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Use a saved partition when repeated observations, conversations or related source examples must stay together. Begin with an inspected, prepared source cell and a known task contract. Start with the fraud example dataset from Prepare data. The agent inspects related transactions and chooses an appropriate split. What you get: A saved partition recipe, actual role counts and exact cells without shared groups. The steps below describe the workflow your agent follows and the results to verify.
  1. Identify related records: source groups, conversations, repeated inputs and synthetic descendants. Declare additional grouping fields from evidence rather than guessing from column names.
  2. Choose role fractions and a fixed seed. Use train for fitting, development for recipe/checkpoint decisions, calibration for fitting calibration and final for the independent comparison. Leave unused roles out of the recipe.
  3. Call create_data_partition with name, request_key, source_cell and recipe. The recipe accepts seed, fractions, group_by, optional stratify_by and explicit holdouts.
  4. Follow the returned job through construction. Inspect actual role counts and group assignment; group sizes may prevent exact requested fractions.
  5. Verify the output cells against their intended consumer. Train/development roles receive training intent, while calibration/final roles receive evaluation intent. Native decision rows in calibration/final members are projected into input-only decisions and separate references. Other row formats are retained; changing intent alone does not convert them.
  6. Save the role cell IDs and use them explicitly in later jobs.
Do not deduplicate repeated observations merely to achieve a ratio. Preserve their weights and provenance. Missing declared group fields are an error to resolve, not a reason to silently drop the grouping rule. Use retry_data_partition only after inspecting a failed construction and the supported recovery action. It resumes the saved recipe rather than inventing another split. For a data-first modelling project, retain the task definition and exact role cells in save_training_plan. Final answers must not guide recipe selection. See Data lineage and held-out evidence.