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Define how your agent presents itself and communicates with users through personality settings, Slack behavior configuration, and auto-respond options.

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Personality

By default, agents use a built-in communication style that produces direct, professional responses without filler or pleasantries. Setting a custom prompt overrides these defaults entirely.

Custom prompt

Provide a custom prompt to define your agent’s personality, tone, and communication style. This prompt guides how the agent interacts with users.
When you set a custom prompt, the Response length, Tone, and Emojis settings below are disabled. Your custom prompt must specify all personality characteristics including verbosity, tone, and emoji usage. The agent will not reference the standard settings.
Example prompts:IT Support Agent:

You are a helpful IT support agent. Be professional and technical but friendly. Keep responses concise and to the point. Use a business tone with minimal emojis. When explaining technical concepts, use clear language that non-technical users can understand. Always be patient and empathetic with frustrated users.

HR Agent:

You are a compassionate HR assistant. Use a warm, supportive tone with moderate emoji usage to create a welcoming atmosphere. Keep responses balanced in length, providing enough detail to be helpful while respecting people's time. Be empathetic and understanding, especially when handling sensitive topics like benefits, time off, or workplace concerns.

RevOps Agent:

You are a strategic Revenue Operations assistant. Communicate in a business-casual tone that's professional yet approachable. Use verbose responses when explaining complex processes or data, but stay concise for quick questions. Include minimal emojis to maintain professionalism. Focus on being clear, data-driven, and solution-oriented in your communication.

Focus on the agent’s character and manner of speaking. Avoid including instructions about tools or processes, which belong in .
Select the desired length of the agent’s responses: Concise, Balanced, or Verbose.
This setting is ignored if a custom prompt is configured.
Choose the tone of the agent’s communication: Business, Casual, or Humorous.
This setting is ignored if a custom prompt is configured.
Set whether the agent should use emojis in its responses and how often: None, Minimal, Moderate, or High.
This setting is ignored if a custom prompt is configured.

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Slack behavior

Configure how your agent responds in Slack channels and threads.

Channel messages

Define how the agent responds to messages in Slack channels:
  • Respond to all messages: The agent replies to every message in the channel
  • Respond to mentions only: The agent only replies when directly mentioned
  • Respond to requests only: The agent only replies to messages detected as requests for assistance
Define how the agent responds to messages in a Slack thread:
  • Respond to all messages: The agent replies to every message in the thread
  • Respond to mentions only: The agent only replies when directly mentioned
  • Smart (classify intent) V3+: The agent uses an AI classifier to determine whether a message is directed at it before responding. Side-conversations, acknowledgments, and human-to-human exchanges are skipped. When the agent has asked a question (for example, while collecting a form field) and the user replies with an @mention such as a manager’s name, the classifier treats the message as an answer to the agent rather than a side-conversation.
Default for V3 agents: Smart (classify intent).
Channel and threaded message settings do not apply to Slack direct messages (DMs) with the agent. Since a DM is a private 1:1 conversation, the agent always responds to every message in a DM, including replies in DM threads.
The agent reads files that users share in Slack as part of the conversation. When a user uploads a document with their message, the agent extracts the document’s text and uses it to answer questions, fill forms, or route the ticket.Supported file types:
  • PDF documents
  • Images (screenshots, photos)
  • Text and document files shared in Slack
How it works:
  • When the agent detects a file share, it briefly defers its response so Slack can finish processing the upload. This prevents the agent from replying before it can read the attachment.
  • The agent then extracts text from the file and treats its contents as additional context for the message.
  • Extracted document content is used the same way as the user’s typed message: for answering questions, prefilling form fields, and selecting rules.
Example use cases:
  • A user pastes a screenshot of an error and asks “what’s going on?” The agent reads the screenshot and references it in its answer.
  • A user attaches a vendor invoice or contract PDF when filing a request. The agent extracts key fields to prefill the form.
  • A user shares an exported log file. The agent summarizes the file before creating the ticket.
File contents are processed at message time and used as part of the agent’s conversation context. They are not automatically added to your knowledge base. To make a document permanently searchable by the agent, ingest it into a knowledge folder.

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Response elements

Configure UI elements that appear in the agent’s Slack responses. These settings control visual components displayed alongside AI answers when the response includes citations from your knowledge base.

Show source

Display the source link in agent responses. When enabled, users see links to the knowledge base articles or documents that the AI used to generate its answer.Default: EnabledThis helps users verify information and explore related documentation.
Display thumbs up and down feedback buttons below AI responses. When enabled, users can indicate whether the response was helpful.Default: EnabledFeedback data helps you identify knowledge gaps and improve your documentation.
Display a button that allows users to create a support ticket directly from the AI response. This is useful when the AI answer doesn’t fully resolve the user’s question and they need human assistance.Default: Disabled
The create ticket button only appears when the ticket has not already been published.

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Create ticket on negative feedback

Automatically create a support ticket when users react with thumbs down to an agent response. Enabled by default to ensure negative feedback receives timely follow-up.
This setting only appears when Show feedback buttons is enabled.

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Auto-respond

Enable automatic AI responses for tickets created from email and integration sources (Jira, Linear, GitHub). When enabled, the agent automatically responds to new tickets using its assigned knowledge bases.

Auto-respond to email

Enable automatic responses to tickets created from inbound emails. The agent analyzes the email content and provides a response based on its knowledge bases.
Enable automatic responses to tickets created from integrations such as Jira, Linear, and GitHub. The agent analyzes the ticket content and provides a response based on its knowledge bases.
Set a delay (0-300 seconds) before the agent responds. This allows time for additional context to be added to the ticket before the AI responds. Options include:
  • Immediate (0 seconds)
  • 5 seconds
  • 10 seconds
  • 30 seconds
  • 1 minute
  • 2 minutes
  • 5 minutes
Enable automatic ticket creation when all required form fields are pre-filled by the agent, without requiring user review.Default: EnabledWhen enabled (default), the agent bypasses the form review step and creates the ticket immediately if all required fields have been provided. When disabled, users are shown a pre-filled form to review and submit manually. If some required fields are missing, the form is still shown to the user with valid prefills so they can complete the remaining fields manually.Enable this setting when you want a faster, more streamlined experience and trust the agent to accurately fill in form fields based on the conversation context.
Auto-submit is disabled for private forms regardless of this setting. Private forms always display the form UI so users can enter sensitive information directly.
Prefilled values are validated before auto-submit. If the agent makes a mistake, it retries with corrected values instead of silently dropping the field.
If the agent cannot provide a definitive answer, the ticket will be tagged with ai-unresolved for human follow-up.

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Conversational form filling

Enable conversational form filling to let the agent collect form field values through natural conversation rather than presenting a form UI. The agent asks for each field one at a time, then presents the completed form for review once all required values are collected.

Enable conversational form filling

Toggle this setting on to switch forms from the standard form to conversational collection. The agent prompts users for each field individually in chat, then presents the completed form for review.Default: Disabled
Set the maximum number of fields a form can have to use conversational mode. Forms with more fields than this threshold will display the standard form instead.Default: 3 fieldsUse a lower threshold for complex forms where users benefit from seeing all fields at once. Increase the threshold for simple forms with few required fields.
The threshold is compared against the maximum number of fields a single user path can reveal, not the raw total. For forms with conditional (dependent) fields, only the longest visible branch counts. For example, take a Laptop Request form with 10 declared fields where any one user only ever sees 6 — top-level fields plus a single Mac or Windows branch. Ravenna treats it as a 6-field form for threshold purposes. This keeps branchy forms eligible for conversational mode even when the total field count is large.
If a form exceeds the threshold, the agent falls back to presenting the standard form regardless of the conversational form filling setting.

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How conversational form filling works

  1. User makes a request that triggers a form (for example, reporting an issue or requesting access)
  2. Agent identifies the required form fields and checks whether the form qualifies for conversational mode (field count is at or below the threshold)
  3. Agent extracts any field values already mentioned in the conversation
  4. For remaining required fields, the agent asks for each value one at a time
  5. For forms with conditional fields, dependent fields are skipped until their parent field has a matching value
  6. User provides values through natural language responses
  7. Once all required fields are collected, the agent presents the form for review (or auto-submits if auto-submit is enabled)
Private forms always use the standard form UI regardless of conversational form filling settings. This ensures sensitive information is collected through the secure form interface rather than in a channel conversation.

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Which mode to use

Conversational mode

Best for straightforward forms with few required fields, like a password reset that only needs a username and urgency level.

Standard form

Best for forms where users benefit from seeing all fields at once, such as access requests with multiple approvers or file attachments.
When forms include user selection fields, the agent uses User Lookup to resolve names to user IDs during conversational collection. For user group selection fields, the agent uses Group Lookup to resolve group names to IDs.
For DATE fields, the agent resolves relative expressions like “tomorrow”, “next Monday”, or “in 2 weeks” to concrete YYYY-MM-DD values automatically. Dates are resolved in UTC, so for requests near midnight the resolved day may be off by one.
Last modified on July 27, 2026