Update Agent Canvas automations docs for new secrets flow

openhands/usage/agent-canvas/prebuilt/github-pr-review.mdx

@@ -63,32 +63,22 @@
 4. Open `MCP Servers`.
 5. Select `GitHub` from the MCP library.
 6. Paste the GitHub token you created earlier.
-7. Save the MCP server configuration.
-
-## Add the GitHub Token as a Secret
-
-Some automations also need the token available as a backend secret, especially when the agent runs GitHub commands or accesses private repositories.
-
-1. Open `Settings`.
-2. Open `Secrets`.
-3. Click `Add a new Secret`.
-4. Set the secret name to `GITHUB_TOKEN`.
-5. Paste the GitHub token as the secret value.
-6. Save the secret.
+7. Make sure the secret-creation toggle is on so Agent Canvas creates the token secret automatically when you save the MCP server configuration.
+8. Save the MCP server configuration.
 
 ## Start the PR Review Workflow
 
 1. Open `Automate` in the left navigation.
 2. Find `Start from a proven workflow`.
 3. Choose the GitHub PR review workflow.
 4. Agent Canvas opens a new conversation with a prefilled setup prompt.
 5. Send the prompt as-is, or edit it first if you already know what you want.
 
 After you send the prompt, the agent starts a setup conversation. It uses the preconfigured skills and GitHub access to interview you, clarify the review workflow, and create the automation.
 
 ## Customize the Review
 
 You do not need to know every detail before sending the prefilled prompt. The agent will ask follow-up questions to clarify:
 
 - The repository owner and name
 - Which pull requests to review
@@ -96,7 +86,7 @@
 - Whether the agent should inspect CI results before commenting
 - Any files, directories, or checks the reviewer should ignore
 
 You can edit the prefilled prompt before sending it if you want to provide any of those details up front.
 
 ## Verify the Automation
 

openhands/usage/agent-canvas/prebuilt/github-repo-monitor.mdx

@@ -65,32 +65,22 @@
 4. Open `MCP Servers`.
 5. Select `GitHub` from the MCP library.
 6. Paste the GitHub token you created earlier.
-7. Save the MCP server configuration.
-
-## Add the GitHub Token as a Secret
-
-Some automations also need the token available as a backend secret, especially when the agent runs GitHub commands or accesses private repositories.
-
-1. Open `Settings`.
-2. Open `Secrets`.
-3. Click `Add a new Secret`.
-4. Set the secret name to `GITHUB_TOKEN`.
-5. Paste the GitHub token as the secret value.
-6. Save the secret.
+7. Make sure the secret-creation toggle is on so Agent Canvas creates the token secret automatically when you save the MCP server configuration.
+8. Save the MCP server configuration.
 
 ## Start the Repository Monitor Workflow
 
 1. Open `Automate` in the left navigation.
 2. Find `Start from a proven workflow`.
 3. Choose the GitHub repository monitor workflow.
 4. Agent Canvas opens a new conversation with a prefilled setup prompt.
 5. Send the prompt as-is, or edit it first if you already know what you want.
 
 After you send the prompt, the agent starts a setup conversation. It uses the preconfigured skills and GitHub access to interview you, clarify the monitoring workflow, and create the automation.
 
 ## Customize the Monitor
 
 You do not need to know every detail before sending the prefilled prompt. The agent will ask follow-up questions to clarify:
 
 - The repository owner and name
 - The events or conditions the monitor should watch
@@ -98,7 +88,7 @@
 - What the agent should do when it finds a match
 - Where the agent should report results, such as a GitHub comment or Slack channel
 
 You can edit the prefilled prompt before sending it if you want to provide any of those details up front.
 
 For example, you can ask the monitor to watch for failed workflow runs, summarize the failure, and open a pull request when the fix is straightforward.
 

openhands/usage/agent-canvas/prebuilt/slack-channel-monitor.mdx

@@ -90,32 +90,22 @@
 5. Select `Slack` from the MCP library.
 6. Paste the bot token.
 7. Enter your Slack workspace ID.
-8. Save the MCP server configuration.
-
-## Add the Slack Bot Token as a Secret
-
-Some automations also need the token available as a backend secret.
-
-1. Open `Settings`.
-2. Open `Secrets`.
-3. Click `Add a new Secret`.
-4. Set the secret name to `SLACK_BOT_TOKEN`.
-5. Paste the bot token as the secret value.
-6. Save the secret.
+8. Make sure the secret-creation toggle is on so Agent Canvas creates the bot token secret automatically when you save the MCP server configuration.
+9. Save the MCP server configuration.
 
 ## Start the Slack Channel Monitor Workflow
 
 1. Open `Automate` in the left navigation.
 2. Find `Start from a proven workflow`.
 3. Choose the Slack channel monitor workflow.
 4. Agent Canvas opens a new conversation with a prefilled setup prompt.
 5. Send the prompt as-is, or edit it first if you already know what you want.
 
 After you send the prompt, the agent starts a setup conversation. It uses the preconfigured skills and Slack access to interview you, clarify the channel monitor, and create the automation.
 
 ## Customize the Monitor
 
 You do not need to know every detail before sending the prefilled prompt. The agent will ask follow-up questions to clarify:
 
 - The Slack channel or channels to monitor
 - The message pattern, keyword, or mention that should trigger the agent
@@ -123,9 +113,15 @@
 - Whether the agent should reply in Slack
 - Any GitHub repository or external service the agent should use
 
+
+<Info>
+  If you want the automation to watch for `@your-bot-name`, tell the agent to watch for Slack bot mentions as well as the trigger phrases you set. That way, it can respond when someone mentions the bot directly, not just when a specific keyword appears.
+</Info>
+
 You can edit the prefilled prompt before sending it if you want to provide any of those details up front.
 
-For example, you can ask the monitor to watch an alerts channel, summarize new incidents, and create a GitHub issue when a message includes a production error.
+For example, you can ask the tell the agent to configure the automation to watch an #alerts channel, summarize new incidents, and create a GitHub issue when a message includes a production error.
+
 
 ## Verify the Automation