Architect skills as modular blocks to control token usage and complexity. Triggers: skills, architecture, modular, design-patterns, modularity, skill design, skill architecture, modularization, token optimization, skill structure, refactoring skills, new skill creation, skill complexity. Use when creating skills >150 lines, breaking down monolithic skills, or planning new architecture. Do not use for evaluating existing skills (use skills-eval) or writing human-facing prose (use writing-clearly-and-concisely). Check this skill before starting any new skill development.
View on GitHubplugins/abstract/skills/modular-skills/SKILL.md
February 1, 2026
Select agents to install to:
npx add-skill https://github.com/athola/claude-night-market/blob/main/plugins/abstract/skills/modular-skills/SKILL.md -a claude-code --skill modular-skillsInstallation paths:
.claude/skills/modular-skills/## Table of Contents - [Overview](#overview) - [Quick Start](#quick-start) - [Workflow and Tasks](#workflow-and-tasks) - [Quality Checks](#quality-checks) - [Resources](#resources) # Modular Skills Design ## Overview This framework breaks complex skills into focused modules to keep token usage predictable and avoid monolithic files. We use progressive disclosure: starting with essentials and loading deeper technical details via `@include` or `Load:` statements only when needed. This approach prevents hitting context limits during long-running tasks. Modular design keeps file sizes within recommended limits, typically under 150 lines. Shallow dependencies and clear boundaries simplify testing and maintenance. The hub-and-spoke model allows the project to grow without bloating primary skill files, making focused modules easier to verify in isolation and faster to parse. ### Core Components Three tools support modular skill development: - `skill-analyzer`: Checks complexity and suggests where to split code. - `token-estimator`: Forecasts usage and suggests optimizations. - `module_validator`: Verifies that structure complies with project standards. ### Design Principles We design skills around single responsibility and loose coupling. Each module focuses on one task, minimizing dependencies to keep the architecture cohesive. Clear boundaries and well-defined interfaces prevent changes in one module from breaking others. This follows Anthropic's Agent Skills best practices: provide a high-level overview first, then surface details as needed to maintain context efficiency. ## Quick Start ### Skill Analysis Analyze modularity using `scripts/analyze.py`. You can set a custom threshold for line counts to identify files that need splitting. ```bash python scripts/analyze.py --threshold 100 ``` From Python, use `analyze_skill` from `abstract.skill_tools`. ### Token Usage Planning Estimate token consumption to verify your skill stays within budget. Run this from t