Agents and maintained in one place. Find the **Skills** section and click **Add**. Select the Skill the Agent should consider during conversations. Sales Agent editor showing the Skills section with PowerPoint Deck Generator attached Publish the Agent so the attached Skill is available to users. See [Use Skills in chat and Workflows](/skills/using-skills#attach-a-skill-to-an-agent) for setup details. ### Workflows Connect [Workflows](/workflows/overview) your Agent can trigger during a conversation. When a user's request matches a connected Workflow, the Agent collects the required inputs and runs the Workflow — sending emails, updating records, generating documents, or any other multi-step automation. Click **+ Add Workflow** to select from your published Workflows. Workflows section in the Agent editor with an added Workflow Add clear, descriptive names and descriptions to your Workflows so the Agent knows when to call them. The Agent uses the Workflow name and description to decide which Workflow matches a user's request. See [Call Workflow](/agents/call-workflow) for the full setup and how it works in practice. ### Brand voice Fine-tune your Agent's writing style by uploading examples of your organization's content. Click **Analyze** to have Cassidy study the examples and calibrate the Agent's tone, vocabulary, and style so every response sounds like your company. Brand voice section with the Analyze button Brand voice analysis showing detected writing style characteristics ## Use the Agent Copilot The Agent Copilot is an AI-powered building partner that helps you configure Agents using plain language. Instead of editing each setting manually, describe what you want and the Copilot generates or updates the Agent's configuration for you — including instructions, name, description, tools, and more. You can use the Copilot at any point: when creating a new Agent from scratch, when starting from a template, or when refining an existing Agent. It's the fastest way to go from an idea to a working Agent. Do not manually edit the Agent while the Copilot is working — your changes will be overwritten. ### Access the Copilot * **When creating a new Agent**: The Copilot opens automatically if you choose **Custom Agent** or a **Template**. * **When editing an existing Agent**: Click the wand icon in the top toolbar of the Agent editor. Wand icon in the Agent editor toolbar for accessing the Copilot ### How the Copilot works Type a plain-language description of the Agent or the change you want to make. The Copilot plans its approach and begins building. Copilot showing its planning process after receiving a description The Copilot may ask follow-up questions to refine the Agent. Questions come as multiple choice, multi-select, free-text, or Knowledge Base attachment prompts. You can answer or click **Skip** to move on. Copilot asking a multiple choice question to refine the Agent Expand the changes summary to see which fields were modified — icon, name, description, instructions, and more. The Copilot explains what it did and why. Copilot changes summary showing modified fields like Icon, Name, Description, and Instructions Send follow-up messages to refine further. You can ask the Copilot to update instructions, add tools, adjust the description, or make any other changes. Copilot conversation showing follow-up refinements to the Agent ### Copilot controls | Control | What it does | | - | - | | **Regenerate** | Try a different approach for any Copilot message | | **Edit message** | Modify your prompt and resubmit | | **Thumbs up/down** | Give feedback on Copilot responses | | **Restore checkpoint** | Revert the Agent to the version before a specific change | | **New chat** | Start a fresh Copilot conversation | | **Chat history** | Browse and return to earlier Copilot conversations | | **Attach Knowledge** | Insert Knowledge Base documents or folders as references in your message | ## Custom AI instructions Beyond the instructions you write directly on each Agent, Cassidy supports two additional layers of AI customization: * **[User-level personalization](/agents/personalize-your-chats)** — Individual users can set their name, role, and response preferences so the AI tailors responses in [Chat](/guides/chatting-with-an-agent). These apply across all chats regardless of which Agent is selected. See [Personalize your chats](/agents/personalize-your-chats) for setup instructions. * **[Global instructions](/settings/global-instructions)** — Admins can set organization-wide rules that apply to every Agent (and optionally Workflows). Use these for brand voice, compliance guardrails, or company context. ## Preview and test Click the preview icon in the top-right corner of the Agent editor to open a test chat. This lets you try out your Agent and iterate on changes before publishing. Preview chat panel in the Agent editor for testing the Agent ## Review chat history The **History** tab shows every conversation users have had with your Agent. Use it to monitor how the Agent handles real requests, spot patterns in what users are asking, and identify areas where the instructions or knowledge need refinement. History tab showing a list of past conversations with the Agent including chat titles, users, and dates ## Manage versions Access version history from the **Draft** dropdown at the top of the Agent editor. From here you can save drafts, publish new versions, compare changes between versions, and revert to a previous version. Draft dropdown showing version history with published versions, changes summary, and options to Publish Current Draft or Save Without Publishing For the full walkthrough, see [Publish versions and review history](/agents/sharing-and-management#publish-versions-and-review-history). ## Deploy your Agent Once published, your Agent is available in Cassidy's [Chat](/guides/chatting-with-an-agent) by default. To make it available where your team already works, open the **Deployments** tab in the Agent editor and configure one or more deployment channels: Chat with your Agent directly in Slack channels and DMs. Add your Agent as a Teams bot for conversations and commands. Deploy your Agent into Google Chat spaces. Deploy your Agent to a dedicated email address. Add a chat widget to your website for customers or internal users. Integrate your Agent into any application via the Cassidy API. ## Next steps Set up which Knowledge Base sources your Agent can search. Organize Agents into folders, manage permissions, and version history. Learn about Chat features including personalization, file uploads, and voice mode. Set organization-wide AI behavior rules for every Agent. # Call a Workflow Source: https://docs.cassidyai.com/agents/call-workflow Let Agents trigger and run Workflows during conversations to automate complex tasks. Call Workflow lets your [Agent](/agents/overview) run [Workflows](/workflows/overview) during a conversation. When a user's request is relevant to a connected Workflow, the Agent automatically decides to trigger it, collects the required inputs, and runs the Workflow — sending emails, updating records, generating documents, or any other multi-step automation. ## Add Workflows to an Agent Go to **Agents**, find the Agent you want to configure, and click **Edit**. Workflows section in the Agent editor with the Add Workflow button In the **Setup** tab, scroll to the **Workflows** section and click **+ Add Workflow**. Browse and select the published Workflows you want the Agent to be able to trigger. You can add multiple Workflows to a single Agent. Agent editor showing the Workflows section with connected Workflows and Add Workflow button Choose from your published Workflows. The Agent uses each Workflow's name and description to understand what it does and when to use it. Workflow selection dialog showing available published Workflows to add Click **Publish** to make the Workflows available in conversations. ## How it works Once Workflows are connected, the Agent autonomously decides when to trigger them based on the conversation context. This isn't a keyword match — the Agent reads the user's intent, evaluates which connected Workflow is relevant (if any), and decides whether to call it. 1. The user makes a request that's relevant to a connected Workflow (e.g., "Send a follow-up email to the prospect"). 2. The Agent determines which Workflow fits the request, then asks the user for any required inputs. 3. The Agent runs the Workflow and reports the results back in the conversation. Chat showing an Agent collecting required inputs and running a connected Workflow Add clear, descriptive names and descriptions to your Workflows — the Agent relies on these to understand when each Workflow should be used. The more context you provide in the Workflow's name and description, the better the Agent is at deciding when to trigger it. ## Next steps Create the Workflows your Agent will trigger. Learn about all the settings you can configure on an Agent. # Artifacts Source: https://docs.cassidyai.com/agents/capabilities/artifacts Enable Agents to create rich, interactive artifacts like documents, tables, and visualizations. The Artifacts capability lets your [Agent](/agents/overview) build interactive content during a conversation — dashboards, calculators, data visualizations, reports, and prototypes — without writing any code yourself. Artifacts render in a dedicated panel next to the chat, and you can iterate on them, open them in full view, and share them via link. ``` * **Modal** — fetch a token from your backend after authenticating the user, then pass it to `Cassidy.initialize` as `authToken`. Your app is responsible for refreshing tokens before they expire. ```html theme={null} ``` ### Troubleshooting If **Require Secure Token** is enabled and the embed does not receive a valid token, visitors will see an **Unauthorized** screen instead of the chat. This means the embed is working, but the token was missing, expired, or not passed correctly. Embedded chat Unauthorized error screen Common causes: * The embed code on your website does not include a token (for example, the iframe URL is missing `#token=...`, or the modal was initialized without `authToken`). * The token expired and your site has not refreshed it yet. * Your backend is not minting tokens correctly, or the token was created for a different deployment key. What to do: * If you copied embed code from Cassidy before setting up secure tokens, update your website with the latest embed instructions above. * Ask whoever manages your website to confirm tokens are being created on your backend and passed into the embed. * Try reloading the page. If the error persists, contact your site administrator or Cassidy support. ## Next steps Learn more about creating and configuring Agents. Deploy your Agent to a dedicated email address. Build a custom integration using the Cassidy API. # Deploy to Google Chat Source: https://docs.cassidyai.com/agents/deploy/google-chat Deploy your Agent to Google Chat so your team can access it in Google Workspace. Deploy your [Agent](/agents/overview) to Google Chat so team members can interact with it in direct messages and Spaces within Google Workspace. **Prerequisites:** * An Agent created in Cassidy * Google Workspace admin access * A [Google Cloud](https://console.cloud.google.com/) project (or the ability to create one) ## Connect Cassidy to Google Chat Go to **Agents** and select the Agent you want to deploy. Click **Edit** to open the Agent settings. Agents page showing the list of available Agents Navigate to the **Deployments** tab and select **Google Chat**. Agent settings with the Deployments tab selected Copy the **Webhook URL** provided by Cassidy. You'll need this when configuring the Chat bot in Google Cloud. Cassidy Deployments tab showing the Webhook URL for Google Chat Go to the [Google Cloud Console](https://console.cloud.google.com/). If you don't have an account, select your country, agree to the Terms of Service, and click **Agree and Continue**. Google Cloud Console setup page with Terms of Service Go to [Create a Project](https://console.cloud.google.com/projectcreate). Enter your project name and organization, select a location, and click **Create**. Google Cloud new project creation form Navigate to the [Chat API Library](https://console.cloud.google.com/apis/library/chat.googleapis.com). Make sure the correct project is selected and click **Enable**. Google Cloud API Library showing the Google Chat API Enable button Go to [Chat API Credentials](https://console.cloud.google.com/apis/api/chat.googleapis.com/credentials). Click the **Create Credentials** dropdown and select **Service Account**. Name it (for example, "Cassidy Service Account") and click **Create and Continue**. Skip optional steps and click **Done**. Google Cloud Credentials page showing the Create Credentials menu Service account creation form with name and description fields On the **Credentials** tab, click the pencil icon next to the service account you just created. Credentials tab showing the service account with the edit icon Go to the **Keys** tab, click **Add Key**, then select **Create New Key**. Choose **JSON** and click **Create** to download the key file. Service account Keys tab showing the Add Key menu Create private key dialog with JSON selected Go to [Chat API Configuration](https://console.cloud.google.com/apis/api/chat.googleapis.com/hangouts-chat) and set up the following: * Check **Build this Chat app as a Workspace add-on** * Fill in the **Application Info** (name, avatar URL, description) * Ensure **Enable Interactive Features** is enabled * Under **Connection Settings**, select **HTTP endpoint URL** * For **Triggers**, choose **Use a common HTTP endpoint URL for all triggers** and paste the **Webhook URL** from Cassidy * Under **Visibility**, select **Make this Chat app available to specific people and groups** and enter your email for testing Click **Save**. Google Chat API configuration showing application info and interactive features Google Chat API configuration showing connection settings and triggers with the Webhook URL Return to your Agent's **Deployments** tab in Cassidy. Under **Service Account Key**, click **Upload JSON File** and upload the key file you downloaded. Cassidy deployment settings showing the Upload JSON File button for the service account key Click **Create Google Chat Deployment**. Optionally toggle on **Show Knowledge Base References** to display source citations in responses. Cassidy Google Chat deployment settings with Show Knowledge Base References toggle Open Google Chat, start a new chat, and search for your Agent name. Send a message to confirm it responds. Google Chat conversation showing the Agent responding to a test message If you only need a few people to access the Agent, enter their emails in the **Visibility** setting and skip publishing to the Marketplace. ## Publish to your workspace To make the Agent available to your entire Google Workspace organization, publish it through the Google Workspace Marketplace. Go to the [Apps Marketplace API](https://console.cloud.google.com/apis/library/appsmarket-component.googleapis.com) and click **Enable**. Go to the [OAuth Consent Screen](https://console.cloud.google.com/auth/overview). Click **Get Started**, enter your app name, support email, and set the audience type to **Internal**. Click **Create**. In the [Google Workspace Marketplace SDK](https://console.cloud.google.com/apis/api/appsmarket-component.googleapis.com/googleapps_sdk), go to **App Configuration**: * Set app visibility to **Private** * Set installation settings to **Individual + Admin Install** * Ensure **Workspace add-on** is selected under App Integrations * Enter your contact info for developer information Click **Save Draft**. Google Workspace Marketplace SDK App Configuration page Go to the [Store Listing](https://console.cloud.google.com/apis/api/appsmarket-component.googleapis.com/googleapps_sdk_publish) tab. Fill in the app details (name, description, graphics), save as draft, then click **Publish**. Your Agent should now appear in the Google Workspace Marketplace under [internal apps](https://workspace.google.com/marketplace/mydomainapps). Google Workspace Marketplace showing the published Cassidy Agent as an internal app ## Using your Agent in Google Chat ### Direct messages Search for the Agent by name and start a direct message conversation. The Agent remembers the full conversation history across the thread. ### Spaces Add the Agent to a Google Chat Space and @mention it to start a conversation. The Agent replies in-thread and remembers messages where it was mentioned. ## Next steps Make your Agent available in Slack channels and DMs. Deploy your Agent to a dedicated email address. Embed your Agent on your website for external users. # Deploy to Microsoft Teams Source: https://docs.cassidyai.com/agents/deploy/microsoft-teams Deploy your Agent to Microsoft Teams so your team can chat with it in channels and direct messages. Deploy your [Agent](/agents/overview) to Microsoft Teams so team members can chat with it in channels, group chats, and direct messages. **May 2026 update:** Microsoft Teams changed its app and bot creation policies. Cassidy can no longer create the Microsoft Teams bot for you automatically, so this guide walks you through creating the bot in Microsoft Teams and using Cassidy to generate the app package. **Prerequisites** * An [Agent created in Cassidy](/agents/build-and-configure) * Access to the Teams Developer Portal * The ability to create a Microsoft Teams bot * Permission to submit custom apps for approval in Microsoft Teams, or a Teams admin who can upload the app package for you * Your Microsoft 365 Tenant ID * A Teams admin who can approve the app after you submit it ## How Microsoft Teams deployment works Cassidy generates the Microsoft Teams app package for you. You create the bot in the Teams Developer Portal, paste Cassidy's callback URL into the bot, download the app package from Cassidy, import the package into Teams, and submit the app for approval. Publishing the app in the Teams Developer Portal submits the app to your organization. A Teams admin must approve the app in the Teams admin center, then install it for users or make it available for users to install. ## Deploy your Agent In Cassidy, open the [Agent](/agents/overview) you want to deploy. Go to the **Deployments** tab and click **Connect** on the Microsoft Teams card. Fill in the details Cassidy will use to generate the Microsoft Teams app package: * **Short name** — The app name shown in Teams. Microsoft requires 30 characters or fewer. * **Long name** — Optional. Use this if your full app name is longer than the short name. * **Short description** — A brief description of the app. * **Long description** — A fuller description for app review. * **App color icon** and **App outline icon** — The icons shown in Teams. Click **Continue**. Cassidy Microsoft Teams deployment wizard showing the App details step Open the [Teams Developer Portal bot management page](https://dev.teams.microsoft.com/tools/bots). Click **New bot**, give the bot a name, and create it. In the bot's **Configure** tab, paste the callback URL from Cassidy into **Endpoint address** and save the bot. Teams Developer Portal Bot management page with the New bot button Teams Developer Portal bot Configure page showing the Endpoint address field In the bot's **Client secrets** tab, click **Create your first client secret** or **New client secret**. Copy the client secret value shown after creation. Microsoft only shows this value once. Do not copy the secret hint. Teams Developer Portal Client secrets tab before a client secret is created Teams Developer Portal dialog showing a newly created client secret value Return to Cassidy and paste: * **Bot ID** — On the Teams Developer Portal Bot management page, copy the value from the **Bot Id** column for the bot you created. You can also paste the full bot page URL and Cassidy will extract the Bot ID for you. * **Client secret** — Paste the one-time secret value from the previous step. * **Tenant ID** — Paste your Microsoft 365 Tenant ID. You can find your Tenant ID in the Microsoft Entra admin center. Microsoft documents the official steps in [Find your Microsoft 365 tenant ID](https://learn.microsoft.com/en-us/sharepoint/find-your-office-365-tenant-id). Teams Developer Portal Bot management page with the Bot Id column highlighted Click **Save and continue** before downloading the app package. The bot will not work until Cassidy has saved these credentials. In Cassidy, click **Download Teams app package**. Cassidy downloads a `.zip` file that contains the Teams app manifest and icons. The app package includes your bot ID, personal chat support, group chat support, channel support, and file support. Cassidy Microsoft Teams deployment wizard showing the app package downloaded confirmation In the Teams Developer Portal, go to **Apps** and click **Import app**. Use the import button to select the `.zip` file you downloaded from Cassidy. Cassidy already generated the app package with your bot configuration, so you do not need to manually add the bot after importing. Teams Developer Portal Import app dialog showing no issues found In the Teams Developer Portal, open **Publish > Publish to your org** and submit the app. This does not immediately make the app available. It creates an approval request for your Teams admin. Publishing can fail if your Microsoft Teams account does not have permission to submit custom apps for your organization. If you see a publish request error, send the generated `.zip` package to your Teams admin. Your Teams admin can upload and approve the app from the [Teams admin center Manage apps page](https://admin.teams.microsoft.com/policies/manage-apps). Teams Developer Portal Publish to your org page before submitting the app Teams Developer Portal Publish to your org page showing submitted and awaiting admin approval After you submit the app for organization approval, return to Cassidy. Cassidy already saved the bot credentials before package generation. You can configure whether the Agent shows Knowledge Base references and collects feedback from Teams users. If you need to repeat setup or rotate bot credentials, disconnect the deployment and connect Microsoft Teams again. ## Admin approval and installation in Teams admin center After the app is submitted to your organization, a Teams admin must approve and publish it in the Teams admin center. Publishing makes the app eligible for your organization, but the admin still needs to decide who gets it. Microsoft Teams can take a while to reflect approval, availability, and install changes after an admin updates the app. If the app still appears as pending or unavailable immediately after approval, wait and refresh Teams before troubleshooting further. Share this section with your Teams admin. In the Teams admin center, go to [**Teams apps > Manage apps**](https://admin.teams.microsoft.com/policies/manage-apps). Search for the app by name and open it. Teams admin center Manage apps page showing the submitted custom app Review the app details, permissions, publisher information, icons, and scope. The app should show the same name and descriptions you entered in Cassidy. Teams admin center app details page for the submitted custom app Click **Publish** to make the app available to users in your organization. Depending on your organization's Teams app policies, users may still need permission to install the app. Teams admin center app details page showing the Publish button and pending action state Open the **Users and groups** tab for the app. Choose who should get the app: * **Everyone** — Install or make the app available for all users in the organization. * **Specific users or groups** — Install or make the app available only for selected people or groups. * **No one** — Keep the app unavailable until the admin is ready. Teams admin center Users and groups tab showing the app installed for everyone Changes to app availability and installation can take time to propagate to users in Teams. ## Update your Teams app You can change the name, description, icons, and other details for an existing Agent app in the same Teams Developer Portal you used during setup. If you are updating an app icon, prepare the corresponding `.png` file: * **Color icon** — A full-color, 192 × 192 px image * **Outline icon** — A transparent, 32 × 32 px image with a white outline See [Microsoft's Teams app icon guidelines](https://learn.microsoft.com/en-us/microsoftteams/platform/concepts/design/design-teams-app-icon-store-appbar) for detailed design requirements. Go to the [Teams Developer Portal](https://dev.teams.microsoft.com/apps), select **Apps**, and open your Agent's app. Under **Configure**, update the details you want to change: * Open **Basic information** to change the app name, descriptions, or other app details. * Open **Branding** to replace the **Color icon** or **Outline icon**. Save your changes. Teams Developer Portal Branding page showing the Color icon and Outline icon settings Under **Configure**, open **Basic information** and change **Version** to a higher number. For example, change `1.0.0` to `1.0.1`. Click **Save**. Teams Developer Portal Basic information page showing an updated app version and the Save button Open **Publish > Publish to org** and click **Submit app update**. Teams Developer Portal Publish to your org page showing an app update awaiting admin approval If the update requires approval, a Teams admin must open [**Teams apps > Manage apps**](https://admin.teams.microsoft.com/policies/manage-apps), search for and open the app, then click **Publish update**. Your changes can take time to appear in Teams after approval. Teams admin center app details page showing a pending version and the Publish update button ## Chat with your Agent in Teams ### In a channel To use the Agent in a Microsoft Teams channel, mention the app using **@** followed by its short name. Start a new post and @mention the Agent — it will respond in that post's thread. The Agent only has access to that specific post's conversation history. Microsoft Teams channel showing an Agent mentioned with @ in a post ### In a direct message Start a new direct message to the Agent for a private, ongoing conversation. The Agent has access to the full chat history in DMs, giving it more context for follow-up questions. Microsoft Teams direct message conversation with a deployed Agent For any user to DM the Agent, they need to manually add the app first. Otherwise they may see "You cannot send messages to this bot." To add the app: 1. Click **Apps** in the left sidebar 2. Search for the app by name and click on it 3. Click **Add** 4. Start a new chat addressed to the app **Known limitations:** * After adding or removing the Agent, the Teams app list may take a moment to update * Bots in private channels are not supported * Bots cannot see the subject line of messages ## Next steps Make your Agent available in Slack channels and DMs. Add your Agent to Google Chat spaces. Deploy your Agent to a dedicated email address. # Agent knowledge Source: https://docs.cassidyai.com/agents/knowledge Set up what your Agent knows by adding Knowledge Base search, referencing specific files, and connecting sources. Give your Agent access to your company's documents so it can answer questions with accurate, cited responses. You can connect entire [Knowledge Base](/knowledge-base/overview) collections, reference specific files in your instructions, and control when the Agent searches. Before configuring Agent knowledge, make sure your [Knowledge Base is set up](/knowledge-base/setup) with the documents and sources your Agent needs. ## Add Knowledge Base search Go to **Agents**, find the Agent you want to configure, click **...** and select **Edit**. In the **Setup** tab, scroll to the **Knowledge** section and click **+ Add**. Knowledge section in the Agent editor showing connected collections and Smart Search toggle Browse your Knowledge Base and select the collections, folders, or individual documents you want your Agent to search. Click **Save** to confirm. Add Knowledge dialog showing Knowledge Base collections with checkboxes to select General Knowledge, Sales, Marketing, and Customer Support Once you add knowledge, the Agent searches it when answering questions and cites the sources it used. ## Smart Search When knowledge is added, you can enable **Smart Search** to let the Agent decide when to search the Knowledge Base. * **Smart Search on** -- The Agent only searches when it determines the Knowledge Base is likely to help answer the request. This reduces unnecessary searches and improves response speed. * **Smart Search off** -- The Agent searches the Knowledge Base on every request, regardless of whether it seems relevant. Smart Search toggle in the Knowledge section of the Agent editor Enable Smart Search for Agents that handle a mix of general questions and company-specific inquiries. Disable it for Agents that should always ground their answers in your documents. ## Reference files in instructions You can reference specific Knowledge Base items directly in your Agent's [instructions](/agents/build-and-configure#instructions) by typing **#** in the instructions field. This opens a search dialog where you can find and select documents. Knowledge Base reference search popup appearing after typing # in the instructions field When you reference an item this way: * The Agent autonomously searches over that content when it's relevant to a user's question. * The referenced item is automatically added to the Agent's Knowledge section. ### Pin content inline Hover over a referenced item in the instructions field and click the **pin icon** to include the content directly in the prompt. Pinned content counts toward the model's token limit but guarantees the Agent always sees it in full — useful for critical guidelines, style guides, or reference tables. Pin icon on a referenced Knowledge Base item in the instructions field Pinning only works when the content is small enough to fit inline. Larger documents should be added to the Knowledge section instead. ## When to use each approach | Approach | Best for | How it works | | - | - | - | | **Knowledge section** | Large document sets the Agent searches on demand | Agent performs semantic search across all added sources | | **# reference in instructions** | Specific documents the Agent should be aware of | Agent searches referenced content when relevant | | **Pinned content** | Small, critical documents the Agent must always see | Content included directly in every prompt | ## Next steps Upload documents, connect integrations, and import websites. Learn about all the other settings you can configure on an Agent. # Overview of Agents Source: https://docs.cassidyai.com/agents/overview Agents are AI teammates that answer questions, complete tasks, and take action across your tools — grounded in your company's knowledge. Agents are AI teammates that answer questions, complete tasks, and take action across your tools. They're grounded in your company's [Knowledge Base](/knowledge-base/overview), follow your guidelines, and work alongside your team — a sales rep who knows every deal, a support lead who's read every ticket, or an HR specialist who never forgets a policy. Build Agents in minutes with natural language — no code, no technical skills required. Cassidy puts the power to build AI in the hands of the people who know the work. Agents directory showing folders and configured Agents organized by team ## What makes an Agent Every Agent is built from a combination of settings that define how it behaves, what it knows, and what it can do. * **AI model** — Choose any foundation model as the base, including models from OpenAI, Anthropic, and Google. Switch as better ones arrive. See [Choose the right AI model](/guides/choose-ai-model) for guidance. * **Instructions and goals** — Describe your Agent's purpose in plain language. Define what it does, who it helps, and what rules to follow. * **[Knowledge Base](/knowledge-base/overview) search** — Agents pull from the same sources your best people use — documents, wikis, transcripts, and more. Responses cite the exact source so every answer is traceable. * **[Connectors](/agents/connectors/overview)** — Chat with live data from tools like HubSpot, Salesforce, Airtable, and Snowflake. Connectors query records, pull structured data, and perform actions like updating a contact or creating a ticket. * **[Capabilities](/agents/capabilities/overview)** — Agents go beyond chat. Give them abilities like [web search](/agents/capabilities/web-search), [image generation](/agents/capabilities/image-generation), [artifacts](/agents/capabilities/artifacts), and [browser use](/agents/capabilities/browser-use). * **[Advanced settings](/agents/advanced/code-execution-file-creation)** — Enable options like Code Execution & File Creation, which lets Agents analyze data, generate files, and handle large results from tools. * **[Skills](/skills/overview)** — Attach reusable procedures, files, and tools the Agent can apply when a request matches. * **Brand voice** — Train Agents on your style guides and sample content so every response matches how your company communicates. * **[Call Workflow](/agents/call-workflow)** — Trigger multi-step [Workflows](/workflows/overview) directly from a conversation to take action across your stack. * **Deployments** — Deploy to [Slack](/integrations/slack/deploy-agent), [Microsoft Teams](/agents/deploy/microsoft-teams), [Google Chat](/agents/deploy/google-chat), [email](/agents/deploy/email), or [embed on your website](/agents/deploy/embed). Agents live inside the tools your team uses every day. ## Default Agents Cassidy provides default Agents for each base AI model. These Agents are not trained on your organization's [Knowledge Base](/knowledge-base/overview) but are useful for general tasks that don't require company-specific context. ## How Agents work across Cassidy Agents power multiple features throughout the platform: In [Chat](/guides/chatting-with-an-agent), Agents let you quickly switch between different contexts — each Agent brings its own instructions, knowledge, and tools to the conversation. Agent chat showing a sales enablement Agent answering questions with cited Knowledge Base sources In [Workflows](/workflows/overview), you can use the [Generate Text with Agent](/reference/actions/generate-text-with-agent) action to apply an Agent's full configuration — instructions, Knowledge Base access, brand voice, and capabilities — to a Workflow step. Workflow builder showing a Generate Text with Agent action configured with a Marketing Manager Agent ## Next steps Create your first Agent from scratch or from a template. Connect your Agent to your Knowledge Base for accurate, cited answers. Add web search, image generation, artifacts, and more. Reuse your team's procedures across Agents and Workflow AI actions. Make your Agent available in Slack, Teams, or on your website. # Personalize your chats Source: https://docs.cassidyai.com/agents/personalize-your-chats Tell Cassidy who you are, connect your business apps, and add Skills so every chat understands your role, your tools, and how you like to work. A few minutes of setup makes every chat more useful, no matter which [Agent](/agents/overview) you use. There are three ways to personalize your chats, and all of them live under **Customize** in the sidebar: * **Personalization** — Cassidy learns your name, role, and how you like answers formatted. * **Connectors** — The Agent can reach the business apps you use every day, like Outlook or Google Sheets. * **Skills** — Cassidy follows reusable instructions for recurring tasks, like a meeting-prep routine your team has refined. These are your personal settings: they shape your own chats without changing any Agent for anyone else. ## Tell Cassidy who you are Personalization shapes how Cassidy responds in your chats — the name it uses, the context it assumes about your work, and the style of its answers. Click **Customize** in the sidebar and select **Personalization**. The same **Customize** menu is in the top-right corner of a new chat. * **What should Cassidy call you?** — The name you want used in responses. * **What do you do?** — Your role or focus, like "Sales leader" or "Product manager". This gives Cassidy context for its answers. * **How should Cassidy respond?** — Preferences, context, or a writing style you want used across your chats, up to 2,000 characters. For example: "I manage the enterprise sales team focused on AmLaw 200 firms. Keep responses concise and action-oriented. Use bullet points for key takeaways." Personalization settings showing fields for your name, role, and response preferences Click **Save personalization**. Your preferences now apply to every new chat. Personalization applies to your own chats in the Cassidy web app. It is not included in [Workflow](/workflows/overview) runs or external Agent deployments like [Slack](/integrations/slack/deploy-agent) or [Microsoft Teams](/agents/deploy/microsoft-teams), and changing your name here does not change your profile name. For organization-wide rules that apply to every Agent and Workflow, see [Global instructions](/settings/global-instructions). ## Connect your business apps [Connectors](/agents/connectors/overview) let the Agent read and update data in tools like Outlook, Google Calendar, and Google Sheets during a chat — look up today's meetings, draft an email, or pull numbers from a spreadsheet. Connect an app once under **Customize** → **Connectors** and it's available in every chat in the Cassidy web app. Connectors directory with installed apps and available Connectors You stay in control: each Connector has action permissions that decide what the Agent can do without asking and what needs your approval first. See [Connect and manage business apps](/agents/connectors/overview) for the full walkthrough, including approvals and managing connections. ## Add Skills [Skills](/skills/overview) are reusable instructions, files, and tools — like "Daily Workday Brief" or "Meeting Prep" — that Cassidy applies automatically when they match your request, so recurring tasks come out the way you want every time. Open **Customize** → **Skills** to see your active Skills, and browse the directory to install more from your team's library. Skills directory with navigation for installed, team, and private Skills See [Use Skills](/skills/using-skills) to learn how to install Skills and how Cassidy applies them in chat. ## Next steps Put your personalization to work in your first conversations. Set up Connectors and control action approvals. Install shared Skills and see how Cassidy applies them. Create an Agent tailored to your team's work. # Share and manage Agents Source: https://docs.cassidyai.com/agents/sharing-and-management Manage Agent permissions, organize with folders, and publish versions. Control who can access and edit your Agents, organize them into folders, and manage version history. ## Organize Agents with folders Folders help keep your Agent library organized and let you set permissions at the folder level. Click **Agents** in the left sidebar. Click **Create a Folder** or the **+** icon next to the **Folders** heading in the sidebar. Agents sidebar showing the Create a Folder button and + icon next to Folders heading Enter a name and choose an access level: * **Team can edit** — Anyone in your organization can view and edit Agents in this folder. * **Team can view** — Anyone can view but not edit. * **Restricted** — Only specific people and [groups](/settings/roles-and-groups) you add can access the folder. Folder creation dialog showing name field and permission options: Team can edit, Team can view, and Restricted Drag and drop Agents from the main area into the folder. You can move Agents between folders at any time. ## Manage permissions ### From the Agents page Update folder permissions by clicking **...** on a folder and selecting **Share**. From there you can: * Change the access type between **Team can edit**, **Team can view**, and **Restricted**. * When using **Restricted** access, add specific people or [groups](/settings/roles-and-groups) who should have access. Start typing a name or email address and select from the list. For each person or group, set either **Can edit** or **Can view** permissions. * Remove access by clicking the **x** next to a person or group. Folder context menu showing the Share option Folder sharing dialog showing access type selector and people and groups with Can edit or Can view permissions Set up [roles and groups](/settings/roles-and-groups) to simplify permission management. Instead of adding individuals one by one, create groups like "Sales Team" or "Support Leads" and grant access to the entire group at once. ### Grant access to Agent chat history Sharing an Agent folder does not automatically let recipients view other team members' conversations. You can separately grant a person or group access to all chat history for the Agents in that folder. Chat history can contain sensitive information. Only grant this access to people who need to review conversations for responsibilities such as quality assurance, support oversight, or compliance. By default, only Admins can grant or revoke chat history access. To delegate this responsibility, create a [custom role](/settings/roles-and-groups#create-a-custom-role) with the **Grant Access to Agent Chat History** privilege. On the **Agents** page, click **...** on the folder containing the Agents, then select **Share**. Agent folder context menu showing the Share option Add a person or group, then choose whether they **Can view** or **Can edit** the Agents in the folder. To update someone who already has access, find the person or group in the sharing dialog and open the **...** menu next to their name. Select **Can view chat history**, then confirm the warning. The person or group can now view conversations that any team member has had with the Agents in this folder. Agent folder sharing dialog with the Customer Support group's permissions menu showing Can view chat history selected To revoke access, open the folder's sharing settings, click **...** next to the person or group, and clear **Can view chat history**. Removing chat history access does not remove their existing **Can view** or **Can edit** access to the Agents. ### From the Agent editor You can also manage permissions while editing an Agent: In the Agent editor, click **...** and select **Organize & Share Agent** under **Sharing**. Agent editor menu showing Organize and Share Agent option under Sharing Select where to save the Agent — **Team**, **Private**, or a specific folder. You can create new folders directly from this dialog. Agent location picker showing Team, Private, and folder options Click **Save** to apply the new permissions. To make an Agent private, drag it into the **Private** section or a private folder on the Agents page. ## Pin an Agent Pin an Agent when you want quick access from the main sidebar and Agent selectors. Only published Agents can be pinned. Open the Agent's **...** menu and select **Pin to sidebar**. Personal pins are visible only to you. Admins with the **Customize Pinned Resources** privilege can instead select **Pin for organization**. An organization pin appears for everyone who already has access to the Agent. Pinning an Agent for your organization does not share it. If the Agent is private or shared with a limited group, only those people will see the pin. Agent actions menu showing Pin to sidebar and Pin for organization ## Publish versions and review history Agents use a versioning system so you can test changes before making them live. ### Save drafts While editing, click **Draft** then **Save Without Publishing** to save your changes without making them available to end users. This lets you iterate on changes over time. ### Publish a version Click **Publish** or go to **Draft** and select **Publish Current Draft**. Publish button dropdown showing Publish Current Draft and Save Without Publishing options Enter a **Version Name** and optional description to document what changed. This helps you track changes over time. Publish dialog with Version Name and description fields Click **Create Version** to save the version, or **Publish** to save and immediately make it live. ### Review version history Open the **Draft** dropdown at the top of the Agent editor to see all published versions and what changed since each one. Draft dropdown showing version history with published versions, changes since each version, and Publish Current Draft option To revert to a previous version, click on the desired version. A modal shows the version details and changes being restored. Click **Restore Version** to confirm. Restore Version modal showing version details and a confirm button Reverting does not delete newer versions — you can go back to any saved version at any time. ## Next steps Create a new Agent or edit an existing one. Set up user groups to simplify permission management. # Install the Chrome and Edge extension Source: https://docs.cassidyai.com/extensions/chrome Access your Cassidy Agents from any webpage with the browser extension for Chrome and Edge. The Cassidy browser extension lets you chat with your [Agents](/agents/overview) while browsing any website. Summarize articles, draft email replies, write LinkedIn messages, and analyze page content — all without leaving your browser tab. The extension works with both **Google Chrome** and **Microsoft Edge**. ## Install the extension Go to the [Cassidy AI extension](https://chrome.google.com/webstore/detail/cassidyai/kmkfkldjbchieogojgcbalncifahjogg) in the Chrome Web Store. You can also access this store from Microsoft Edge. Cassidy AI extension listing in the Chrome Web Store Click **Add to Chrome** (in Chrome) or **Get** (in Edge) to start the installation. A dialog will ask for permission to add the extension. Review the request and click **Add extension** to allow Cassidy to read page content. Chrome permission dialog asking to add the Cassidy extension For quick access, pin Cassidy to your browser toolbar. Click the **puzzle piece** icon in the toolbar to open the extensions menu, then click the **pin** icon next to Cassidy. Extensions menu showing the pin icon next to Cassidy Once pinned, you'll see the Cassidy icon in your toolbar. Click it to open the extension and start chatting with your Agents. ## Configure the extension After installing, you can customize when and how the extension appears. Locate the Cassidy tag in the bottom-right corner of your browser window. Hover over it to reveal the **gear** icon, then click it to open settings. Cassidy tag in the bottom-right corner of the browser with the settings gear icon revealed on hover In the settings menu, configure when to show the Cassidy tag: * **Show Cassidy icon on all browser tabs** — displays the tag on every webpage you visit. * **Show Cassidy icon when selecting text** — displays the tag only when you highlight text on a page. Cassidy extension settings with display toggle options Your preferences save automatically when you close the settings menu. When the Agent needs to read your current page, it requests your permission. You can respond in one of three ways: * **Always allow** — the Agent reads the page automatically on every message without prompting again. * **Allow once** — the Agent reads the page for this message only and asks again next time. * **Deny** — the Agent responds without reading the page. Agent approval card with Always allow, Allow once, and Deny buttons for granting page access You can change this preference at any time from the **Tools** dropdown in the chat input area. Toggle **View Page** on or off to control whether the Agent automatically reads pages. Tools dropdown in the chat input area showing the View Page toggle enabled ## What you can do with the extension ### Draft email replies When viewing an email in Gmail, click the **Automate** button that appears next to the reply buttons. The Cassidy chat panel opens with a suggested prompt based on the email thread, giving you a starting point for your reply. Gmail email view with the Automate dropdown showing Summarize email thread and Write reply to email options ### Write LinkedIn messages On LinkedIn, the **Automate** button appears next to message controls. Click it to open the chat panel with a pre-filled prompt that helps you craft a personalized message based on the conversation context. Cassidy Automate button on LinkedIn with a suggested message prompt ### Summarize and analyze webpages Click the Cassidy tag on any webpage to open the chat panel. Ask your Agent to summarize the page, extract key takeaways, or answer questions about the content. The Agent automatically reads the page to provide context-aware responses. Cassidy extension sidebar summarizing a Forbes article with key takeaways about Apple MacBook Pro ### Work with selected text Highlight any text on a page to trigger the Cassidy tag (if the display setting is enabled). Click it to open the chat panel with the selected text included, so you can ask your Agent to rewrite it, translate it, explain it, or use it as context for a task. Highlighted text on a Forbes article with Cassidy extension sidebar showing analysis of the selected text ## Next steps Customize the Agent your extension uses with instructions, knowledge, and capabilities. Bring Cassidy directly into your Outlook inbox. Add Cassidy to your iPhone or Android home screen. # Deploy extensions for your organization from Microsoft 365 Source: https://docs.cassidyai.com/extensions/microsoft-365-admin-deploy Install Cassidy's Office and Outlook extensions for your entire team from the Microsoft 365 admin center. If you're a Microsoft 365 admin, you can deploy the Cassidy extensions to everyone in your organization — or to specific users and groups — so team members don't need to install them individually. This uses Microsoft's built-in **Integrated Apps** portal. **Prerequisites**: You need **Global Admin** or **Exchange Admin** access in your Microsoft 365 tenant. ## Deploy a Cassidy extension Sign in to the [Microsoft 365 admin center](https://admin.microsoft.com) and go to **Settings** → **Integrated apps** (you may need to click "Show all" for Settings to appear). Microsoft 365 admin center Integrated Apps page under Settings Click **Get apps** to open the Microsoft Marketplace. Search for **Cassidy** and select the extension you want to deploy: * **Cassidy for Outlook** — brings Agents into the Outlook inbox * **Cassidy** — brings Agents into Word, Excel, and PowerPoint Microsoft Marketplace search results showing the Cassidy for Outlook and Cassidy extensions Click **Deploy** (or **Get it now** followed by **Deploy**) on the extension listing. This opens the deployment configuration wizard. Select who the extension should be deployed to: * **Entire organization** — every user in your tenant * **Specific users/groups** — only the people or Microsoft 365 groups you select Deployment wizard showing user assignment options including Entire organization and Specific users/groups ## Manage the deployment After deploying, you can update who has access at any time: 1. Go to **Settings** → **Integrated apps** in the [Microsoft 365 admin center](https://admin.microsoft.com). 2. Find the Cassidy extension in the **Deployed apps** list and click on it. 3. Under the **Users** tab, update the assignment to add or remove users and groups. 4. Click **Update** to save your changes. ## Next steps Individual installation instructions for end users. Individual installation instructions for Word, Excel, and PowerPoint. # Install the Microsoft Office extension Source: https://docs.cassidyai.com/extensions/microsoft-office Access your Cassidy Agents in Microsoft Word, Excel, and PowerPoint to generate content, edit files, and answer questions without leaving the app. The Cassidy Microsoft Office extension brings your [Agents](/agents/overview) into Word, Excel, and PowerPoint. Draft and rewrite documents, analyze and edit workbooks, generate and refine slides, and tap into your company's [Knowledge Base](/knowledge-base/overview) — all from a side panel inside each app. A single installation enables Cassidy in all three apps. ## Install the extension Go to the [Cassidy Microsoft Office extension](https://appsource.microsoft.com/en-us/product/office/WA200008195) in the Microsoft Office Store. Cassidy extension listing in the Microsoft Office Store Click **Get it now** to begin the installation process. If you're not already signed in, you'll be prompted to log in to your Microsoft account before continuing. Microsoft sign-in prompt during Cassidy extension installation A confirmation dialog shows your account information. Verify you're signed in with the correct account and click **Get it now**. Click **Edit your details** if you need to make changes. Microsoft account confirmation dialog with a Get it now button A dialog asks if you'd like to install Cassidy for Word, Excel, and PowerPoint. Click **Continue** to proceed. Installation confirmation dialog with a Continue button Once installed, you'll see the Cassidy icon in the toolbar of Word, Excel, and PowerPoint. You can also find it through each app's **Add-ins** menu. Cassidy icon visible in the Word toolbar Cassidy listed in the Add-ins menu in Word The first time you open the extension in any of the three apps, you'll be prompted to sign in to your Cassidy account. Signing in once covers Word, Excel, and PowerPoint. Cassidy login screen inside the Microsoft Office extension side panel ## Use Cassidy in Word Open the Word document you want to work with. Click the **Cassidy** icon from your toolbar or the Add-ins menu. The Agent opens in a side panel. A prompt is automatically populated in the chat box based on your document, giving you a starting point. You can ask the Agent to draft new content, rewrite a section, summarize the document, or answer questions using your [Knowledge Base](/knowledge-base/overview). Cassidy Agent side panel in Word with a suggested prompt for document editing Once you're happy with the generated content, click **Add to Document** to insert it directly into your Word document. ## Use Cassidy in Excel Use Cassidy in Excel when you want an Agent to help with the workbook you have open. Ask questions about your data, fill in spreadsheet answers, build charts, and more. Excel workbook with a chart created by a Cassidy Agent in the side panel Select the cell or range you want the Agent to work with. Cassidy shows your current Excel selection above the chat box so you can confirm the Agent has the right context. Excel workbook with a selected range shown in the Cassidy side panel Click the **Cassidy** icon from your toolbar and ask for the outcome you want. For example, ask the Agent to answer RFP questions, generate data insights, or create a chart. Cassidy side panel in Excel with a prompt asking the Agent to plot revenue versus net income If the Agent needs to change your workbook, Cassidy shows an approval card before applying the edit. Review the pending edits, then choose **Allow once**, **Allow all edits**, or **Deny**. Cassidy approval card in Excel with Allow all edits, Allow once, and Deny options Use the edit permission button in the chat toolbar to choose how Cassidy handles future workbook edits. Select **Ask before edits** when you want to review each change, or **Accept all edits** when you want the Agent to apply edits without asking again in that chat. Excel extension edit permission dropdown with Ask before edits and Accept all edits options ## Use Cassidy in PowerPoint Use Cassidy in PowerPoint when you want an Agent to help with the deck you have open. Generate new slides, rewrite copy, restructure bullets, draft speaker notes, and ask questions about your presentation — all without leaving PowerPoint. Starting a new presentation or making substantial changes through conversation? Use [Cassidy Slides](/slides/create-and-export-presentations), then export the finished deck to PowerPoint. Use the Office extension for native edits to a PowerPoint file you already have open. PowerPoint presentation with a slide edited by a Cassidy Agent in the side panel Select one or more slides in the thumbnail panel, or click a shape on a slide, when you want the Agent to focus on a specific part of the deck. Cassidy shows your selection above the chat box, and the Agent always has visibility into your full deck so it can place new slides in the right spot. PowerPoint with selected slides shown in the Cassidy side panel Click the **Cassidy** icon from your toolbar and ask for the outcome you want. Common prompts: * Polish the selected slide's wording, structure, and visual clarity * Add a new slide to this presentation about a given topic * Summarize this presentation Cassidy side panel in PowerPoint with a prompt to tighten bullets on the selected slide Before changing your deck, Cassidy shows an approval card describing what the Agent wants to do. Choose **Allow once**, **Allow all edits**, or **Deny**. Cassidy approval card in PowerPoint with Allow all edits, Allow once, and Deny options Use the edit permission button in the chat toolbar to choose how Cassidy handles future deck edits. Select **Ask before edits** when you want to review each change, or **Accept all edits** when you want the Agent to apply edits without asking again in that chat. PowerPoint extension edit permission dropdown with Ask before edits and Accept all edits options ## Next steps Customize the Agent your extension uses with instructions, knowledge, and capabilities. Add company documents so your Agent gives accurate, context-aware answers in Word, Excel, and PowerPoint. Install Cassidy extensions for your entire team from the Microsoft 365 admin center. Build, refine, present, and export a new deck through an Agent conversation. # Add Cassidy to your phone's home screen Source: https://docs.cassidyai.com/extensions/mobile Add Cassidy to your iPhone or Android home screen so Chat opens like an app. Chat with Agents, continue conversations, and run Workflows from your phone. You can chat with your [Agents](/agents/overview) from your phone. Add Cassidy to your home screen so it opens like an app — with its own icon, and without the browser address bar. On your phone, Cassidy Chat is the full experience: start and continue conversations, switch Agents, attach files, use voice, and run [Workflows](/workflows/overview). Use a desktop browser to build Agents, edit Workflows, and manage your [Knowledge Base](/knowledge-base/overview). ## Add to your home screen Sign in at [app.cassidy.ai](https://app.cassidy.ai) on your phone first, then follow the steps for your device. Use **Safari**. Other iPhone browsers may not add Cassidy as an app. Open **Safari** and go to [app.cassidy.ai](https://app.cassidy.ai). Sign in if you aren't already. Safari on iPhone showing Cassidy Chat after sign-in, with the Safari toolbar at the bottom Tap the **•••** button in the Safari toolbar, then tap **Share**. If you already see a **Share** button — a square with an arrow pointing up — tap that instead. Safari menu on iPhone with Share highlighted The share sheet opens with apps like Messages and Mail. Scroll down and tap **Add to Home Screen**. If you don't see that option, scroll to the bottom, tap **Edit Actions**, and add **Add to Home Screen**. iPhone share sheet showing AirDrop, Messages, Mail, and other sharing options iPhone share sheet scrolled down with Add to Home Screen highlighted Confirm the name **Cassidy**. If you see **Open as Web App**, leave it turned on so Cassidy opens like an app instead of a Safari tab. Tap **Add**. The Cassidy icon appears on your home screen. Add to Home Screen confirmation showing the Cassidy icon, name, Open as Web App toggle, and Add button Tap the Cassidy icon. Chat opens without the Safari address bar. iPhone home screen with the Cassidy app icon Cassidy is on your home screen and opens like an app. These steps also work on iPad. Add Cassidy from Safari, then tap the icon on your Home Screen or in the Dock. Use **Chrome**. After you tap **Install and create shortcut**, Chrome may ask whether to **Install** Cassidy or **Create shortcut**. Choose **Install**. Open **Chrome** and go to [app.cassidy.ai](https://app.cassidy.ai). Sign in if you aren't already, then tap the **three-dot** menu in the top-right corner of Chrome. Chrome on Android showing Cassidy Chat after sign-in, with the three-dot menu highlighted Tap **Install and create shortcut**. Some phones show **Add to Home screen** or **Install app** in this menu instead. If you see **Install app**, tap that, then skip the next step. Chrome menu on Android with Install and create shortcut highlighted If Chrome asks how to add Cassidy, tap **Install**. Don't choose **Create shortcut** — shortcuts open in Chrome with the address bar. Chrome Install and create shortcut sheet with Install highlighted above Create shortcut Review the Cassidy name and icon, then tap **Install**. Android Install app dialog showing the Cassidy icon, name, and Install button Tap the Cassidy icon on your home screen or in your app drawer. Chat opens without the Chrome address bar. Android home screen with the Cassidy app icon Cassidy is installed and opens like an app. Firefox and Samsung Internet can also add Cassidy to your home screen from their menus. Look for **Install** or **Add page to Home screen**. ## Use Cassidy on your phone After you add Cassidy, tap the icon anytime to open Chat. If you're asked to sign in, use the same account you use on desktop. You can: * Start a new chat with the **+** button * Open past chats from the **menu** in the top-left corner * Switch [Agents](/agents/overview) * Send messages, attach files, and use voice * Run a [Workflow](/workflows/overview) from Chat * Add items from your [Knowledge Base](/knowledge-base/overview) to a message * Share a chat from the header For a full walkthrough of Chat, see [Chat with an Agent](/guides/chatting-with-an-agent). ## Troubleshooting Make sure you're in **Safari**, not Chrome or an in-app browser (for example, a link opened from Slack or Gmail). Open [app.cassidy.ai](https://app.cassidy.ai) in Safari itself. Also avoid **Private Browsing**. Close the private tab, open a regular Safari tab, and try again. If the action still doesn't appear, open the share sheet, scroll to the bottom, tap **Edit Actions**, and add **Add to Home Screen**. On iPhone, delete the home screen icon, add Cassidy again, and leave **Open as Web App** turned on. On Android, choose **Install** instead of **Create shortcut** if Chrome asks. Sign in at [app.cassidy.ai](https://app.cassidy.ai) in a regular browser tab first, then add Cassidy to your home screen again. Private or incognito tabs won't keep you signed in. Still stuck? Contact support at [support@cassidy.ai](mailto:support@cassidy.ai). ## Next steps Select Agents, upload files, use tools, and continue conversations. Use Cassidy while you browse on your computer. # Install the Outlook extension Source: https://docs.cassidyai.com/extensions/outlook Access your Cassidy Agents directly in Outlook to draft replies, summarize threads, and automate email tasks. The Cassidy Outlook extension brings your [Agents](/agents/overview) into your inbox. Draft email replies, summarize long threads, and work with email content — all from a side panel within Outlook. ## Install the extension Go to the [Cassidy Outlook extension](https://appsource.microsoft.com/en-us/product/office/WA200008206) in the Microsoft Office Store. Cassidy for Outlook listing in the Microsoft Office Store Click **Get it now** to begin the installation process. If you're not already signed in, you'll be prompted to log in to your Microsoft account before continuing. Microsoft sign-in prompt during the Cassidy extension installation A confirmation dialog shows your account information. Verify you're signed in with the correct account and click **Get it now**. Click **Edit your details** if you need to make changes. Microsoft account confirmation dialog showing user details with a Get it now button A dialog asks if you'd like to install Cassidy for Outlook. Click **Continue** to proceed. Installation confirmation dialog with a Continue button Once installed, find the Cassidy icon by clicking the **three dots** (more actions) at the right of the Outlook toolbar. Outlook toolbar with the more actions menu showing the Cassidy extension Cassidy listed in the Outlook overflow menu For quicker access, click **Customize toolbar** from the overflow menu and add Cassidy to your main toolbar. Customize toolbar option in the Outlook overflow menu Animation showing how to pin Cassidy to the Outlook toolbar ## Use the extension Once installed, open any email and click the **Cassidy** icon in your toolbar to open the Agent side panel. From there you can draft replies, summarize threads, and ask questions about email content — all without leaving Outlook. ### Draft email replies Open the email you want to respond to. An email open in the Outlook reading pane Click the **Cassidy** icon from your toolbar. The Agent opens in a side panel next to your email. Cassidy Agent side panel open next to an email in Outlook A prompt is automatically populated in the chat box based on the email content, giving you a starting point for your reply. Cassidy chat panel showing a suggested reply prompt based on the email thread Once you're happy with the generated reply, click **Add to Reply** to insert it directly into your email. Add to Reply button in the Cassidy chat panel Animation showing the full flow of drafting and inserting an email reply with Cassidy ### Summarize email threads Open a lengthy email conversation you need to catch up on. Click the **Cassidy** icon from your toolbar and ask for a summary of the thread. Cassidy chat panel with a prompt asking for a thread summary Cassidy analyzes the conversation and provides a concise summary of important points, action items, and decisions. Cassidy Agent displaying a summary of an email thread with key points and action items ## Next steps Customize the Agent your extension uses with instructions, knowledge, and capabilities. Bring Cassidy into your documents, spreadsheets, and presentations. Install Cassidy extensions for your entire team from the Microsoft 365 admin center. # Analyze data with an Agent Source: https://docs.cassidyai.com/guides/analyze-data-with-agent Ask an Agent to analyze spreadsheets, CSVs, and structured files to find insights, create charts, and answer questions. Agents can analyze structured data like CSVs, spreadsheets, and tabular files. Instead of treating files as plain text, an Agent can write and run code to inspect the actual data, calculate results, create visualizations, and explain the findings in conversation. This is powered by [Code Execution & File Creation](/agents/advanced/code-execution-file-creation), which is enabled by default for new custom Agents. ## Before you start If data analysis is not available for an Agent, edit the Agent and make sure **Code Execution & File Creation** is enabled under **Customize** > **Advanced Settings**. ## Provide data for analysis You can provide data in several ways: * **Upload a file in Chat** — Attach a CSV, Excel file, or other structured data file directly in the conversation. * **Reference a Knowledge Base file** — If your data is already in the [Knowledge Base](/knowledge-base/overview), reference it in the conversation or in the Agent's instructions using **#**. * **Use Connector results** — If your Agent has [Connectors](/agents/connectors/overview), Code Execution & File Creation can help the Agent work with large structured results from those tools. ## Analyze a file in Chat Open [Chat](/guides/chatting-with-an-agent) and choose the Agent you want to use. Upload a spreadsheet, CSV, or other structured file. Ask the Agent what you want to learn from the data. For example: *"Analyze this sales data and show monthly revenue trends, top-performing products, and any unusual changes."* The Agent writes and runs code behind the scenes, then returns the results in the conversation. It can include summaries, tables, charts, or downloadable files depending on your request. Agent analyzing uploaded data and returning results in a conversation ## Use Knowledge Base files If you want the Agent to analyze the same file regularly, add the file to the Agent's instructions or reference a [Knowledge Base](/knowledge-base/overview) file in the conversation. Knowledge Base files can also come from synced integrations like Google Drive, OneDrive, SharePoint, and Box, so the Agent can analyze the latest version. Agent instructions referencing a specific data file from the Knowledge Base for analysis ## Tips for best results The more detail you provide, the fewer assumptions the Agent needs to make. * **Use specific column names** — Reference columns by their actual names, such as "Location" or "Revenue." * **Explain value formats** — Describe whether states are abbreviated, dates use a specific format, or currencies are mixed. * **Provide context about the data source** — Explain where the data came from and what each table represents. * **Use a powerful model** — Data analysis works best with high-powered, reasoning-capable models. See [Choose the right AI model](/guides/choose-ai-model). ## Related Learn how the Agent setting works and how to turn it on or off. Generate documents, spreadsheets, presentations, and reports. Analyze files and generate reports in repeatable Workflows. # Chat with an Agent Source: https://docs.cassidyai.com/guides/chatting-with-an-agent Everything you need to know about chatting: selecting Agents, uploading files, using tools, voice mode, and more. Cassidy's Chat interface is where you interact with AI [Agents](/agents/overview), access your [Knowledge Base](/knowledge-base/overview), and run [Workflows](/workflows/overview) — all in one place. Cassidy Chat interface with the shared sidebar, Projects, recent chats, and New Chat button To start a new chat, click **New Chat** in the sidebar or on Home. The **Chats** tab on Home is where you can find and reopen previous conversations. You can also chat from your [phone](/extensions/mobile), through the [Chrome extension](/extensions/chrome), [Outlook extension](/extensions/outlook), [Microsoft Office extension](/extensions/microsoft-office) (Word, Excel, and PowerPoint), and external deployments like [Slack](/integrations/slack/deploy-agent), [Microsoft Teams](/agents/deploy/microsoft-teams), [Google Chat](/agents/deploy/google-chat), [email](/agents/deploy/email), [embed](/agents/deploy/embed), and [API](/agents/deploy/api). ## Find chats and resources Click **Search** in the sidebar, or press **Command + K** on a Mac or **Ctrl + K** on Windows. You can search your chats, meetings, Agents, Workflows, projects, Skills, files, and Cassidy help articles from one place. Use the tabs at the top when you want to narrow the results. Search only shows resources you can access. Draft Agents, Workflows, and Skills do not appear because they are not ready to use. Choosing a result takes you to the most useful next step. Agents start a chat, Workflows open in the Run view, Skills are added to a new chat, projects filter the **Chats** tab, and files open in a preview. You can also search for destinations such as **Account Settings → Notifications**. Cassidy search showing matching Agents, Meetings, navigation, and organization settings ## Select an Agent Every chat uses an Agent. You can switch between custom Agents, foundational models, and Cassidy's pre-built Agents at any time. Click the Agent dropdown at the top of the chat or in the text box to see your options. Agent dropdown showing custom, default, and pre-built Agents You'll see three categories: * **Custom Agents** — built by your team, trained on your [Knowledge Base](/knowledge-base/overview) with tailored instructions * **Default Agents** — foundational models like GPT, Claude, and Gemini without your business context * **Pre-built Agents** — Cassidy's ready-made options like the Data Analyst and Cassidy Help Agent Default Agents don't have access to your company's Knowledge Base or custom instructions. Claude 4.6 Sonnet selected as a default Agent with a banner noting it has no company context Hover over a published Agent, open its **...** menu, and select **Pin to sidebar**. Pinned Agents appear in the **Pinned** section of your sidebar and near the top of the Agent list. Draft Agents must be published before you can pin them. Agent actions menu showing Pin to sidebar and Pin for organization Need a different Agent? Click the dropdown again and select a new one. The chat continues with the new Agent — no need to start over. When chatting with a Q\&A Agent, responses include source citations that link back to your Knowledge Base so you can verify the information. Chat response with Knowledge Base citations highlighted ## Personalize your chat Tell Cassidy your name, role, and response preferences so every chat is tailored to you, no matter which Agent you use. Open **Customize** → **Personalization** from the sidebar or from the top-right corner of a new chat. See [Personalize your chats](/agents/personalize-your-chats) for the full walkthrough and where your preferences apply. For organization-wide AI behavior rules that apply to every Agent and Workflow, see [Global instructions](/settings/global-instructions). ## Reference your Knowledge Base You can pull specific items from your [Knowledge Base](/knowledge-base/overview) directly into a chat to ask targeted questions. In the chat text box, type **#** to open a search dropdown for your Knowledge Base. Knowledge Base reference dropdown showing folders like Carrier Data, Call Intelligence, and Meeting Notes Start typing keywords to filter results. Click the item you want to reference — it appears as a tag in your message. New Employee Onboarding Guide added as a Knowledge Base reference tag in the chat text box Send your message with the referenced item. The Agent uses that specific document as context for its response. For example: * "Can you summarize the main points of this employee handbook?" * "How many vacation days am I entitled to according to this policy?" * "What is the process for requesting time off?" The **#** reference is useful when you want to point the Agent at a specific document for a single question. To have an Agent always search certain Knowledge Base items, add them to the Agent's configuration — see [Build and configure an Agent](/agents/build-and-configure) for details. The **#** picker can include recorded [meetings](/meetings/getting-started), not only Knowledge Base items. To search **across** your meeting library in chat (with citations back to recordings), add the [Meetings Connector](/agents/connectors/meetings) to the Agent — see [Chat with your meetings](/meetings/knowledge-base). ## Upload files and media Share files, images, videos, and audio directly in chat to ask questions about their content. These uploads are temporary — they are not saved to your Knowledge Base. In the bottom-left corner of the text box, click **+** to open attachment options. Attachment menu showing file and image upload options Select **Attach a File** or **Attach an Image** from the menu. You can also drag and drop files directly into the chat window. Once uploaded, the Agent can analyze the content. Try prompts like: * "Summarize the key findings in this report" * "What text is visible in this screenshot?" * "Extract the data from this chart" Agent response analyzing an uploaded file Uploaded files are temporary and tied to the chat session. If you need to store a file permanently, [upload it to your Knowledge Base](/knowledge-base/setup) first, then reference it with **#**. ## Use the tools picker Click **Tools** at the bottom of the text box to see everything available in the current chat. From here you can turn [capabilities](/agents/capabilities/overview) such as [Web Search](/agents/capabilities/web-search), [Image Generation](/agents/capabilities/image-generation), [Artifacts](/agents/capabilities/artifacts), and [Browser Use](/agents/capabilities/browser-use) on or off for the chat. Tools menu in chat showing capabilities, personal Connectors, and Connectors enabled on the Agent The menu also lists your [Connectors](/agents/connectors/overview). Your own Connectors follow your account settings rather than per-chat toggles. Select **Add connector** to browse apps or **Manage connectors** to reconnect, change action permissions, or turn a Connector off. Connectors the Agent's builder added appear under **Enabled on Agent**. A warning icon means you need to reconnect. [Code Execution & File Creation](/agents/advanced/code-execution-file-creation) is configured on the Agent itself. New custom Agents have it enabled by default. If it is missing, edit the Agent and enable **Code Execution & File Creation** under **Customize** > **Advanced Settings**. ## Use voice mode Voice mode lets you have a spoken conversation with your Agent instead of typing. Click the **microphone** icon in the text box to start speaking. The Agent transcribes your speech, processes it, and responds — both in text and, optionally, with audio playback. Dictate button and microphone icon in the chat text box ## Use the writing editor The writing editor is a side-by-side panel where you can draft and refine content while chatting with an Agent. Click **Open editor** in the top-right corner of the chat interface. Open editor button in the chat interface Type directly in the rich text editor while chatting with the Agent. This is useful for researching ideas, drafting content, or getting real-time writing assistance. Writing editor open alongside a chat conversation When the Agent generates something you want to keep, click **Add to Editor** on the message. The content is automatically added to your document. Add to Editor button on an Agent response Click **File** then **Save to Knowledge Base** to store your document permanently. Choose a name and folder location, then click **Save**. Save to Knowledge Base option in the writing editor file menu Save dialog with document name and Knowledge Base location fields You can also export to Microsoft Word or PDF format. Once saved, changes sync automatically between the writing editor and the Knowledge Base document. The writing editor is tied to each individual chat. Save your work to the Knowledge Base before closing if you want to keep it. ## Run a Workflow in chat You can execute [Workflows](/workflows/overview) directly within a chat conversation to automate tasks without leaving the interface. In the text box, click the **Workflows** button to see available Workflows. Workflows menu showing a list of Workflows including Sales RFP, Marketing Blog Post, and Generate In-Depth reports Choose the Workflow you want to run from the list. A form replaces the text box with input fields for the Workflow. Fill in the required information. Generate In-Depth Company Report Workflow form with Company Name and Company Domain fields Click **Generate** to run the Workflow. Results appear directly in the chat. Workflow results displayed within a chat conversation After the Workflow runs, you can ask follow-up questions, refine inputs, or explore the results further in the same chat. ## Use a Skill [Skills](/skills/overview) give Agents reusable procedures, files, and tools for specialized tasks. Installed Skills are available across your chats, while Agent-attached Skills are available whenever you use that Agent. Agents choose relevant Skills automatically based on each Skill's name and description. To select one yourself: Type **/** in the chat box. Choose a published Skill under **Current Agent's Skills** or **My Skills**. Chat slash menu showing a Skill attached to the current Agent and personally installed Skills Continue writing your request and send the message. The Agent reads the selected Skill before responding. See [Use Skills in chat and Workflows](/skills/using-skills) to install Skills and understand automatic selection. ## Use the prompt library The prompt library lets you create reusable prompt templates so you can quickly apply consistent instructions across chats. ### Manage your prompts In the chat text box, type **/** and click **Manage prompt library** from the menu. Slash command menu showing the Manage prompt library option Click **+ New prompt**. Describe what you want, and Cassidy generates a refined prompt for you. Or click **Create prompt manually (advanced)** to write it yourself. New prompt creation interface in the prompt library Prompt description field where Cassidy auto-generates a prompt When writing prompts manually, you can: * Use **\[brackets]** for placeholders that change each time (e.g., \[professional] or \[witty] for tone) * Type **#** to reference [Knowledge Base](/knowledge-base/overview) items * Add example outputs so the Agent matches your preferred style Prompt editor showing placeholders, Knowledge Base references, and example outputs Click **Save** to store it. You can then click **Use prompt** to apply it immediately. Saved prompt with Use prompt and Edit buttons Prompts created in the library are visible to everyone in your organization. ### Apply a prompt in chat The menu shows Cassidy's default prompts (like **Improve writing** and **Summarize**) and your custom prompts. Prompt menu showing default and custom prompts Click a custom prompt to insert it. Replace any placeholders with your actual values — these edits do not change the saved template. Custom prompt inserted into the chat with placeholders highlighted Send the message. The Agent generates a response using your prompt template. Agent response generated from a custom prompt template For default prompts like **Improve writing** or **Summarize**, a quick form appears where you paste your text and click **Generate**. ## Analyze data Upload spreadsheets or data files and let the Agent create charts, run calculations, and extract insights. Choose the **Data Analyst** default Agent, or use a custom Agent. New custom Agents have [Code Execution & File Creation](/agents/advanced/code-execution-file-creation) enabled by default. Data Analyst Agent selected in the Agent dropdown Click **+** and attach a CSV or Excel file, or drag and drop it into the chat. CSV file being uploaded to a chat for data analysis Describe what you need: * "Create a bar chart showing sales by region" * "What are the key trends in customer behavior?" * "What was the total revenue for Q1?" Data analysis chart generated from an uploaded spreadsheet Click **Analyzed sources** in the results, then click the code icon (``) next to any step to see the Python code the Agent used to process your data. Analyzed sources dropdown showing processing steps Python code modal showing the data analysis logic * **Use CSV or Excel format** — these are the only supported file types for data analysis * **Organize data in rows and columns** — each row is a record, each column is a variable * **Include descriptive column headers** in the first row — avoid blank rows above the headers * **Keep data consistent** — no empty rows between entries, no multiple tables in one file, avoid multiple worksheets Well-formatted spreadsheet with clear headers and consistent data Code Execution & File Creation can also: * **Manipulate branded templates** — fill out forms, convert reports to presentations, edit Word documents and PDFs * **Create synthetic data** — generate sample datasets for testing or demonstrations For more on generating files, see [Create files in Cassidy](/guides/create-files). ## Edit and regenerate messages You can modify a sent message and have the Agent generate a new response. Move your cursor over the message you want to change. An edit icon appears on the right. Edit pencil icon appearing on hover over a chat message Click the edit icon, modify your text, and press **Enter**. The Agent generates a new response based on your updated message. Chat message in edit mode with modified text Click the left and right arrows at the top of the Agent's response to cycle through all generated versions. Response version navigation arrows on an Agent message You cannot edit Agent messages directly, but you can click **Regenerate** to produce a new response with the same prompt. ## Branch a conversation Branching creates a copy of a conversation up to a specific message, so you can explore a different direction without losing the original thread. Open a chat and scroll to the message you want to branch from. Click the **...** menu below the message and select **Branch in new chat**. Branch in new chat option in the message menu A new chat opens in a separate tab with the full conversation history up to that message. The original chat remains unchanged. The new chat is labeled "Branched from \[Chat Title]." Branched chat showing the conversation history and branch label Continuing a branched conversation in a new direction ## Share and organize chats Chats use the same sharing model as [Agents](/agents/sharing-and-management) and [Workflows](/workflows/sharing-and-deployment) — you can share with specific teammates, [groups](/settings/roles-and-groups), or your whole organization, and set each person's access to **View** (read-only) or **Edit** (can send messages). ### Share a chat Open the **...** menu on any chat and select **Share**, or click the **Share** button in the chat header. Choose who can access it and set their permission level. Sharing a chat does not notify the recipient — you'll need to send them the link directly. Share modal for a chat showing access level options and View or Edit permission toggle ### Organize chats with projects Projects keep related chats together. They are useful for work such as a customer account, hiring process, or quarterly planning where several conversations should share the same access. Go to Home and select the **Projects** tab. This page includes projects you own and projects shared with you. Click **New project**, enter a name, and choose who can access it. New projects start as restricted unless you choose a broader access level. Open a chat's **...** menu and select **Move to project**. If Projects are visible in your sidebar, you can also drag chats into and out of a project. Select a project from the **Projects** tab. Cassidy returns to the **Chats** tab and adds the project as a filter. Projects tab showing project search, filters, chat counts, and the New project button Chats inside a project use the project's sharing settings and cannot be shared separately. Change access from the project's **...** menu. When you move a shared chat into or out of a project, Cassidy shows how its access will change before completing the move. The Projects section appears in the sidebar automatically once you create, open, or are directly shared on a project. To show or hide it yourself, open the **...** menu beside **Recents**, choose **Customize sidebar**, and change **Show Projects section**. From the Projects menu, choose **My projects**, **My projects and shared with me**, or **All projects I can access**. Projects can be sorted by recent activity or name. Chats that teammates share with you appear in **Recents** once you open them. To see them right away, open the **...** menu beside **Recents**, choose **Chats shared with me**, then select **Always show**. Pin a project when you want it in the main **Pinned** section instead of the Projects section. Keep these things in mind when sharing chats: * Chats inside a project use the project's sharing settings and cannot be shared individually * New messages added to a shared chat are visible to everyone with access in real time * Projects shared with you appear in the sidebar when your **Show projects** setting includes them Deleting a project permanently deletes every chat inside it. This action cannot be undone. ## Use Cassidy in multiple languages While the Cassidy interface is in English, the AI models can understand and respond in virtually any language. Type your message in the language you prefer, and the Agent responds in the same language. Chat conversation in Spanish with the Agent responding in Spanish If the Agent doesn't consistently use your preferred language, add a specific instruction to the Agent's settings — for example, "Always respond in Spanish." Agent instruction field with a language preference set to Spanish For more on customizing Agent behavior, see [Build and configure an Agent](/agents/build-and-configure). ## Next steps Create a custom Agent with tailored instructions and Knowledge Base access. Compare GPT, Claude, and Gemini to pick the best model for each task. Write effective prompts for better, more consistent AI outputs. Generate documents, spreadsheets, and presentations through chat. # Choose the right AI model Source: https://docs.cassidyai.com/guides/choose-ai-model Pick the right AI model for each Agent and Workflow task using Cassidy's recommendations and thinking levels. Cassidy gives you access to all leading AI models and automatically recommends the best options for different scenarios. You can choose models per [Agent](/agents/overview), per chat, and per [Workflow](/workflows/overview) step - so you always use the right tool for the job. For most work, start with **Recommended Models**. Browse the full list when you want a specific model, thinking level, or provider. ## Where you choose models Choose any foundational model as the base for your custom Agents. You can also use default Agents that run on foundational models without your business context. Model selector in the Agent configuration panel Switch between models and Agents at any time during a conversation. This gives you flexibility to use the best model for each part of your chat. Model selector dropdown in the Chat interface Each [Workflow](/workflows/overview) action can use a different model. The **Generate Text** action lets you select the AI model that best fits each automation step, so routine steps can stay cheap while harder steps use a more capable model. Model selector in a Workflow Generate Text action ## Start with recommended models Cassidy's **Recommended Models** section is continuously updated as new models are released and evaluated. The platform surfaces the best-performing, most cost-effective models for your needs, and cost reductions from providers are automatically passed on to you. Recommended Models section showing Default, Fastest, Best Writer, and Smartest | Recommended pick | Best for | | - | - | | **Default** | Everyday Agent chats and Workflow steps — the best starting point for most work | | **Fastest** | High-volume, routine tasks like classification, extraction, formatting, and summaries | | **Best Writer** | Emails, marketing copy, and other writing that should sound natural | | **Smartest** | Complex work, [connectors](/agents/connectors/overview), [artifacts](/agents/capabilities/artifacts), and anything where accuracy matters most | You do not need to track AI model releases yourself - Cassidy keeps recommendations current as new models launch. If you are not sure which model to use, choose **Default**. ## Model providers and strengths Each provider has distinct strengths. Use this as a starting point, then experiment to find what works best for your specific tasks. Best for general Agent applications, everyday tasks, and Q\&A. Reliable for information retrieval and a wide range of business queries. Excels at automation and general knowledge tasks. Preferred for creative writing, sales, and marketing content that needs a human-like touch. Ideal for drafting emails, marketing copy, and communication-heavy tasks that require natural-sounding language. Strong at combining information from many sources and working with documents, images, and other files. A good fit for [deep research](/agents/deep-research) and analysis that pulls from a lot of material at once. ## Which model and how much thinking When you look past Recommended, two settings matter: **which model** you pick, and **how much thinking** it does. Not all models within a provider are the same. Some are faster and cheaper; others are more capable and cost more. | Category | Best for | Speed | Cost | Examples | Notes | | - | - | - | - | - | - | | **Mini** | High-volume, routine tasks like customer support triage, formatting, and summaries | Fast | Low | GPT-5.6 Luna, Claude 4.5 Haiku | Latest mini models often match previous-generation full models in quality | | **Standard** | Everyday tasks - Q\&A, creative writing, moderate analysis, and automation | Moderate | Moderate | GPT-5.6 Terra, Claude 5 Sonnet | The best starting point for most use cases | | **High-powered** | Complex multi-step reasoning, legal analysis, financial workflows, STEM | Slow | High | GPT-5.6 Sol, Claude 5.5 Opus | More capable and more expensive — use when the task is worth the extra cost | ### Thinking level Thinking level controls how long the model works before it answers. | Thinking level | When to use it | | - | - | | **Instant** | Fast replies when speed matters more than extra deliberation | | **Thinking** | Better accuracy for most Agent work | | **High Thinking** | The hardest problems — slower, and it uses more credits | Thinking variants use the same credit rate as Instant for that model. They cost more per task because they generate extra thinking tokens and run longer before answering. You can use this analogy to understand the model and thinking level choices: model power is how smart the brain is, and thinking level is how long that brain gets to work. ## Understanding credit consumption Credit usage scales with prompt size and response length. Longer prompts, more [Knowledge Base](/knowledge-base/overview) context, and more thinking all use proportionally more credits. | Category | Relative cost | Examples | | - | - | - | | **Mini** | \~0.3x | GPT-5.6 Luna, Claude 4.5 Haiku | | **Standard** | 1x | GPT-5.6 Terra, Claude 5 Sonnet | | **High-powered** | \~2–3x | GPT-5.6 Sol, Claude 5.5 Opus | Start with standard general-purpose models (or the **Default** recommended pick) since they offer excellent performance at the best value. Switch to **High-powered** or **High Thinking** models only when you need their specialized capabilities or the task needs complex reasoning. For more on managing credits, see [Manage credits](/settings/manage-credits). ## Best practices * Start with **Default** unless you already know you need Fastest, Best Writer, or Smartest. * Use **Mini** models for summarization, formatting, and other high-volume Workflow steps. * Turn thinking up (**Thinking** or **High Thinking**) when accuracy matters more than speed. * Use **High-powered** models for complex analysis, planning, or Agents that rely on tools. * In a single [Workflow](/workflows/overview), mix models: Mini for routine steps, Standard for generating content, High-powered or High Thinking only where the extra cost pays off. ### Consider your specific use case | Use case | Typical provider | | - | - | | Quick answers, document retrieval, general automation | **GPT** | | Natural-sounding writing, emails, creative content | **Claude** | | Deep research, combining many sources, working with documents and files | **Gemini** | ## Next steps Create a custom Agent and select the right model for its role. Write effective prompts that get the most out of any model. # Create files in Cassidy Source: https://docs.cassidyai.com/guides/create-files Generate documents, spreadsheets, and presentations through Agents, Workflows, and Chat. Cassidy gives you three ways to create downloadable files — from quick one-off documents in [Chat](/guides/chatting-with-an-agent) to repeatable, branded deliverables in [Workflows](/workflows/overview). Choose the approach that fits your need. ## Choose your approach **Best for**: One-off files you want to iterate on in conversation — sales follow-ups, competitor one-pagers, summaries, draft decks. A PDF generated through an Agent chat conversation **Best for**: Consistent formatting every time — brand-safe decks, proposals, client reports, onboarding packets. You design the template once, and the Workflow fills it with live data on every run. A branded PowerPoint template being filled by a Workflow **Best for**: Output that varies too much for a strict template — charts, dynamic reports, and files that need AI-generated formatting. Also the approach to use when building reusable file-generation Workflows for [Call Workflow](/agents/call-workflow). Creating a presentation through Chat? Use [Cassidy Slides](/slides/create-and-export-presentations) to build and refine the deck conversationally, present from Cassidy, and export to PowerPoint, Google Slides, or PDF. Use the Workflow template approach when the same fixed layout needs to be populated repeatedly with structured data. ## Create files in Chat The Chat interface lets you generate downloadable files — PDFs, Word documents, spreadsheets, and more — directly in a conversation with an [Agent](/agents/overview). Describe what you need, and the Agent automatically uses [Code Execution & File Creation](/agents/advanced/code-execution-file-creation) to build and return a polished file. For presentations, follow the dedicated [Cassidy Slides guide](/slides/create-and-export-presentations). The walkthrough below uses a competitor one-pager as an example, but the same flow works for any file type — reports, proposals, decks, spreadsheets, and more. Click **+ New Chat** and choose your Agent from the dropdown: * **Default Agents** (like Data Analyst) handle general file and data tasks but lack your business context * **Custom Agents** configured with your [Knowledge Base](/knowledge-base/overview) and domain-specific instructions produce outputs tailored to your organization. New custom Agents have [Code Execution & File Creation](/agents/advanced/code-execution-file-creation) enabled by default. Agent dropdown with the Data Analyst default Agent selected For custom Agents, attach reference files (like a branded template or battlecard) directly in the Agent's instructions so it uses them automatically whenever it creates a file. Custom Agent configuration with Knowledge Base and reference files attached If Data Analysis is missing, edit the Agent and enable **Code Execution & File Creation** under **Customize** > **Advanced Settings**. Agent Advanced Settings showing Code Execution and File Creation enabled Click the **+** button and select **Attach a File** or **Attach an Image** to upload supporting materials — call notes, spreadsheets, competitor docs, etc. This is helpful when using a default Agent that does not have reference files in its instructions. Attachment menu with file and image upload options Type your request with as much detail as possible — format, audience, length, sections, and tone. For example: "I just wrapped up a prospect call and they mentioned MyCase as a competitor. Create a one-pager PDF I can send them about why we are better. Use our competitor battlecard template." Chat message requesting a competitor one-pager PDF The Agent automatically decides to use Code Execution & File Creation to produce the file — you do not need to tell it which setting to use. The Agent gathers relevant context, then builds the file. Progress indicators appear as it works. Loading indicator showing the Agent generating a file Preview indicator showing a PDF being rendered The finished file appears as a downloadable card at the bottom of the Agent's response. Click the download icon to save it. Downloadable file card with download icon Generated PDF one-pager preview Continue the conversation to refine the output: * "Keep it to 1 page, skimmable, and non-combative" * "Add a 3-row comparison table: Feature / Competitor / Us" * "Write a short email to attach this one-pager to" ## Create files in Workflows (template approach) For deliverables that need consistent formatting every time, use a [Workflow](/workflows/overview) with a template-based file creation action. Design the template once with placeholders, and the Workflow fills it with live data on every run. ### File creation actions Cassidy offers several template-based actions you can add as Workflow steps: | Action | Description | | - | - | | **Create Microsoft PowerPoint Presentation from Template** | Fill a branded PPTX template with dynamic content, loops, and conditionals | | **Create Microsoft Word Document from Template** | Populate a DOCX template with variables from previous Workflow steps | | **Create Microsoft Excel Spreadsheet** | Generate formatted XLSX files with structured data | ### Build a template-based file Workflow This walkthrough uses a Quarterly Business Review (QBR) deck as an example, but the same pattern applies to proposals, onboarding packets, client reports, and more. Create a [Workflow](/workflows/building) with a Manual Trigger (or a scheduled, webhook, or [email](/reference/triggers/email) trigger). Add input fields for the information your template needs — client name, date range, file uploads, etc. Workflow trigger configuration with input fields for client name and date range Add **Generate Text** or integration actions to look up account information, summarize objectives, analyze product usage, or pull relevant data. Each step returns structured data that subsequent steps can reference. Workflow Generate Text action gathering content from integrations Use **Generate Text** actions with structured output fields to produce clean variables that map directly to your template placeholders — including arrays for loops and booleans for conditionals. Structured output fields producing variables for a template Add the appropriate file creation action (e.g., **Create Microsoft PowerPoint Presentation from Template**). Upload your branded template, set an output name, and map your variables into the template fields. PowerPoint and Word templates support: * **Text placeholders**: `{variableName}` for dynamic content * **Conditionals**: `{#if:condition}` ... `{/if:condition}` to show or hide sections * **Loops**: `{#loop:arrayName}` ... `{/loop:arrayName}` to repeat content for lists * **Slide loops / slide conditionals**: `{%loop:arrayName}` and `{%if:conditionName}` to repeat or conditionally show entire slides Template action with uploaded PPTX template and variable mappings Execute the Workflow. The generated file appears in the results panel. You can also pass it to a subsequent action — like **Send Email** — to deliver it automatically. Workflow results panel with generated PowerPoint file Generated QBR deck preview showing branded template with filled data ## Create files in Workflows (Code Execution & File Creation) When the output varies too much for a fixed template — or you need the AI to generate charts, format documents, or manipulate files programmatically — enable **Code Execution & File Creation** on a Generate Text action. For a detailed end-to-end walkthrough, see [Analyze data in Workflows](/workflows/advanced/data-analysis). Write a prompt describing the file you need. For example: "Using the analysis results and chart from the previous step, create a professional PowerPoint presentation with key findings and an executive summary." Generate Text action with a prompt describing the desired file Expand **Code Execution & File Creation** and turn on the setting. This allows the AI to write and execute code to create, edit, or manipulate files. Screenshot needed: Generate Text action settings with Code Execution & File Creation enabled. Pass in files from the trigger (like an uploaded spreadsheet) or reference outputs from earlier steps so the AI has the data it needs. When Code Execution & File Creation is enabled, the action produces a **Generated Files** variable containing any files created during processing. Reference this variable in subsequent steps or download the files from the results panel. Generated Files variable available for use in subsequent Workflow steps Use one Code Execution & File Creation step to analyze data and produce insights, then a second step to compile those insights into a formatted document or presentation. If you just need a quick, ad-hoc file and are not building a multi-step automation, use the Chat + Agent approach instead. ## Advanced: attach a file-creation Workflow to Agents You can build a Workflow whose job is to generate a specific type of file, then attach it to one or more [Agents](/agents/overview) using [Call Workflow](/agents/call-workflow). When a user asks the Agent for that deliverable, the Agent automatically runs the Workflow, collects required inputs through conversation, and returns the finished file. This combines the convenience of Chat with the power of Workflows. Call Workflow configuration attaching a file-generation Workflow to an Agent For setup instructions, see [Call Workflow](/agents/call-workflow). ## Next steps Full walkthrough of using Code Execution & File Creation in Workflows. Learn how Agents use code execution and file creation to analyze data. Create Workflows with template actions and structured outputs. Attach Workflows to Agents so users can generate files through chat. Master the Chat interface for quick file generation and more. # Migrate to custom roles Source: https://docs.cassidyai.com/guides/migrate-to-custom-roles Move from legacy group permissions to custom roles while preserving team access and cleaning up generated roles afterward. Some Cassidy workspaces used groups for both visibility and permissions. Cassidy now separates those jobs: [roles](/settings/roles-and-groups) control what people can do, and groups control which shared resources people can see. Use this guide if your workspace shows a migration prompt for custom roles in Organization Settings. New workspaces already use the current roles and groups model. You need admin access to manage roles and run the migration. ## What changes Before migration, groups controlled both visibility and permissions. If someone belonged to multiple groups, their permissions were additive. For example, if one group allowed editing Workflows and another group allowed inviting members, the person could do both. After migration, roles control privileges and groups control visibility. A person can still have multiple roles, and their effective privileges are the union of those roles. Group membership stays focused on which Agents, Workflows, Knowledge Base collections, chats, and meetings the person can access. ## What Cassidy creates Migration is designed to preserve existing access. Cassidy generates a migration plan before changing your workspace. Legacy admins keep the managed admin role they need to manage the workspace. Groups that previously granted feature permissions become custom roles, such as **Migrated: Sales Team**. Existing group memberships stay in place for visibility, so shared resources stay visible to the same teams. Existing SAML group mappings are backfilled into role mappings where needed, so automatic role assignment keeps working after migration. ## Migrate your workspace Go to **Organization Settings** and click **Roles**. If your workspace still uses legacy group permissions, click the migration prompt. Custom roles migration banner on the Roles page with the migration action highlighted Review the managed role assignments and custom roles Cassidy will create. The plan explains which groups map to each generated custom role. Custom roles migration plan showing generated managed role assignments and custom roles Click **Enable Custom Roles**. Cassidy updates your workspace to the custom roles system. Open each generated custom role. Rename roles to match how your team talks about access, such as **Workflow Editors** or **Knowledge Base Managers**. Adjust generated role privileges if the migrated role is broader than you want going forward. Keep the generated role in place until everyone who needs those privileges has another role that grants them. Your workspace now uses roles for privileges and groups for visibility. Do not delete generated custom roles until you have confirmed that everyone who needs those privileges has another role that grants them. ## Next steps Learn the current roles and groups model. Map your identity provider attributes to Cassidy roles and groups. # Write effective prompts Source: https://docs.cassidyai.com/guides/prompt-engineering Write effective prompts for Agents and Workflows to get consistent, high-quality AI outputs. Prompt engineering is the practice of designing AI instructions that are clear, specific, and optimized for the task at hand. Unlike casual AI interactions, business automation requires prompts that are robust, modular, and capable of handling dynamic information while maintaining consistent quality. ## Where to use prompts in Cassidy Prompts serve different purposes depending on where you use them: System instructions that define your [Agent's](/agents/overview) role, personality, and behavior across all interactions. Think of these as the Agent's permanent memory. **Example**: A customer support Agent configured with tone guidelines, response format, and escalation procedures. Agent configuration panel showing system instructions Learn more in [Build and configure an Agent](/agents/build-and-configure). Messages you send in [Chat](/guides/chatting-with-an-agent) that work together with your Agent's instructions. The Agent already knows how to behave from its system instructions — your message provides the specific context. **Example**: "Here's the customer ticket: \[ticket description]. The customer has been with us for 2 years and this is their first technical issue." Chat message providing specific context to an Agent Prompts embedded in [Workflow](/workflows/overview) actions like **Generate Text** that process dynamic data and reference variables from previous steps. **Example**: A prompt that takes a form submission from a trigger and generates a categorized response using data from earlier Workflow steps. Workflow Generate Text action with a prompt referencing variables ## Core principles Every effective prompt follows these four principles: 1. **Clarity and specificity** — every instruction should be unambiguous and actionable. Avoid vague language that could produce inconsistent results. 2. **Structured organization** — well-organized prompts follow a logical flow that guides the AI step by step. 3. **Dynamic context support** — business prompts must handle changing information while maintaining quality and format consistency. 4. **Robust instruction following** — include explicit formatting requirements and constraints for reliable automation. ## The seven-section prompt structure Every effective business prompt should follow this structure. You do not need all seven sections for every prompt — use what is relevant to the task. ### 1. Role and objective Define the AI's role and primary goal. This sets context and expectations. ``` # Role and Objective You are a customer support specialist at a SaaS company. Your objective is to analyze customer feedback and categorize issues by priority level and department for efficient routing. ``` ### 2. Instructions Provide detailed, step-by-step guidance for completing the task. ``` # Instructions - Analyze the customer feedback provided in the context section - Categorize each issue using the following priority levels: a. Critical: System outages, security breaches, data loss b. High: Feature failures affecting multiple users c. Medium: Minor bugs or usability issues d. Low: Feature requests or general inquiries - Assign each issue to the appropriate department: Engineering, Product, or Support ``` ### 3. Reasoning steps Break down the thought process the AI should follow. This ensures consistent logic across different inputs. ``` # Reasoning Steps 1. Read through all customer feedback carefully 2. Identify the core issue or request in each piece of feedback 3. Assess the impact level based on user count and business criticality 4. Determine which team is best equipped to address the issue 5. Format the results according to the specified output structure ``` ### 4. Output format Specify exactly how the response should be structured. ``` # Output Format - Return a numbered list of issues with the following format for each: **Issue [number]**: [Brief description] - Priority: [Critical/High/Medium/Low] - Department: [Engineering/Product/Support] - Details: [Additional context if needed] - Do not include any introductory or closing text - Use markdown formatting as specified above ``` ### 5. Examples Provide complete examples that demonstrate expected input-output relationships. Examples enable few-shot learning and clarify ambiguous instructions. ``` # Examples **Issue 1**: Login system completely down for all users - Priority: Critical - Department: Engineering - Details: Affects entire user base, immediate attention required **Issue 2**: Export feature missing from reports dashboard - Priority: Medium - Department: Product - Details: Workaround available, but impacts user workflow efficiency ``` ### 6. Context Include all information the prompt needs to reference. This section changes depending on the situation. When using **Agent system instructions**, you often provide context directly in your chat message instead of a formal context section. When using **Workflow prompts**, you reference [variables](/workflows/building) from previous steps or triggers. ``` # Context Customer feedback: {feedback_data} Company priority matrix: {priority_guidelines} Department responsibilities: {dept_responsibilities} ``` In [Workflows](/workflows/overview), reference variables from previous steps. In [Chat](/guides/chatting-with-an-agent), reference [Knowledge Base](/knowledge-base/overview) items with **#**. ### 7. Final instructions End with explicit step-by-step thinking instructions and formatting reminders. ``` # Final instructions and prompt to think step by step Think step by step: First, read through all feedback items. Then, assess each issue's impact and urgency. Next, match issues to appropriate departments based on their expertise. Finally, format your response exactly as specified above. Only return the numbered list of categorized issues, nothing else. ``` ## Formatting best practices Different models have preferences for structure syntax: * **GPT (OpenAI)** works well with markdown formatting (headers, bullet points, bold) * **Claude (Anthropic)** responds well to XML tags like `` and `` Regardless of syntax, the seven-section structure is the most important element. Pick a formatting approach and use it consistently throughout your entire prompt. For model-specific guidance, see [Choose the right AI model](/guides/choose-ai-model). ## Sample prompts ``` # Role and Objective You are a customer service representative at a SaaS company. Your objective is to generate professional, helpful email responses to customer inquiries. # Instructions - Read the customer inquiry and identify the main issue - Determine response type: technical support, billing, feature request, or general inquiry - Use a professional, empathetic tone - Include troubleshooting steps or next actions when applicable # Reasoning Steps 1. Analyze the inquiry to understand the specific problem 2. Identify the urgency level and emotional tone 3. Select the most appropriate response approach 4. Craft a response that addresses the concern 5. Include clear next steps # Output Format - Subject line addressing the customer's inquiry - Professional email body with greeting and closing - Clear, actionable next steps - Keep responses concise but comprehensive # Examples **Customer Inquiry**: "I can't log into my account and I have an important presentation tomorrow." **Response**: Subject: Quick Resolution for Your Login Issue Hello [Customer Name], I understand how frustrating this must be, especially with your presentation tomorrow. Let's get you back in quickly. Try these steps: 1. Clear your browser cache and cookies 2. Try an incognito/private browser window 3. Verify you're using the correct email address If these don't work, I can reset your password immediately. Best regards, [Your Name] # Context Customer inquiry: {customer_message} Account details: {account_info} Company policies: {policy_guidelines} # Final instructions Think step by step: First, understand the customer's inquiry and emotional state. Then, determine the response type and tone. Craft a helpful response. Only return the email, nothing else. ``` ``` # Role and Objective You are a sales operations analyst. Your objective is to analyze incoming leads and score them based on qualification criteria. # Instructions - Evaluate each lead against qualification criteria - Assign a lead score from 1-100 based on the scoring matrix - Categorize leads as Hot (80-100), Warm (60-79), or Cold (<60) - Identify the primary pain point or business need - Recommend the most appropriate next action # Reasoning Steps 1. Review all available lead information 2. Apply the scoring matrix 3. Assess timeline and budget indicators 4. Determine decision-making authority level 5. Recommend prioritization and next steps # Output Format **Lead Score**: [Number]/100 **Category**: [Hot/Warm/Cold] **Primary Need**: [Brief description] **Key Insights**: - [Insight 1] - [Insight 2] - [Insight 3] **Recommended Action**: [Specific next step] **Priority Level**: [High/Medium/Low] # Context Lead information: {lead_data} Scoring matrix: {scoring_criteria} Sales team capacity: {team_availability} # Final instructions Think step by step: Review all lead information, apply the scoring matrix, analyze buying signals, and recommend specific actions. Only return the formatted analysis, nothing else. ``` ``` # Role and Objective You are a content marketing analyst. Your objective is to analyze content performance data and create actionable insights. # Instructions - Review performance metrics for all content in the time period - Identify top performers by engagement, traffic, and conversions - Analyze trends and patterns - Provide specific optimization recommendations - Highlight concerning performance drops # Output Format ## Executive Summary [2-3 sentence overview] ## Top Performers 1. **[Title]** - [Key metric] 2. **[Title]** - [Key metric] 3. **[Title]** - [Key metric] ## Key Insights - [Content type/topic performance] - [Audience engagement patterns] - [Conversion performance] ## Recommendations 1. **[Action]**: [Recommendation with rationale] 2. **[Action]**: [Recommendation with rationale] 3. **[Action]**: [Recommendation with rationale] ## Areas of Concern - [Issues requiring attention] # Context Performance data: {analytics_data} Content inventory: {content_list} Benchmark metrics: {performance_benchmarks} # Final instructions Think step by step: Analyze all metrics, compare against benchmarks, determine actionable insights, and format the report. Only return the formatted report, nothing else. ``` ## The power of examples Examples are the most impactful section of any prompt. They serve as training data for the AI, demonstrating exactly what you expect. Effective examples should: * Include **complete input-output pairs** that show the full transformation from raw input to desired output * Demonstrate how to **handle different scenarios** — include edge cases if they matter * **Match your specified output format** exactly — the AI mirrors what it sees When outputs are not quite right, adding one or two well-crafted examples is often more effective than rewriting your instructions. ## Advanced techniques Always include explicit instructions for the AI to "think step by step" in your final instructions section. This improves accuracy for complex tasks by forcing the model to break down its reasoning process before producing a final answer. Use precise language to control output boundaries: * "Only return the \[output type], nothing else" * "Do not include introductory or closing text" * "Keep the response under 200 words" * "Use only the information provided in the context section" Constraints prevent the AI from adding unnecessary preamble, disclaimers, or off-topic content. For production Workflow prompts, include instructions for handling edge cases: * "If the input is empty, return: 'No data provided'" * "If the information is ambiguous, state the ambiguity and provide your best interpretation" * "If the request falls outside your defined scope, explain what you can help with instead" This prevents Workflow failures and ensures graceful handling of unexpected inputs. Effective prompt engineering is iterative. Test your prompts with different inputs, review the outputs, and refine based on what you learn. Small adjustments often lead to big improvements. ## Next steps Put your prompts to use — including the prompt library for reusable templates. Apply your prompt engineering skills to Agent system instructions. Use prompts in Workflow actions with dynamic variables. # Getting started Source: https://docs.cassidyai.com/index Learn how to build AI-powered automations for your team with Agents, Workflows, and your company's Knowledge Base. Welcome to the Cassidy documentation. Get started by learning the platform basics or dive into a specific feature.