Methodology · Pattern Pressure

Pattern Pressure: what it measures and what it cannot prove.

Detect cliché AI-slop scaffolds, unsupported boosters, repeated em-dash rhythm, and formulaic phrasing pressure without pretending burstiness proves authorship.

Open free tool Trust model

How this works

Plain-English method

Pattern pressure replaces naive burstiness claims with visible lexical markers. It is cheap, explainable, and useful for draft cleanup — not proof that a model wrote the text.

Mechanism and scoring

The score is a deterministic density/weighting pass over phrase dictionaries, boosters, and punctuation rhythm markers. It is intentionally transparent and easy to audit.

Read the full methodology →

What this catches

  • Generic AI-slop phrases
  • Boosters and intensifiers
  • Dense em-dash rhythm
  • Formulaic marketing scaffolds

What this misses

  • AI text that avoids clichés
  • Human marketing copy that uses the same language
  • Truth, source support, or authorship
How it fits the layered approach

This is one signal in a layered stack.

Single-method detectors are too easy to overtrust. Pattern Pressure is useful when it changes routing: allow, revise, human_review, or reject. It should be layered with specificity, provenance, pattern pressure, Unicode sanitation, media provenance, and paid Deep Scan when the decision matters.

check_pattern_pressure is available through local MCP with no LLM cost, and through the remote MCP endpoint with free unauthenticated rate limits. See all detection methodologies and the dedicated methodology page for the deepest treatment of this signal.