> ## Documentation Index
> Fetch the complete documentation index at: https://handlebar.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Deterministic Rule Engine

> How Handlebar evaluates your policies for AI agents

This is the core of Handlebar.

If this part isn't solid, nothing else matters.

## The Problem We're Solving

Most agent governance systems rely on:

* Probabilistic classifiers
* Post-hoc analysis
* Human review after damage is done

That breaks down immediately in regulated environments.

You cannot:

* Explain probabilistic decisions to auditors
* Replay historical decisions reliably
* Enforce guarantees with systems that "usually" work

**Handlebar's rule engine is intentionally boring.**

**Rules are pure functions over explicit inputs.**

## What Rules Can See

Rules are evaluated at well-defined points (primarily before tool calls).

They can inspect:

* Agent identity
* Run metadata
* Tool identity and metadata
* Tool call parameters
* Organisation configuration
* Historical signals (explicitly versioned)

**If data is not explicitly available to a rule, it does not exist.**

This constraint is intentional. It makes decisions explainable.

## Rule Evaluation Lifecycle

At runtime:

1. An agent attempts a tool call
2. Relevant rules are evaluated in a defined order
3. Actions are produced
4. Actions are enforced

No retries. No best-effort. No silent fallbacks.

## Ordering and Conflicts

Rules are evaluated in a predictable order.

When multiple rules apply:

* Actions are composed deterministically
* Conflicts are resolved explicitly

For example:

* A single block action wins over multiple allows
* A require approval can short-circuit execution

There is no "last rule wins" ambiguity.

## Versioning and Replay

Every rule has a version.

When a decision is made, we record:

* Rule IDs
* Rule versions
* Inputs
* Outputs

This allows:

* Exact replay of historical decisions
* Diffing behaviour across rule versions
* Confident rule changes

You can answer questions like:
**"Would this run have been allowed under last month's rules?"**

## Bottom Line

The rule engine is the line you don't cross.

Everything before it can be creative.
Everything after it can be powerful.

**The decision itself must be boring, predictable, and provable.**