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.
npx agentmods add skills/kid-sid/codex-spellbook/pydanticnpx skills add kid-sid/codex-spellbook --skill pydanticgit clone --depth 1 https://github.com/kid-sid/codex-spellbookWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/kid-sid/codex-spellbook/pydantic)<a href="https://agentmods.dev/skills/kid-sid/codex-spellbook/pydantic"><img src="https://agentmods.dev/badge/skills/kid-sid/codex-spellbook/pydantic.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00043 | $0.03031 |
| Opus 5 | $0.00022 | $0.01515 |
| Sonnet 5 | $0.00009 | $0.00606 |
| Haiku 4.5 | $0.00004 | $0.00303 |
Grade A, and why
pydantic 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 372 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pydantic v2 Patterns
Validation, serialization, and settings management with Pydantic v2.
When to Activate
- Defining request/response schemas or domain models
- Writing
@field_validatoror@model_validatorfor custom validation - Using
Annotatedto build reusable constrained types - Controlling serialization with
model_dump()/model_dump_json() - Building generic models or discriminated unions
- Validating arbitrary data (not a model) with
TypeAdapter - Configuring app settings from environment variables with
pydantic-settings
BaseModel Basics
from pydantic import BaseModel, Field
from datetime import datetime
from uuid import UUID
class User(BaseModel):
id: UUID
name: str
email: str
age: int = Field(ge=0, le=150)
role: str = "user" # default value
created_at: datetime | None = None
# Instantiate
user = User(id="a1b2...", name="Alice", email="[email protected]", age=30)
# Access
user.name # "Alice"
user.model_fields # dict of FieldInfo
# Validate from dict / JSON
user = User.model_validate({"id": "...", "name": "Alice", ...})
user = User.model_validate_json('{"id": "...", "name": "Alice", ...}')
Field Constraints
from pydantic import BaseModel, Field
from typing import Annotated
class Product(BaseModel):
name: str = Field(min_length=1, max_length=200, strip_whitespace=True)
price: float = Field(gt=0, description="Price in USD")
discount: float = Field(ge=0, le=1, default=0.0) # 0–100%
tags: list[str] = Field(default_factory=list, max_length=10)
sku: str = Field(pattern=r"^[A-Z]{3}-\d{6}$")
metadata: dict = Field(default_factory=dict)
# Alias — accept "product_name" in input, use "name" in Python
name: str = Field(alias="product_name")
Reusable constrained types with Annotated
from typing import Annotated
from pydantic import Field
# Define once, reuse everywhere
PositiveInt = Annotated[int, Field(gt=0)]
Percentage = Annotated[float, Field(ge=0.0, le=1.0)]
NonEmptyStr = Annotated[str, Field(min_length=1, strip_whitespace=True)]
EmailStr = Annotated[str, Field(pattern=r"^[^@]+@[^@]+\.[^@]+$")]
UserId = Annotated[str, Field(min_length=36, max_length=36)]
class CreateUserRequest(BaseModel):
name: NonEmptyStr
email: EmailStr
age: PositiveInt
discount: Percentage = 0.0
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.
- 4d ago First seen · 372 lines · 43 tokens per session scan A c146249406a9
pydantic is a skill published in the GitHub repository kid-sid/codex-spellbook (21 stars, last pushed 3mo ago), licensed MIT. It adds 43 tokens to every session and 3,031 once invoked, about $0.0002 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 2026-08-30.
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