What is Agent Framework?
An agent framework is a class of software library or toolkit that provides the scaffolding for building systems in which a language model plans, calls tools, and acts over multiple steps. Typical components include a control loop, tool registration, state and memory handling, and observability hooks. Frameworks differ in how much control they take from application code.
The recurring core is a loop. The framework sends the model a prompt describing the available tools, parses the response into either a final answer or a tool call, executes the call, appends the result to the conversation state, and repeats until a stopping condition is met. Everything else a framework provides is arranged around making that loop observable, resumable, and safe.
Common features include declarative tool schemas so the model knows call signatures, memory abstractions for short and long term context, retry and timeout policies, structured output validation, checkpointing so a run can resume after failure, and tracing that records every prompt, tool call, and result. Multi agent variants add message passing, role assignment, and coordination between separate agent instances.
Frameworks vary along an important axis of control. Higher level ones supply opinionated abstractions that reduce code but constrain how the loop behaves and make debugging indirect. Lower level ones expose the graph or state machine explicitly, which costs more implementation effort but keeps behavior inspectable. Some teams write the loop themselves, since the loop itself is short.
Security is a framework concern rather than an afterthought, because tool access converts model output into real actions. Sandboxed execution, least privilege on every credential, validation of tool arguments, explicit approval steps for consequential actions, egress restrictions, and a complete audit trail are the controls that limit damage when a model is misled by instructions hidden in retrieved content.
Key points
- Software scaffolding for tool using, multi step model driven systems.
- Provides the control loop, tool schemas, state, and tracing.
- Options range from opinionated abstractions to explicit state machines.
- Multi agent variants add messaging and coordination.
- Sandboxing, least privilege, and audit trails are core concerns.
In practice
A developer builds an assistant that answers questions about internal documents. The framework registers two tools, a search function and a ticket creation function, and describes both to the model. On each turn the loop passes the conversation plus the tool schemas to the model, executes whichever tool is requested, and feeds the result back. Every step is traced for review.