An AI agent without tools is a language model that generates answers but does nothing further. Tools give the agent the ability to act: search, read, write, calculate, call external systems. This article provides an overview of the types of tools and how to make a good selection.
The choice of tools largely determines what an AI agent can do. An agent with only a search tool can do research but cannot save anything. An agent with write access to a database can update data but may make unintended changes. Thinking about which tools an agent gets is therefore also thinking about its capabilities and risks.
In the context of AI agents, tools are functions that the agent can call to do something outside its own context. The model does not generate the output of the tool itself; it calls the tool with parameters and receives the result back. The model then processes that result as part of its reasoning.
Tools are defined by the developer: name, description, parameters and what they return. The model uses the description to decide when a tool is relevant. A good description is not technical documentation but a clear explanation of what the tool does and when to use it.
Search tools give the agent access to information that is not in its training data. The most common are:
Search tools are almost always safe to give to an agent: they only read, they write nothing. The risks lie with write tools.
Write tools give the agent the ability to create or modify something. That can include:
These tools have a higher risk profile. A writing error or a misunderstood instruction can lead to incorrect data, unwanted communications or loss of information. Limit write tools to what is strictly necessary and consider human-in-the-loop for irreversible actions.
Some agents have the ability to execute code in a sandboxed environment. This is useful for:
Code execution adds power but requires a good sandbox. Make sure the environment has no access to production data or systems unless that is explicitly intended.
Via API connectors an agent can control external systems. Think of:
Each API connector carries the risk of actions in production systems. Work with minimal permissions: the agent receives only the API permissions it needs for its task, nothing more.
Start with the question: what does the agent need to be able to do to complete its task? List the steps and determine which tool is needed for each step. Then add only those tools, no more.
Avoid the temptation to give an agent an extensive toolkit on the expectation that it will use it well by itself. The more tools, the greater the chance of unintended use. The more specific the toolset, the better the agent performs at its core task.
At Mach8 we design toolsets as part of the broader agent design, always with minimal permissions and the risk profiles of the individual tools in mind.
AI tools are the building blocks that turn a language model into an agent that actually does something. The right selection of tools determines what an agent can handle and what the risks are. Start narrow and only expand once the basic tools are working well.
Want to know which tools fit your desired agent use? Get in touch with Mach8 or see our AI agents services.
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