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Add AGENTS.md

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@@ -54,7 +54,7 @@ requests, not rows, if you want to keep them together.
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  ## Row order and configs
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  The first 1,000 train rows rotate through sources (in alphabetical order) so the Hub viewer shows
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- variety; after them, train is shuffled by question group. Shuffle before training or taking a
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  sample, or the prefix over-represents small sources:
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  ```python
@@ -76,6 +76,7 @@ The `default` config is a steered mix of about 1M rows. `full` has every row of
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  one label), `criteria_permutation`, `instruction_paraphrase`, `paired_text_format`
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  (surface variations), `packed_derived` (questions over 2-4 packed items).
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  - `example_id`: a stable hash of the source example's input and gold answer, shared by its variants.
 
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  - `split`: the source's own split (`train`, `dev`, `test`); it matches the Hub split.
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  ```python
 
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  ## Row order and configs
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  The first 1,000 train rows rotate through sources (in alphabetical order) so the Hub viewer shows
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+ variety; after them, train is shuffled by question group, by a hash of the group, so a group keeps its relative place across releases. Shuffle before training or taking a
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  sample, or the prefix over-represents small sources:
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  ```python
 
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  one label), `criteria_permutation`, `instruction_paraphrase`, `paired_text_format`
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  (surface variations), `packed_derived` (questions over 2-4 packed items).
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  - `example_id`: a stable hash of the source example's input and gold answer, shared by its variants.
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+ - `source_index`: the example's original row in its source dataset (`split:row`), to trace a label back to the source; empty for packed and procedural rows.
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  - `split`: the source's own split (`train`, `dev`, `test`); it matches the Hub split.
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  ```python