An AI tool is a skill or capability that the Thunk.AI platform gives an AI agent to extend what it can do, to bring in information it doesn't have, or for it to record its work. Instead of responding to an instruction with a message, an AI agent can respond by invoking an AI tool with appropriate parameters. You can think of a tool invocation as a structured response from the AI agent. Thunk.AI makes extensive use of tool invocations as the primary mechanism for AI agents to respond.
Usually, AI tools are used to connect an AI agent to the rest of the business work environment and the other applications and data in that environment. Some tools are used to fetch information (eg: search a company database) while other tools perform actions (eg: create new documents or update external systems).
AI Tool Libraries
Many AI tools are built into the system in functionality bundles called AI Tool Libraries. There are different kinds of libraries:
Standard libraries: these are a default set of AI tool libraries with capabilities like web search and browsing, email drafting, image and video processing, and document processing.
Web search: tools to search the web, answer questions based on web content, read and extract information from web pages
File system module: tools to read, create, update, move, and delete files in a cloud file system (Google Drive or Office 365, depending on the user's work environment).
Image processing: tools to edit and query image content
Video processing: tools to edit and query video content
Communications: tools to draft or send email and messages
Document templating: tools to create documents based on parameterized templates
Application libraries: every user can augment their account with connections to other systems. For example, a user may add a Google Drive connection and this automatically enables an AI tool library that allows that user's AI agents to read and write files and spreadsheets and folders in that Google Drive. Learn more about integration with applications.
Imported thunk libraries: users can define AI tools in one thunk and share them across many other thunks (of their own or for access to other users as well). There are many benefits, especially when teams of users are implementing many AI agent automation processes. Learn more about modular reuse of thunks.
Platform libraries: some of the internal capabilities of the platform (eg: dynamic planning, or reflection, or workflow state update) are also represented as AI tools. While the user cannot directly author these tools, they can be configured in the same way as any other AI tool.
Custom AI Tools
In each thunk, the designer (with the help of their AI agent) can also create custom AI tools (eg: to connect to specific enterprise systems or databases). Custom tool categories include:
API tools that can invoke any REST API using HTTPS. The API tools can utilize connection credentials that have been saved at the account level. This ensures that connection credentials do not have to be repeated in every tool.
Database query and update tools that invoke any SQL commands with a database connection.
Code-based tools that implement logic using deterministic Typescript code
AI tools that combine natural language instructions with existing tools to build intelligent composite tools.
Tool and Library Configuration
The thunk designer can enable or disable entire libraries or specific tools within the libraries. Only these libraries and tools are made available to the AI agents as they execute specific AI Instructions within the thunk. Further, the designer can define constraints on how the tool should be used. For example, the web search tool can be constrained as follows: “only search within site: acme.com”.
The choice of enabled libraries (and enabled tools within those libraries) and constraints on those tools are an important aspect of control for the thunk designer. They limit the degrees of freedom afforded to the AI agents and control the autonomy and agency of the AI agents are they execute workflows.