project-setup

project-setup is a skill for OpenCode from meaningfy-ws/skillery. It costs 226 tokens per session (3,514 once invoked), scanned A, original, GPL-3.0.

A project setup tool for creating or modernising a Python repository with a defined package layout, automated checks, and tests. TDD means writing tests as part of the development process, while BDD structures tests around expected user behaviour.

In plain words
What is it for?
Use it to start a new repository, bring an existing one up to the Meaningfy standard, configure Poetry and code-quality tools, and add TDD, BDD, and import-boundary checks.
Why use it?
It provides a consistent project structure and checks that the code follows its intended layers. It also sets up instructions and tests for both developers and coding agents.

Skill for OpenCode

Written for OpenCode: installed under .opencode/.

Good fit Use it to start a new repository, bring an existing one up…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/meaningfy-ws/skillery/project-setup
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 meaningfy-ws/skillery --skill project-setup
Clone the repo
git clone --depth 1 https://github.com/meaningfy-ws/skillery

Made for: OpenCode.

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 project-setup

README.md
[![agentmods](https://agentmods.dev/badge/skills/meaningfy-ws/skillery/project-setup.svg)](https://agentmods.dev/skills/meaningfy-ws/skillery/project-setup)
Your own site
<a href="https://agentmods.dev/skills/meaningfy-ws/skillery/project-setup"><img src="https://agentmods.dev/badge/skills/meaningfy-ws/skillery/project-setup.svg" alt="Measured on agentmods" height="20"></a>
Per session 226 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,514 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 $0.00226 $0.03514
Opus 5 $0.00113 $0.01757
Sonnet 5 $0.00045 $0.00703
Haiku 4.5 $0.00023 $0.00351

Measured 6d ago against content hash f5c0cddd2a66, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

project-setup 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.

The scan reads SKILL.md. This mod also ships 4 executable files (assets/templates/infra/scripts/entrypoint.sh, assets/templates/tests/conftest.py, assets/templates/tests/feature/test_example.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.opencode/skills/project-setup/SKILL.md · 178 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

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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 · 178 lines · 226 tokens per session scan A f5c0cddd2a66

Subscribe to this mod's changes

project-setup is a skill published in the GitHub repository meaningfy-ws/skillery (2 stars, last pushed 1mo ago), licensed GPL-3.0. It adds 226 tokens to every session and 3,514 once invoked, about $0.0011 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.

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