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

# AgentsComparatorWorker.transform

**def AgentsComparatorWorker.transform**(self, data, agents=tuple(AGENTS)) [\[source\]](https://github.com/aigensys-labs/aidflow/blob/main/AID/\TRUENAS\aig_modeling_Products\AID\1_0_Lib\AID\selector\compare\agents_comparator.py#L522)

Re-evaluate the full comparison on a new dataset.

Runs the complete multi-agent scoring pipeline on any
data sample. Use this to:

* Monitor agent rankings on subsequent OOT windows.
* Compare a subset of agents (e.g., the top 2 from
  the initial ranking).
* Generate a fresh scoring report for a different
  segment or time period.
* Perform "What-If" analysis: does the ranking hold
  on a different sample?

#### Parameters

**`data`** : *`pDF`*
The dataset for performance evaluation (must contain\
target + features).

**`agents`** : *`tuple`*
Subset of agents to include (e.g., `(1, 2)` for\
a head-to-head comparison, or `(1, 3, 4)` for\
multiple agents).

#### Returns

*`AgentsComparatorResult`*
Full scoring package (overview, scoring, lift,\
calibration) for the requested agents.

> [!NOTE]
>
> **No State Change**: This method does not modify the
> fitted state. It produces a fresh analysis on the new
> data. The original fit results remain accessible via
> `.result` and `.stats`.
>
> **Head-to-Head**: Use `agents=(i, j)` for a focused
> comparison between two specific agents.


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