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| research_task: | |
| description: > | |
| You will be given {data}, a 2D Python List[List[str|None]] structured as follows: | |
| - Row 0 is the header: the first column is always 'String', and the rest are language names. | |
| - Rows 1…n contain translation data for each key. | |
| YOU MUST identify the list of language columns **explicitly** from the header row for translating later. | |
| ONLY and must translate into languages that are actually present — do NOT assume or invent or copy (for example copy English phase to French language). | |
| Your responsibilities: | |
| 1. Parse the headers to identify all **existing** language columns. | |
| → DO NOT assume the existence of any column unless explicitly present. | |
| → DO NOT create new columns (e.g., 'English'). | |
| 2. For each row: | |
| a. Derive the English phrase from the 'String' key: | |
| - Remove the prefix 'STR_' | |
| - Replace all underscores with spaces | |
| - Convert the phrase to Title Case | |
| b. Use this derived phrase as the translation base. | |
| c. IMPORTANT STEP: For each language cell: | |
| - If the cell is: | |
| • Empty | |
| • Null | |
| • Whitespace | |
| • **OR exactly matches `english_phrase`** (**CRITICAL**: this is not a valid translation!) | |
| → Then translate `english_phrase` into the TARGET LANGUAGE. | |
| → The translation must: | |
| • Be natural and fluent | |
| • Match Title Case | |
| • Contain **no** extra punctuation, quotes, or added words | |
| - Otherwise: leave the cell unchanged. | |
| expected_output: > | |
| A 2D Python `List[List[str]]` of identical shape where: | |
| - All originally missing translation cells are now correctly filled | |
| - Table structure is preserved exactly (no added columns, no reordering) | |
| - Existing non-empty translations remain unchanged | |
| - All derived English phrases are used strictly as translation bases | |
| - All new translations follow capitalization and output rules strictly | |
| agent: translator_researcher | |