Mmcp.market

modular-code skill

by parcadei·parcadei/Continuous-Claude-v3·3.9k stars·MIT

Modular Code Organization

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Clean: nothing in its files matched our rules. We read 1 file in the folder on 2026-09-28.

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Install the modular-code skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.

git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3.git /tmp/Continuous-Claude-v3
mkdir -p ~/.claude/skills
cp -r /tmp/Continuous-Claude-v3/.claude/skills/modular-code ~/.claude/skills/modular-code
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

Modular Code Organization

Write modular Python code with files sized for maintainability and AI-assisted development.

File Size Guidelines

When to Split

Split when ANY of these apply:

  • File exceeds 500 lines
  • Multiple unrelated concerns in same file
  • Scroll fatigue finding functions
  • Tests for the file are hard to organize
  • AI tools truncate or miss context

How to Split

Natural Split Points

  1. By domain concept: auth.py → auth/login.py, auth/tokens.py, auth/permissions.py
  2. By abstraction layer: Separate interface from implementation
  3. By data type: Group operations on related data structures
  4. By I/O boundary: Isolate database, API, file operations

Package Structure

feature/
├── __init__.py      # Keep minimal, just exports
├── core.py          # Main logic (under 500 lines)
├── models.py        # Data structures
├── handlers.py      # I/O and side effects
└── utils.py         # Pure helper functions

DO

  • Use meaningful module names (data_storage.py not utils2.py)
  • Keep init.py files minimal or empty
  • Group related functions together
  • Isolate pure functions from side effects
  • Use snake_case for module names

DON'T

  • Split files arbitrarily by line count alone
  • Create single-function modules
  • Over-modularize into "package hell"
  • Use dots or special characters in module names
  • Hide dependencies with "magic" imports

Refactoring Large Files

When splitting an existing large file:

  1. Identify clusters: Find groups of related functions
  2. Extract incrementally: Move one cluster at a time
  3. Update imports: Fix all import statements
  4. Run tests: Verify nothing broke after each move
  5. Document: Update any references to old locations

Current Codebase Candidates

Files over 2000 lines that need attention:

  • Math compute modules (scipy, mpmath, numpy) - domain-specific, may be acceptable
  • patterns.py - consider splitting by pattern type
  • memory_backfill.py - consider splitting by operation type

Sources

  • The Hitchhiker's Guide to Python
  • Python Project Best Practices - Dagster
  • Right-Sizing Python Files for AI Editors
  • PEP 8 Style Guide

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