modular-code
Modular Code Organization
Install
npx skills add https://github.com/parcadei/continuous-claude-v3 --skill modular-codeSKILL.md
Modular Code Organization
Write modular Python code with files sized for maintainability and AI-assisted development.
File Size Guidelines
| Lines | Status | Action |
|---|---|---|
| 150-500 | Optimal | Sweet spot for AI code editors and human comprehension |
| 500-1000 | Large | Look for natural split points |
| 1000-2000 | Too large | Refactor into focused modules |
| 2000+ | Critical | Must split - causes tooling issues and cognitive overload |
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
- By domain concept:
auth.py→auth/login.py,auth/tokens.py,auth/permissions.py - By abstraction layer: Separate interface from implementation
- By data type: Group operations on related data structures
- 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.pynotutils2.py) - Keep
__init__.pyfiles 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:
- Identify clusters: Find groups of related functions
- Extract incrementally: Move one cluster at a time
- Update imports: Fix all import statements
- Run tests: Verify nothing broke after each move
- 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
Related skills
improve-codebase-architecturemattpocock1MScan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.codebase-designmattpocock691KShared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.web-design-guidelinesvercel-labs676KReview UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices".code-reviewmattpocock631KReview the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to \"review since X\".
