What AI Writing Patterns No AI Slop Cuts: The Complete 25-Pattern Library

No AI Slop identifies and removes over 20 specific AI writing patterns—including filler transitions like "Firstly," vague hedging such as "It is important to note," passive-voice dominance, and generic openers like "In today's world"—through two operational modes: detect (audit-only) and edit (auto-apply).

The petergyang/no-ai-slop repository provides a Codex-compatible skill designed to strip machine-generated prose of its most telltale signatures. According to the README.md at line 59, this tool checks for more than 20 distinct patterns that make AI-assisted writing sound generic, while the plugin-submission.md at line 5 clarifies the goal as removing these patterns "without flattening the writer’s voice."

The 25 AI Writing Patterns No AI Slop Eliminates

The skill targets specific rhetorical and syntactic markers that signal machine authorship. Below are the categories of patterns detected according to the source documentation.

Structural Transitions and Connectors

Over-use of filler transitions represents one of the most flagged categories. The skill catches robotic sequencing terms like "Firstly," "Secondly," "In conclusion," and "Overall" that make text feel scripted rather than naturally flowing.

Repetitive connective words are flagged when conjunctions like "and," "but," or "so" appear back-to-back, breaking rhythmic cadence. Similarly, repeated rhetorical questions such as "Do you ever wonder…?" used multiple times trigger detection as gimmicky constructions.

Redundant summarising sentences—such as "To sum up, …" when the paragraph already concludes—are identified as unnecessary fluff that adds length without content.

Hedging and Non-Committal Language

Vague phrasing like "It is important to note…" or "One could argue…" reduces clarity and authority, while excessive hedging through words like "Maybe," "Possibly," or unnecessary "I think" statements dilutes the writer’s confidence.

The skill also targets "In my opinion" without personal insight and excessive use of "I think" or "I believe" without supporting arguments, both of which signal the uncertainty typical of AI drafts.

Generic and Impersonal Constructions

Generic openers such as "As we all know…" or "In today's world…" immediately signal boiler-plate content. The system flags lack of personal anecdotes or concrete examples when it encounters generic abstractions without real-world detail that makes prose feel detached.

Over-use of "you" in generic advice—phrases like "You should…" without audience specificity—triggers detection as mass-produced copy. Additionally, repeated use of "This" as a subject (e.g., "This leads to… This shows…") makes prose feel mechanical rather than human-centered.

Stylistic Redundancies and Weak Modifiers

The skill aggressively targets redundant qualifiers including "basically," "actually," and "just," alongside unnecessary qualifiers like "quite," "somewhat," and "rather." Excessive use of "very" in constructions like "very important" or "very effective" is flagged for weakening impact.

Non-specific quantifiers such as "many," "some," or "a few" without concrete numbers leave statements vague and are marked for revision. Superfluous prepositional phrases like "in order to" or "with respect to" are identified as adding length without semantic content.

Syntactic and Voice Patterns

Passive-voice dominance in phrases like "It was decided that…" or "The results were analyzed…" weakens engagement and directness. The skill flags convoluted phrasing containing overly complex clauses that could be simplified for readability.

Over-formal language such as "Henceforth," "Thus," or "Therefore" in informal contexts creates a robotic tone. Similarly, repetitive sentence structures across paragraphs cause monotony that hides the writer’s unique voice.

Lexical and Industry Markers

Cliché buzzwords including "Leverage," "Synergy," and "Cutting-edge"—common in AI-generated marketing copy—are highlighted. Unnecessary technical jargon such as "utilize," "implement," or "facilitate" where simpler terms suffice increases perceived AI-ness.

The skill also detects over-use of adjectives/adverbs ("very important," "extremely useful") that add fluff rather than meaning, and common AI-detector clues like overly balanced sentiment or perfectly neutral tone that give away AI-authorship.

How Detection and Edit Modes Work

The skills/no-ai-slop/SKILL.md defines two operational modes. In detect mode, the skill audits drafts without rewriting, quoting each offending line and suggesting a concise fix. In edit mode, it automatically applies minimal effective changes.

Detect Mode Example

# Detect mode – ask the skill to audit a draft without rewriting

- name: No AI Slop – Detect
  skill: no-ai-slop
  mode: detect
  input: |
    In today’s world, it is important to note that many people think that...
    Firstly, we should consider the benefits...
    Overall, the results were quite significant.

Output excerpt:

Pattern: “Firstly, …”
Quote: “Firstly, we should consider the benefits…”
Fix: Replace with a more natural transition (e.g., “One key benefit is…”)

Pattern: “In today’s world, it is important to note…”
Quote: “In today’s world, it is important to note that many people think that…”
Fix: Remove generic intro; start with the concrete point.

Edit Mode Example

# Edit mode – automatically apply the minimal edits

- name: No AI Slop – Edit
  skill: no-ai-slop
  mode: edit
  input: |
    In today’s world, it is important to note that many people think that...
    Firstly, we should consider the benefits...
    Overall, the results were quite significant.

Output excerpt:

Edited draft:
Many people think that...
One key benefit is...
The results were significant.

Repository Structure and Implementation Files

The pattern-detection logic relies on specific configuration and build files within the repository:

• README.md (line 59): Outlines the purpose and the "20+ patterns" feature set.
• plugin-submission.md (line 5): Describes the pattern-removal goal and version updates.
• skills/no-ai-slop/SKILL.md: Contains the detailed skill specification, including detect versus edit modes and pattern-audit guidelines.
• skills/no-ai-slop/agents/openai.yaml: Configures the OpenAI model parameters used for pattern recognition.
• scripts/build_plugin.py: Handles the Codex plugin build process, packaging the pattern-detection logic for deployment.

Summary

• No AI Slop targets over 20 specific AI writing patterns ranging from filler transitions to passive-voice dominance.
• The skill preserves the writer’s genuine voice by offering detect mode (flagging only) and edit mode (minimal auto-revision).
• Key patterns include generic openers ("In today's world"), hedging language ("It is important to note"), and mechanical transitions ("Firstly," "Overall").
• Implementation relies on YAML configurations in skills/no-ai-slop/ and build scripts in scripts/.

Frequently Asked Questions

How many AI writing patterns does No AI Slop actually check for?

According to the README.md at line 59 and the plugin-submission.md at line 5, the skill checks for more than 20 patterns. The documentation enumerates approximately 25 distinct categories covering structural, syntactic, lexical, and tonal markers.

Does No AI Slop automatically rewrite my content?

It depends on the mode. In detect mode, the skill only flags offending lines and suggests fixes without modifying your text. In edit mode, it applies minimal effective changes automatically, removing the AI-slop patterns while preserving your original voice and intent.

What is the difference between "filler transitions" and "redundant qualifiers"?

Filler transitions are structural markers like "Firstly" or "In conclusion" that sequence ideas mechanically. Redundant qualifiers are unnecessary adverbs like "basically," "actually," or "just" that clutter sentences without adding meaning. Both are flagged, but filler transitions affect document structure while redundant qualifiers affect sentence-level concision.

Can No AI Slop handle technical or academic writing?

Yes. The skill specifically targets unnecessary technical jargon (such as "utilize" where "use" suffices) and over-formal language like "Henceforth" in informal contexts. For legitimate technical precision, the detection algorithms distinguish between required terminology and superfluous Latinate constructions that increase perceived AI-ness.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}