Learning guide
AI Agent Safety Terms in Market Tools
Understand tool routers, policy engines, human approval, audit logs, and prompt firewalls in AI-assisted workflows.
Agent words describe control flow
An AI agent is not just a chat box. In product language, it often means a system that can receive a goal, choose tools, read context, take steps, and decide whether to continue. That makes the safety vocabulary important.
Market and finance tools can involve sensitive data, permissioned actions, or time-sensitive decisions. Before an agent is useful, the workflow needs clear rules about what it may read, what it may call, and when a human must approve the next step.
Routers and policy engines
A tool router decides which external capability an AI system should use. A policy engine checks whether a requested action fits the allowed rules. For example, a system may allow a read-only dashboard query while blocking an account-changing action.
These terms are operational. They describe how a workflow prevents a model from turning a vague instruction into an unsafe action.
Approvals and audit trails
Human approval means a person must review a proposed action before it happens. An audit log records what the system saw, what it decided, which tool it called, and what result came back.
The point is accountability. If an agent makes a surprising recommendation or tries to call the wrong tool, traces and logs help developers understand where the behavior came from.
How this appears in the game
AI safety cards often group by permission, traceability, and constraint. Tool router, policy engine, human approval, audit log, and prompt firewall all describe ways to limit or review automated actions.
The game includes AI terms because financial products increasingly use automation language. The site still stays educational and does not provide trading automation instructions.