python-type-safety

A guide to using Python type hints, reusable type parameters, protocols, and strict checking to catch code errors before running the program.

In plain words
What is it for?
Use it to annotate public functions and classes, describe reusable interfaces, and handle values that may be missing or have different types.
Why use it?
It makes expected inputs and outputs explicit and lets checking tools find mismatches during development.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/jartan-llc/grimoire/python-type-safety
Any agent
npx skills add Jartan-LLC/grimoire --skill python-type-safety
Clone the repo
git clone --depth 1 https://github.com/Jartan-LLC/grimoire

Made for: Claude Code, Codex.

Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,303 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00022 $0.01303
Opus 5 $0.00011 $0.00651
Sonnet 5 $0.00004 $0.00261
Haiku 4.5 $0.00002 $0.00130

Measured 2d ago against content hash 91b403f3d045, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

python-type-safety scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/pythonica/skills/python-type-safety/SKILL.md · 194 lines

How it starts

The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Type Safety

Leverage Python's type system to catch errors at static analysis time. Type annotations serve as enforced documentation that tooling validates automatically.

Core Concepts

1. Type Annotations

Declare expected types for function parameters, return values, and variables.

2. Generics

Write reusable code that preserves type information across different types.

3. Protocols

Define structural interfaces without inheritance (duck typing with type safety).

4. Type Narrowing

Use guards and conditionals to narrow types within code blocks.

Quick Start

def get_user(user_id: str) -> User | None:
    """Return type makes 'might not exist' explicit."""
    ...

# Type checker enforces handling None case
user = get_user("123")
if user is None:
    raise UserNotFoundError("123")
print(user.name)  # Type checker knows user is User here

Fundamental Patterns

Pattern 1: Annotate All Public Signatures

Every public function, method, and class should have type annotations.

def get_user(user_id: str) -> User:
    """Retrieve user by ID."""
    ...

def process_batch(
    items: list[Item],
    max_workers: int = 4,
) -> BatchResult[ProcessedItem]:
    """Process items concurrently."""
    ...

class UserRepository:
    def __init__(self, db: Database) -> None:
        self._db = db

    async def find_by_id(self, user_id: str) -> User | None:
        """Return User if found, None otherwise."""
        ...

    async def find_by_email(self, email: str) -> User | None:
        ...

    async def save(self, user: User) -> User:
        """Save and return user with generated ID."""
        ...

Use mypy --strict or pyright in CI to catch type errors early. For existing projects, enable strict mode incrementally using per-module overrides.

Pattern 2: Use Modern Union Syntax

Python 3.10+ provides cleaner union syntax.

# Preferred (3.10+)
def find_user(user_id: str) -> User | None:
    ...

def parse_value(v: str) -> int | float | str:
    ...

# Older style (still valid, needed for 3.9)
from typing import Optional, Union

def find_user(user_id: str) -> Optional[User]:
    ...

Read the full file on GitHub · 194 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 194 lines · 22 tokens per session scan A 91b403f3d045

Subscribe to this mod's changes

python-type-safety is a skill published in the GitHub repository Jartan-LLC/grimoire (2 stars, last pushed 14d ago), licensed MIT. It adds 22 tokens to every session and 1,303 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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