output-quality

name	output-quality
description	Detect and eliminate generic, low-quality "AI slop" patterns in natural language, code, and design. Use when REVIEWING existing content (text, code, or visual designs) for quality issues, cleaning up generic patterns, or establishing quality standards. Focuses on pattern detection—not content creation.

Output Quality

Identify and remove telltale patterns that signal low-quality, generic content across text, code, and design.

What is "Slop"?

"Output slop" refers to predictable patterns that signal generic, low-effort AI-generated content:

Text slop: Overused phrases ("delve into," "navigate the complexities"), excessive buzzwords, meta-commentary ("In this article, we will discuss..."), vague hedging

Code slop: Generic variable names (data, result, temp), obvious comments that restate code, unnecessary abstraction layers, over-engineered solutions

Design slop: Cookie-cutter layouts, generic gradient backgrounds, overused visual patterns, vague marketing copy ("Empower Your Business")

When to Use This Skill

Apply output-quality techniques when:

• Reviewing AI-generated content before delivery
• Creating original content and want to avoid generic patterns
• Cleaning up existing content that feels generic or low-effort
• Establishing quality standards for a project or team
• Content has telltale signs of lazy, templated generation

Core Workflow

1. Detect Slop

For text files:

Read the appropriate reference guide for detailed patterns:

• text-patterns.md — Natural language slop patterns
• code-patterns.md — Programming slop patterns
• design-patterns.md — Visual/UX design slop patterns

2. Clean Slop

Manual cleanup (recommended): Apply strategies from the reference files based on detected patterns.

Text-specific automated tools (optional): Python scripts in references can help analyze and suggest cleanup:

• See python-detection.md for setup and usage

Text Quality Principles

Be Direct

• Skip preambles and meta-commentary
• Lead with the actual point
• Cut transition words that don't add meaning
• Remove "In this article, we will..." throat-clearing

Be Specific

• Replace generic terms with concrete examples
• Name specific things instead of "items," "things," "data"
• Use precise verbs instead of vague action words
• Avoid lazy extremes ("every," "always," "never") doing vague work

Be Authentic

• Vary sentence structure and length
• Use active voice predominantly
• Write in a voice appropriate to context, not corporate-generic
• Trust readers to understand without hand-holding

Code Quality Principles

Meaningful Names

• Variables should describe their content, not their type
• Function names should describe action + object
• Avoid single-letter names or temp, data, result, item

Appropriate Documentation

• Document why, not what (code should be self-evident)
• Skip documentation for obvious code
• Focus documentation on public APIs and complex logic
• Don't restate what the code does

Simplicity Over Cleverness

• Write code that's easy to understand
• Optimize only when profiling shows need
• Prefer simple solutions to complex ones
• Avoid unnecessary abstraction layers

Design Quality Principles

Content-First Design

• Design around actual content needs
• Create hierarchy based on importance, not templates
• Let content determine layout, not vice versa

Intentional Choices

• Every design decision should be justifiable
• Use patterns because they serve users, not because they're trendy
• Vary visual treatment based on element importance

Authentic Voice

• Copy should reflect brand personality
• Avoid generic marketing speak
• Be specific about value proposition

Common High-Priority Targets

Text:

• "delve into" → delete or replace with "examine"
• "navigate the complexities" → "handle" or delete
• "in today's fast-paced world" → delete entirely
• Meta-commentary and preambles → cut to the point

Code:

• Generic names: data → name what data it represents
• Obvious comments: // Create a user before user = User() → delete
• Over-engineering: Unnecessary design patterns, multiple abstraction layers
• One-off utilities: Extract only when genuinely reused

Design:

• Purple/pink/cyan gradient backgrounds → use intentional color palette
• Floating 3D shapes without purpose → remove
• "Empower Your Business" type headlines → be specific about value
• Generic layouts → design for actual content

Integration with Code-Deduplication and Coding-Discipline

These three skills work together:

• output-quality catches style and pattern smells in finished code
• code-deduplication prevents reimplementation of existing logic
• coding-discipline guides the writing process to avoid overcomplication from the start

Use output-quality for cleanup and review; use the other two to prevent problems from the start.

Examples

For detailed before/after examples in text, code, and design, see examples.md.