python-project-structure

python-project-structure is a skill for Claude Code from NorkzYT/claude-code-autopilot. It costs 39 tokens per session (1,503 once invoked), scanned A, original, GPL-3.0.

A guide to organizing Python projects, including module architecture, directory layouts, and the public functions or classes a package exposes.

In plain words
What is it for?
Use it when starting a Python project, rearranging modules, designing package interfaces, or planning directories.
Why use it?
It helps keep a Python codebase understandable as it grows and makes its intended interfaces clear.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Good fit Use it when starting a Python project, rearranging modules, designing package interfaces, or planning directories.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/norkzyt/claude-code-autopilot/python-project-structure
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.

Any agent
npx skills add NorkzYT/claude-code-autopilot --skill python-project-structure
Clone the repo
git clone --depth 1 https://github.com/NorkzYT/claude-code-autopilot

Made for: Claude Code.

Wrote 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.

agentmods badge for python-project-structure

README.md
[![agentmods](https://agentmods.dev/badge/skills/norkzyt/claude-code-autopilot/python-project-structure/github.svg)](https://agentmods.dev/skills/norkzyt/claude-code-autopilot/python-project-structure)
Your own site
<a href="https://agentmods.dev/skills/norkzyt/claude-code-autopilot/python-project-structure"><img src="https://agentmods.dev/badge/skills/norkzyt/claude-code-autopilot/python-project-structure/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.

agentmods 80×15 button for python-project-structure

Your own site · 80×15
<a href="https://agentmods.dev/skills/norkzyt/claude-code-autopilot/python-project-structure"><img src="https://agentmods.dev/badge/skills/norkzyt/claude-code-autopilot/python-project-structure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,503 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown 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 5.1 $0.00039 $0.01503
Opus 5 $0.00019 $0.00751
Sonnet 5 $0.00008 $0.00301
Haiku 4.5 $0.00004 $0.00150

Measured 6d ago against content hash c53696fb8d90, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

python-project-structure 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 6d 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.

.claude/skills/python-project-structure/SKILL.md · 253 lines

The source is not reproduced here

Licensed GPL-3.0

The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

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. 6d ago First seen · 253 lines · 39 tokens per session scan A c53696fb8d90

Subscribe to this mod's changes

python-project-structure is a skill published in the GitHub repository NorkzYT/claude-code-autopilot (2 stars, last pushed 2mo ago), licensed GPL-3.0. It adds 39 tokens to every session and 1,503 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 2026-09-03.

Related

Other skills, from other repositories

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

pennylane

Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with…

K-Dense-AI/scientific-agent-skills · 98 tokens

dd-code-generation

Use pup CLI for immediate Datadog operations or generate code for integration into applications.

DataDog/pup · 16 tokens

rocm-kernels

Provides guidance for writing and benchmarking optimized Triton kernels for AMD GPUs (MI355X, R9700) on ROCm, targeting HuggingFace diffusers (LTX-Video, SD3, FLUX) and transformers. Core kernels: RMSNorm, RoPE 3D, GEGLU, AdaLN. Includes XCD swizzle, autotune, diffusers integration patterns, and LTX-Video pipeline…

huggingface/kernels · 93 tokens

holoscan-install-wheel

Install Holoscan SDK Python wheel via pip into a venv. Use for Python installs; not for native C++/apt or Conda installs.

NVIDIA/skills · 37 tokens

typing-exclusion-worker

Python typing exclusion worker: remove assigned mypy exclusion modules in small scoped batches, fix typing issues, run validation, and produce a structured completion summary. Use when running parallel typing-debt workers or when asked to remove modules from pyproject mypy exclusion overrides.

getsentry/skills · 57 tokens