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 skills add hackermanishackerman/claude-skills-vault --skill pydantic-modelgit clone --depth 1 https://github.com/hackermanishackerman/claude-skills-vaultWrote 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/hackermanishackerman/claude-skills-vault/pydantic-model)<a href="https://agentmods.dev/skills/hackermanishackerman/claude-skills-vault/pydantic-model"><img src="https://agentmods.dev/badge/skills/hackermanishackerman/claude-skills-vault/pydantic-model/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hackermanishackerman/claude-skills-vault/pydantic-model"><img src="https://agentmods.dev/badge/skills/hackermanishackerman/claude-skills-vault/pydantic-model.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00028 | $0.02473 |
| Opus 5.5 | $0.00011 | $0.00989 |
| Sonnet 5.5 | $0.00006 | $0.00495 |
| Haiku 4.5 | $0.00003 | $0.00247 |
Grade A, and why
pydantic-model 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 1mo 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.
This is a copy
100% identical to pydantic-model — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 373 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pydantic Model Skill
Pydantic v2 model guidance for Travel Panel.
When to Use
- Creating req/res models for endpoints
- Defining DTOs
- Adding validation rules
- MongoDB ↔ API response conversion
Project Context
- Models:
app/classes/<feature>/ - Version: Pydantic v2 only
- Docs:
docs/endpoint-development-guide.md
CRITICAL: v2 API Only
| Deprecated (v1) | Use (v2) |
|---|---|
__fields__ |
model_fields |
__validators__ |
model_validators |
schema() |
model_json_schema() |
parse_obj() |
model_validate() |
dict() |
model_dump() |
json() |
model_dump_json() |
Model Creation
Step 1: Create Model File
Location: app/classes/<feature>/<feature>_models.py
from pydantic import BaseModel, Field, field_validator, model_validator
from typing import Optional, List
from datetime import datetime, timezone
from enum import Enum
class StatusEnum(str, Enum):
ACTIVE = "active"
INACTIVE = "inactive"
PENDING = "pending"
class ItemCreate(BaseModel):
"""Create item request."""
name: str = Field(..., min_length=1, max_length=255, examples=["My Item"])
description: Optional[str] = Field(None, max_length=2000)
status: StatusEnum = Field(default=StatusEnum.ACTIVE)
tags: List[str] = Field(default_factory=list, max_length=10)
price: float = Field(..., gt=0)
@field_validator("name")
@classmethod
def validate_name(cls, v: str) -> str:
v = v.strip()
if not v:
raise ValueError("Name cannot be empty")
return v
@field_validator("tags")
@classmethod
def validate_tags(cls, v: List[str]) -> List[str]:
return list(set(tag.lower().strip() for tag in v if tag.strip()))
class ItemUpdate(BaseModel):
"""Update item request (all opt)."""
name: Optional[str] = Field(None, min_length=1, max_length=255)
description: Optional[str] = Field(None, max_length=2000)
status: Optional[StatusEnum] = None
tags: Optional[List[str]] = None
price: Optional[float] = Field(None, gt=0)
@model_validator(mode="after")
def check_at_least_one_field(self) -> "ItemUpdate":
if not self.model_dump(exclude_unset=True):
raise ValueError("At least one field must be provided")
return self
class ItemGet(BaseModel):
"""Item response."""
id: str
name: str
description: Optional[str] = None
status: str
tags: List[str] = Field(default_factory=list)
price: float
company_id: str
created_at: datetime
updated_at: Optional[datetime] = None
created_by: Optional[str] = None
@classmethod
def from_mongo(cls, doc: dict) -> "ItemGet":
return cls(
id=str(doc.get("_id", "")),
name=doc.get("name", ""),
description=doc.get("description"),
status=doc.get("status", "active"),
tags=doc.get("tags", []),
price=doc.get("price", 0.0),
company_id=doc.get("company_id", ""),
created_at=doc.get("created_at", datetime.now(timezone.utc)),
updated_at=doc.get("updated_at"),
created_by=doc.get("created_by"),
)
class ItemListMeta(BaseModel):
totalRowCount: int
page: Optional[int] = None
pageSize: Optional[int] = None
stats: Optional[dict] = None
class ItemListResponse(BaseModel):
data: List[ItemGet]
meta: ItemListMeta
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.
- 1mo ago First seen · 373 lines · 28 tokens per session scan A b0be82f97fec
pydantic-model is a skill published in the GitHub repository hackermanishackerman/claude-skills-vault (2 stars, last pushed 15d ago), licensed MIT. It adds 28 tokens to every session and 2,473 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to pydantic-model, differing in 0 lines, and is treated as a copy.
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