Unlock the full potential of your AI assistant by turning conversations into real-world actions, from creating records to triggering workflows.
In most chats, the conversation ends when the question is answered. But with Cogfy’s creation tools, that’s just the beginning. These tools transform your chatbot into an active agent—capable of triggering real actions like creating records, updating databases, scheduling events, and even sending files.
While retrieval tools make your assistant smarter, creation tools make it useful. They allow your chat to become a seamless extension of your product, operations, or workflow engine. Whether it’s logging support tickets, capturing leads, or triggering custom backend processes—these tools are how your chat stops being passive and starts doing things.
Now let’s look at the tools that move your chatbot from helpful to hands-on. These tools allow your assistant to actually do things—submit, store, trigger, update. Think of them as the bridge between conversation and action.
This is where your chatbot starts shaping data. The Cogfy Interaction tool lets you create, update, or delete records from your own collections, making it easy to capture structured information as part of the conversation.
The HTTP Request tool gives your bot access to the web in a more direct way—by calling predefined APIs. Whether it’s sending a webhook or pushing an order to your backend, this tool is the universal connector.
Your bot, now with calendar superpowers. This tool lets the assistant manage events—create, update, delete, or check availability—on a connected Google Calendar.
Turn chat into tickets. With Jira integration, your chatbot can create and list issues directly onto your configured board, saving users the trouble of logging in and navigating forms.
All of these tools are powerful because they turn chat into action—and the next section will show you how to set them up for success.
Setting up creation tools is all about clarity and control. You’re giving your assistant the ability to act, so your configuration needs to guide that power carefully. Here are a few best practices to keep things smooth, safe, and effective:
🛠️ Be clear with tool descriptions Each creation tool you configure includes a name and a description—this is the assistant’s instruction manual. Make the description specific, action-oriented, and free of ambiguity. For example, instead of “Sends user data,” go with “Creates a new lead with name, email, and company.”
🔒 Use separate tools for separate actions It’s better to split actions across multiple tools rather than overloading one. For instance, use one Cogfy tool for saving lead info and another for booking a meeting. This keeps things modular, easier to debug, and gives the assistant clearer decision paths.
🤖 Guide the LLM to format data correctly
When you're using creation tools—especially Cogfy Interaction—it’s crucial to tell the assistant how to shape the data before saving it. Use the Instructions middleware to guide formatting explicitly. For example, if you're saving a date, add a note like: “Always convert dates to ISO 8601 format (e.g., 2025-12-31) before submitting.” This helps prevent invalid inputs and keeps your records clean and structured.
🧼 Sanitize user input before saving Even though the LLM handles text beautifully, remember that user input isn’t always clean. If your workflow involves saving structured data (like names, emails, feedback), make sure your tool setup matches the expected format. Use validation on your collections if needed.
Once configured well, creation tools transform your chatbot from a passive helpdesk into an active teammate—ready to file, schedule, update, and streamline operations in real time.
Now that you've seen how Cogfy’s creation tools can turn conversations into structured, actionable data, the next step is connecting that data to your workflows. Whether it's generating leads, automating scheduling, or capturing user feedback—you’re not just building a chatbot, you’re building a workflow engine.
In the next post, we’ll show you how to bring it all together with real-world use cases. From combining retrieval and creation tools to designing full conversational funnels, you'll see how these pieces unlock powerful automation. Keep building—your chatbot is about to become your favorite coworker.