statistical tests

.github/agents/plot-creator.agent.md

@@ -48,13 +48,12 @@ Check if an existing `transform_<descriptive_name>` function exists in `utils.py
 def transform_<descriptive_name>(self, df: pl.LazyFrame | pl.DataFrame) -> tuple[pl.LazyFrame, dict | None]:
     """Transform <input_description> to <output_description>.
     
-    Original request: "<paste user's original question here>"
+    Original use-case: "<paste user's original question here>"
     
     This function <concise 1-2 sentence explanation of what it does>.
     
     Args:
-        df: Pre-fetched data (e.g., from get_character_refine()). 
-            Do NOT call get_*() methods inside this function.
+        df: Pre-fetched data as a Polars LazyFrame or DataFrame.
     
     Returns:
         tuple: (LazyFrame with columns [...], Optional metadata dict)
@@ -96,19 +95,11 @@ chart = S.plot_character_trait_frequency(trait_freq)
 ```
 
 ### Step 5: Create Temporary Test File
-Create `debug_plot_temp.py` for testing. **You MUST ask the user to provide:**
+Create `debug_plot_temp.py` for testing. **Prefer using the data snippet already provided by the user.**
 
-1. **The exact code snippet to create the test data** - Do NOT generate or assume file paths
-2. **Confirmation of which notebook they're working in** (so you can read it for context if needed)
+**Option A: Use provided data snippet (preferred)**
+If the user provided a `df.head()` or sample data output, create inline test data from it:
 
-Example prompt to user:
-> "To create the test file, please provide:
-> 1. The exact code snippet that produces the dataframe you shared (copy from your notebook)
-> 2. Which notebook are you working in? (I may read it for context, but won't modify it)
-> 
-> I will NOT attempt to load any data without your explicit code."
-
-**Test file structure using user-provided data:**
 ```python
 """Temporary test file for <plot_name>.
 Delete after testing.
@@ -118,15 +109,32 @@ from theme import ColorPalette
 import altair as alt
 
 # ============================================================
-# USER-PROVIDED TEST DATA (paste from user's snippet)
+# TEST DATA (reconstructed from user's df.head() output)
 # ============================================================
-# <user's code goes here>
+test_data = pl.DataFrame({
+    "Column1": ["value1", "value2", ...],
+    "Column2": [1, 2, ...],
+    # ... recreate structure from provided sample
+})
 # ============================================================
 
 # Test the plot function
-# ...
+from plots import QualtricsPlotsMixin
+# ... test code
 ```
 
+**Option B: Ask user (only if necessary)**
+Only ask the user for additional code if:
+- The provided sample is insufficient to test the plot logic
+- You need to understand complex data relationships not visible in the sample
+- The transformation requires understanding the full data pipeline
+
+If you must ask:
+> "The sample data you provided should work for basic testing. However, I need [specific reason]. Could you provide:
+> 1. [specific information needed]
+> 
+> If you'd prefer, I can proceed with a minimal test using the sample data you shared."
+
 ### Step 6: Create Plot Function
 Add a new method to `QualtricsPlotsMixin` in `plots.py`: