# Introduction
The system around your model.
HarnessX is a Python SDK for building agents that reason, call tools, and carry work across turns. You supply the model, tools, and policies. The harness runs the loop and exposes what happens along the way.
## Start with one agent
A typed Python function can be a tool. Pass it when you construct the agent, then await a run.
~~~python
import asyncio
from harnessx import Agent
def multiply(a: int, b: int) -> int:
"""Multiply two numbers."""
return a * b
async def main():
async with Agent(tools=[multiply]) as agent:
result = await agent.run("What is 40 * 10? Use multiply.")
if result.error:
raise RuntimeError(result.error["message"])
print(result.output)
asyncio.run(main())
~~~
This example makes live calls using the default Anthropic provider. Export your API key first. Custom tools inherit the default ALLOW policy; choose explicit permissions for tools with external effects.
## What the harness provides
| Layer | What it does | Learn more |
| --- | --- | --- |
| Agent loop | Sends context to a provider, validates and dispatches tools, returns results | [Agents](../agents/) |
| Capabilities | Typed functions, external MCP tools, lazy skill instructions, and OKF knowledge bundles | [Tools](../tools/), [MCP](../mcp/), [Skills](../skills/), [Knowledge](../knowledge/) |
| Context | Conversation history, notes, structured facts, and result spilling | [Memory](../memory/) |
| Decisions | Standalone Choice routing, Score rubrics, and Noul evidence assessments | [Decisions with Jev](../decisions/) |
| Control | Permissions, explicit approval, budgets, and replay policies | [Permissions](../permissions/) |
| Execution | Direct runs or durable sessions with persisted execution boundaries | [Durable agent runs](../durable-agent-runs/) (advanced) |
| Inspection | Typed streaming events, lifecycle hooks, traces, and incident archives | [Streaming](../streaming/), [Flight recorder](../flight-recorder/) |
## Choose the execution model
Use **Agent** for an in-process conversation or request. It retains history while the instance lives. Use snapshots to explicitly save and reload a conversation.
The advanced [Durable agent runs](../durable-agent-runs/) guide introduces **AgentRuntime** for work that must pause for an approval or be recovered after a process failure. Its default SQLite backend persists execution state and events. PostgreSQL and Temporal implementations exist, with service qualification still required.
These are two entry points into the shared execution engine. Ordinary and streaming runs use the same tool and permission semantics.
## Explore the city
[The city map](../../) is an interactive map of the SDK: the workshops are tools, the crossing is permissions, the archive is memory, the vault is the flight recorder, and the fenced yard is the sandbox. Select a district to learn what it represents and follow its link into these docs.
The city illustrates the architecture; it is not connected to a running agent.
## Know the boundaries
HarnessX does not promise universal rollback or exactly-once external writes. Recovery depends on the tool's replay policy and its adapter. Incident playback displays captured records without running models or tools; it is not a deterministic rerun of a live model.
See [Implementation status](../status/) for available, service-dependent, and planned capabilities.