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docs: Use column description in skill schema example #395

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11 changes: 5 additions & 6 deletions skills/SKILL.md
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Original file line number Diff line number Diff line change
Expand Up @@ -25,10 +25,8 @@ class MyHouseSchema(dy.Schema):

street = dy.String(primary_key=True)
number = dy.UInt16(primary_key=True)
#: Description on the number of rooms.
rooms = dy.UInt8()
#: Description on the area of the house.
area = dy.UInt16()
rooms = dy.UInt8(description="Number of rooms")
area = dy.UInt16(description="Area of the house")
```

The schema can be used in type hints via `dy.DataFrame[MyHouseSchema]` and `dy.LazyFrame[MyHouseSchema]` to express
Expand All @@ -41,8 +39,9 @@ runtime.

### Defining Constraints

Persist all implicit assumptions on the data as constraints in the schema. Use docstrings purely to answer the "what"
about the column contents.
Persist all implicit assumptions on the data as constraints in the schema. Prefer using the `description` argument to
answer the "what" about the column contents, while comments can be used to specify details that are not strictly
schema-related or relevant only to a specific data interface.
Comment on lines +42 to +44

@mathisdrn Mathis Derenne (mathisdrn) Aug 17, 2026 •
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The # Shared primary key component with MyHouseSchema comment in MyStreetSchema was re-added because it relate to documentation rather than reference code example for AI agents.


- Use the most specific type possible for each column (e.g. `dy.Enum` instead of `dy.String` when applicable).
- Use pre-defined arguments (e.g. `nullable`, `min`, `regex`) for column-level constraints if possible.
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