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 userbeforeuser = 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.