scaffold-python

A set of instructions for creating or standardizing a Python project with common development, testing, and release files.

In plain words
What is it for?
Use it when starting a Python CLI, library, or application, or when adding CI/CD and shared project conventions to an existing Python project.
Why use it?
It removes the need to assemble project structure, code checks, continuous integration, and release setup from scratch.

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/urmzd/dotfiles/scaffold-python
Any agent
npx skills add urmzd/dotfiles --skill scaffold-python
Clone the repo
git clone --depth 1 https://github.com/urmzd/dotfiles

Made for: Claude Code, Codex.

Per session 135 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,712 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 $0.00135 $0.01712
Opus 5 $0.00068 $0.00856
Sonnet 5 $0.00027 $0.00342
Haiku 4.5 $0.00014 $0.00171

Measured yesterday against content hash d3963a5368c9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

scaffold-python 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 yesterday.

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.

dot_agents/skills/scaffold-python/SKILL.md · 269 lines

How it starts

The opening of the file, as written. The whole thing — 269 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Scaffold Python Project

Generate a production-ready Python project following established CI/CD patterns. Read the scaffold-project skill first for standard files (README, AGENTS.md, LICENSE, CONTRIBUTING.md, llms.txt).

When to Use

  • Creating a new Python CLI, library, or application
  • Adding CI/CD to an existing Python project missing workflows
  • Standardizing a Python project to match org conventions

Generated Files

.github/workflows/ci.yml

name: CI

on:
  pull_request:
    branches: [main]
  workflow_call:

permissions:
  contents: read

concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true

jobs:
  lint:
    name: Lint
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: astral-sh/setup-uv@v5
      - run: uv python install
      - run: uv sync --group dev
      - name: Check formatting
        run: uv run ruff format --check .
      - name: Run linter
        run: uv run ruff check .

  test:
    name: Test
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: astral-sh/setup-uv@v5
      - run: uv python install
      - run: uv sync --group dev
      - name: Run tests
        run: uv run pytest

.github/workflows/release.yml

name: Release

on:
  push:
    branches: [main]
  workflow_dispatch:

concurrency:
  group: release
  cancel-in-progress: false

permissions:
  contents: write

jobs:
  ci:
    if: github.actor != 'sr[bot]'
    uses: ./.github/workflows/ci.yml

  release:
    needs: ci
    runs-on: ubuntu-latest
    steps:
      - name: Generate app token
        id: app-token
        uses: actions/create-github-app-token@v1
        with:
          app-id: ${{ secrets.SR_RELEASER_APP_ID }}
          private-key: ${{ secrets.SR_RELEASER_PRIVATE_KEY }}
          repositories: ${{ github.event.repository.name }}

      - uses: actions/checkout@v4
        with:
          fetch-depth: 0
          token: ${{ steps.app-token.outputs.token }}

      - uses: urmzd/sr@v8
        id: sr
        with:
          github-token: ${{ steps.app-token.outputs.token }}

    outputs:
      released: ${{ steps.sr.outputs.released }}
      tag: ${{ steps.sr.outputs.tag }}
      version: ${{ steps.sr.outputs.version }}

Read the full file on GitHub · 269 lines

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. yesterday First seen · 269 lines · 135 tokens per session scan A d3963a5368c9

Subscribe to this mod's changes

scaffold-python is a skill published in the GitHub repository urmzd/dotfiles (3 stars, last pushed 19d ago), licensed Apache-2.0. It adds 135 tokens to every session and 1,712 once invoked, about $0.0007 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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