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 perniemann/pnCore --skill pn-python-scaffoldinggit clone --depth 1 https://github.com/perniemann/pnCoreWrote 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/perniemann/pncore/pn-python-scaffolding)<a href="https://agentmods.dev/skills/perniemann/pncore/pn-python-scaffolding"><img src="https://agentmods.dev/badge/skills/perniemann/pncore/pn-python-scaffolding/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/perniemann/pncore/pn-python-scaffolding"><img src="https://agentmods.dev/badge/skills/perniemann/pncore/pn-python-scaffolding.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 | $0.00051 | $0.01253 |
| Opus 5.5 | $0.00020 | $0.00501 |
| Sonnet 5.5 | $0.00010 | $0.00251 |
| Haiku 4.5 | $0.00005 | $0.00125 |
Grade A, and why
pn-python-scaffolding 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.
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python backend scaffolding
When to use
- Starting a new Python API project (FastAPI, Flask, Django).
- Adding a new route, router, or domain module.
- Establishing project structure and config patterns from scratch.
Project structure
# FastAPI — domain-driven layout (preferred)
src/
users/
router.py # APIRouter with route definitions
service.py # Business logic
schemas.py # Pydantic request/response models
models.py # SQLAlchemy ORM models (if used)
orders/
router.py
service.py
schemas.py
core/
config.py # Settings via pydantic-settings
database.py # Async DB engine + session factory
errors.py # AppError class and exception handlers
security.py # Auth helpers (JWT decode, password hash)
main.py # FastAPI app factory, router registration
pyproject.toml # Dependencies + project metadata (preferred over requirements.txt)
.env.example # Required environment variables with placeholders
FastAPI scaffold
# src/users/schemas.py
from pydantic import BaseModel, EmailStr, field_validator
class CreateUserRequest(BaseModel):
email: EmailStr
name: str
role: str = "user"
@field_validator("name")
@classmethod
def name_not_empty(cls, v: str) -> str:
if not v.strip():
raise ValueError("Name cannot be empty")
return v.strip()
class UserResponse(BaseModel):
id: int
email: str
name: str
role: str
model_config = {"from_attributes": True} # allow ORM model input
# src/users/router.py
from fastapi import APIRouter, Depends, HTTPException, status
from .schemas import CreateUserRequest, UserResponse
from .service import create_user, get_user_by_id
from ..core.security import get_current_user
router = APIRouter(prefix="/users", tags=["users"])
@router.post("/", response_model=UserResponse, status_code=status.HTTP_201_CREATED)
async def create_user_route(
body: CreateUserRequest,
current_user=Depends(get_current_user),
) -> UserResponse:
return await create_user(body)
@router.get("/{user_id}", response_model=UserResponse)
async def get_user_route(
user_id: int,
current_user=Depends(get_current_user),
) -> UserResponse:
user = await get_user_by_id(user_id, requester_id=current_user.id)
if not user:
raise HTTPException(status_code=404, detail="User not found")
return user
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 · 182 lines · 51 tokens per session scan A 1c733b7d25fe
pn-python-scaffolding is a skill published in the GitHub repository perniemann/pnCore (0 stars, last pushed yesterday), licensed MIT. It adds 51 tokens to every session and 1,253 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
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