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Agent Inputs and Outputs
An AI agent receives inputs and produces outputs. Understanding what goes in and what comes out is essential for designing agent systems.
6 min•By Priygop Team•Updated 2026
Agent Inputs
- Goal or task description: what the agent is supposed to achieve
- User context: who is asking, their preferences, permissions, and history
- Tool results: data returned by tools the agent has already called
- External data: information from APIs, databases, or files
- System instructions: rules and restrictions the agent must follow
- Previous state: what the agent has already done in the current task
Agent Outputs
- Actions: API calls, file operations, email sends, database writes
- Tool calls: requests to use specific tools with specific arguments
- Decisions: what to do next, which tool to use, whether to continue or stop
- Responses: text, reports, summaries, or structured data returned to the user
- Escalations: requests for human review or approval before continuing
- Logs: records of what the agent did, when, and what result it received
Key Takeaways
- An AI agent receives inputs and produces outputs.
- Goal or task description: what the agent is supposed to achieve
- User context: who is asking, their preferences, permissions, and history
- Tool results: data returned by tools the agent has already called