new-module — for Claude Code new-module, helmlog, community, for Claude Code, ide skills, $ARGUMENTS, storage, conftest.py, Module, ARGUMENTS

v1.0.0
GitHub

Acerca de este Skill

Perfecto para agentes de análisis de Python que necesitan capacidades de registro y prueba robustas para módulos aislados por hardware. Resumen localizado: Scaffold a new hardware-isolated module with tests and wiring # New Module: $ARGUMENTS Follow this checklist to create a new hardware-isolated module. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Características

New Module: $ARGUMENTS
Follow this checklist to create a new hardware-isolated module. Use TDD (/tdd)
for each step that involves code.
Create tests/test $ARGUMENTS.py with tests for the module's public API.
Use the storage fixture from conftest.py and mock any external I/O.

# Core Topics

for Claude Code $ARGUMENTS storage conftest.py Module ARGUMENTS
weaties weaties
[1]
[1]
Updated: 3/18/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 8/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
8/11
Quality Score
24
Canonical Locale
en
Detected Body Locale
en

Perfecto para agentes de análisis de Python que necesitan capacidades de registro y prueba robustas para módulos aislados por hardware. Resumen localizado: Scaffold a new hardware-isolated module with tests and wiring # New Module: $ARGUMENTS Follow this checklist to create a new hardware-isolated module. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

¿Por qué usar esta habilidad?

Habilita a los agentes a crear módulos de registro aislados utilizando TDD y Python, proporcionando un proceso de desarrollo robusto con operaciones de E/S externas aisladas, utilizando protocolos como HTTP, serie y USB, y aprovechando el fixture de almacenamiento de conftest.py para pruebas

Mejor para

Perfecto para agentes de análisis de Python que necesitan capacidades de registro y prueba robustas para módulos aislados por hardware.

↓ Casos de uso accionables for new-module

Crear aplicaciones de registro para instrumentos B y G en Raspberry Pi
Aislar operaciones de E/S externas para desarrolladores
Implementar el desarrollo impulsado por pruebas para la creación robusta de módulos

! Seguridad y limitaciones

  • Requiere entorno de Python y Raspberry Pi
  • Limitado a módulos aislados por hardware
  • Se requiere implementación de TDD para cada paso que involucre código

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Install Path

Start With Installation And Validation

If this skill is worth continuing with, the next step is to confirm the install command, CLI write path, and environment validation.
Trusted Recheck

Cross-Check Against Trusted Picks

If you are still comparing multiple skills or vendors, go back to the trusted collection before amplifying repository noise.
Workflow

Move To Workflow Collections For Team Rollout

When the goal shifts from a single skill to team workflows, approvals, and repeatable execution, move into workflow collections.
Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is new-module?

Perfecto para agentes de análisis de Python que necesitan capacidades de registro y prueba robustas para módulos aislados por hardware. Resumen localizado: Scaffold a new hardware-isolated module with tests and wiring # New Module: $ARGUMENTS Follow this checklist to create a new hardware-isolated module. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

How do I install new-module?

Run the command: npx killer-skills add weaties/helmlog/new-module. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for new-module?

Key use cases include: Crear aplicaciones de registro para instrumentos B y G en Raspberry Pi, Aislar operaciones de E/S externas para desarrolladores, Implementar el desarrollo impulsado por pruebas para la creación robusta de módulos.

Which IDEs are compatible with new-module?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for new-module?

Requiere entorno de Python y Raspberry Pi. Limitado a módulos aislados por hardware. Se requiere implementación de TDD para cada paso que involucre código.

↓ How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add weaties/helmlog/new-module. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use new-module immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

new-module

Install new-module, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

New Module: $ARGUMENTS

Follow this checklist to create a new hardware-isolated module. Use TDD (/tdd) for each step that involves code.

Checklist

1. Write tests first

Create tests/test_$ARGUMENTS.py with tests for the module's public API. Use the storage fixture from conftest.py and mock any external I/O.

2. Create the module

Create src/logger/$ARGUMENTS.py:

  • Single-purpose, under ~200 lines
  • All external I/O (HTTP, serial, USB, etc.) isolated in this module
  • Use dataclasses for structured data
  • Use loguru for logging (never print())
  • Full type annotations on all functions

3. Schema migration (if needed)

If the module needs database tables:

  • Bump _CURRENT_VERSION in storage.py
  • Add migration SQL to _MIGRATIONS dict
  • Add async storage methods (CRUD)
  • Test with the in-memory storage fixture

4. Web routes (if needed)

If the module needs API endpoints or admin UI:

  • Add to web.py following existing patterns
  • Admin pages: require require_auth("admin")
  • Add nav link in _nav_html()
  • Add web route tests in test_web.py

5. Wire into main.py

  • Import the module only in main.py (hardware isolation principle)
  • Parse config from env vars
  • Pass to _web_loop() / create_app() if needed
  • Add CLI subcommand if applicable

6. Sync dependencies

If the module requires new packages:

  • Add with uv add <package> (never edit pyproject.toml manually for deps)
  • Run uv sync and verify the import works
  • Never use uv pip install — it bypasses the lockfile and won't persist

7. Update config

  • Add new env vars to .env.example with comments
  • Update CLAUDE.md project structure tree

8. Run /pr-checklist

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