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Use when reading or writing Python files (.py, pyproject.toml, requirements.txt).
Passed 23 of 23 test cases with the skill, and 19 of 23 without it.
and 3 more in the full report
4 fixed19 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
What command should be placed in a GitHub Actions workflow to run Astral's fast type checker on the src/ directory using uvx without installing it beforehand?
| Checked | Without skill | With skill |
|---|---|---|
| The response specifies the command uvx ty check src/. | Missed | Passed |
The instructions your model reads when the skill loads.
Follows type-first, functional, and error handling patterns from CLAUDE.md. This skill covers language-specific idioms only.
Use Python's type system to prevent invalid states at type-check time.
Frozen dataclasses for immutable domain models:
from dataclasses import dataclass
from datetime import datetime
@dataclass(frozen=True)
class User:
id: str
email: str
name: str
created_at: datetime
# Frozen dataclasses are immutable — no accidental mutation
Discriminated unions with Literal:
from dataclasses import dataclass
from typing import Literal
@dataclass
class Success:
status: Literal["success"] = "success"
data: str
@dataclass
class Failure:
status: Literal["error"] = "error"
error: Exception
RequestState = Success | Failure
test cases passed, vs 19 / 23 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.