Night Market Skill — ported from claude-night-market/abstract. For the full experience with agents, hooks, and commands, install the Claude Code plugin.

Table of Contents#

• Overview
• Quick Start
• Workflow and Tasks
• Quality Checks
• 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.

Module Ownership (IMPORTANT)#

Deprecated: skills/shared/modules/ directories. This pattern caused orphaned references when shared modules were updated or removed.

Current pattern: Each skill owns its modules at skills/<skill-name>/modules/. When multiple skills need the same content, the primary owner holds the module and others reference it via relative path (e.g., ../skill-authoring/modules/anti-rationalization.md). The validator flags any remaining skills/shared/ directories.

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 the skill directory:

bash

python scripts/tokens.py

Module Validation#

Check for structure and pattern compliance before deployment.

bash

python scripts/abstract_validator.py --scan

Workflow and Tasks#

Start by assessing complexity with skill_analyzer.py. If a skill exceeds 150 lines, break it into focused modules following the patterns in ../../docs/examples/modular-skills/. Use token_estimator.py to check efficiency and abstract_validator.py to verify the final structure. This iterative process maintains module maintainability and token efficiency.

Quality Checks#

Identify modules needing attention by checking line counts and missing Table of Contents. Any module over 100 lines requires a TOC after the frontmatter to aid navigation.

bash

# Find modules exceeding 100 lines
find modules -name "*.md" -exec wc -l {} + | awk '$1 > 100'

Standards Compliance#

Our standards prioritize concrete examples and a consistent voice. Always provide actual commands in Quick Start sections instead of abstract descriptions. Use third-person perspective (e.g., "the project", "developers") rather than "you" or "your". Each code example should be followed by a validation command. For discoverability, descriptions must include at least five specific trigger phrases.

TOC Template#

markdown

## Table of Contents

- [Section Name](#section-name)
- [Examples](#examples)
- [Troubleshooting](#troubleshooting)

Resources#

Shared Modules: Cross-Skill Patterns#

Standard patterns for triggers, enforcement language, and anti-rationalization:

• Trigger Patterns: See trigger-patterns.md
• Enforcement Language: See enforcement-language.md
• Anti-Rationalization: See anti-rationalization.md

Skill-Specific Modules#

Detailed guides for implementation and maintenance:

• Enforcement Patterns: See modules/enforcement-patterns.md
• Core Workflow: See modules/core-workflow.md
• Implementation Patterns: See modules/implementation-patterns.md
• Migration Guide: See modules/antipatterns-and-migration.md
• Design Philosophy: See modules/design-philosophy.md
• Troubleshooting: See modules/troubleshooting.md
• Optimization Techniques: See modules/optimization-techniques.md - reducing large skill file sizes through externalization, consolidation, and progressive loading

Tools and Examples#

• Tools: skill_analyzer.py, token_estimator.py, and abstract_validator.py in ../../scripts/.
• Examples: See ../../docs/examples/modular-skills/ for reference implementations.