Writing Standards Content Quality — Knowledge Module

Writing Quality

A writing quality gate that detects and eliminates AI-generated writing patterns. Merges 29 detection patterns from humanizer with 5-dimension scoring from stop-slop. Use this module as the final quality check before publishing any content.

See ATTRIBUTION.md for licensing details.

Two-Pass Audit Process

Pass 1: Pattern Detection

Scan the content for AI writing patterns across 6 categories. Each detected pattern is a signal that the text sounds machine-generated.

Category	Patterns	What to look for
Content	1-6	Significance inflation, notability name-dropping, superficial analyses, promotional language, vague attributions, formulaic conclusions
Language	7-13	AI vocabulary overuse, copula avoidance ("serves as" instead of "is"), tailing negations, rule of three, synonym cycling, false ranges, passive voice
Style	14-19, 26-29	Em dash overuse, boldface overuse, inline-header lists, title case, emojis, hyphenated pairs, authority tropes, signposting, fragmented headers
Communication	20-22	Chatbot artifacts ("I hope this helps!"), knowledge-cutoff disclaimers, sycophantic tone
Filler & Hedging	23-25	Filler phrases, excessive hedging, generic positive conclusions
Structural	S1-S6	Binary contrasts, negative listings, dramatic fragmentation, rhetorical setups, false agency, narrator-from-distance

Full pattern catalog with before/after examples: references/banned-patterns.md

Pass 2: Scoring & Verdict

Rate the content 1-10 on five dimensions. The scoring system measures how human the writing sounds, not whether it's "good" writing in general.

Dimension	Measures	7+ (good)	3- (bad)
Directness	Statements vs announcements	Direct assertions, confident claims	Throat-clearing, "here's why this matters"
Rhythm	Sentence length variation	Natural mix of short and long	Every sentence roughly the same length
Trust	Reader respect	States facts, lets reader conclude	Over-explains, hedges, hand-holds
Authenticity	Human voice	Specific, opinionated, some rough edges	Generic, corporate, sanitized
Density	Signal-to-noise	Every word earns its place	Filler phrases, redundant qualifiers

Threshold: 35/50 to pass. Any single dimension below 5 = automatic revision, regardless of total score.

Full rubric with scoring examples: references/scoring.md

Core Rules

These 8 rules from stop-slop are the active editing directives. Apply them when rewriting flagged content:

1. Cut filler phrases — if removing a phrase doesn't change the meaning, remove it. See references/banned-phrases.md.
2. Break formulaic structures — binary contrasts, dramatic fragments, rhetorical striptease. See references/banned-structures.md.
3. Use active voice — every sentence needs a named human subject doing something. "The decision was made" → "Sarah decided."
4. Be specific — replace vague declaratives with concrete details. "The results were significant" → "Output increased 2.4x."
5. Put the reader in the room — "you" beats "people", "users", "one." Second person creates immediacy.
6. Vary rhythm — mix sentence lengths. Two items in a list beat three. No em dashes (use commas or periods instead).
7. Trust readers — state facts directly. Skip softening ("it's worth noting that"), hedging ("arguably"), and meta-commentary ("let me explain").
8. Cut quotables — if a sentence sounds like a pull-quote or inspirational poster, rewrite it. Real writing doesn't pose.

Quick Checks

A 12-item pre-delivery checklist. Run mentally before submitting any content:

1. Any adverbs (-ly words)? Cut them or replace with stronger verbs.
2. Any passive voice? Name the actor.
3. Any false agency? (Objects doing human things: "the data tells us", "the market rewards")
4. Any paragraphs starting with Wh- words? (What, When, Where, Which, Who, Why, How) Restructure.
5. Any throat-clearing openers? ("Here's the thing:", "Let me be clear:") Delete.
6. Any binary contrasts? ("Not X. But Y.") Rewrite as a direct statement.
7. All sentences roughly the same length? Vary them.
8. Every paragraph ending punchily? That's a pattern — vary endings too.
9. Any em dashes? Replace with commas, periods, or parentheses.
10. Any vague declaratives? ("The implications are significant.") Replace with specifics.
11. Any narrator-from-distance? ("Nobody designed this.", "This happens because...") Name actors.
12. Any meta-joiners? ("And that's okay.", "Here's what I mean:", "Think about it:") Cut.

Voice Calibration

When rewriting content to remove AI patterns, don't strip all personality. Good human writing has:

• Opinions — take a stance, don't hedge everything
• Varied rhythm — mix short punchy sentences with longer flowing ones
• Specificity — concrete details, not abstract claims
• First person (when appropriate) — "I" and "we" are fine in blog posts and social
• Imperfection — not every transition needs to be smooth. Some mess is human.
• Tension — good writing creates and resolves small tensions. Don't flatten everything.

If a brand context is available, calibrate voice to match its tone and personality. The goal is to sound like a specific human writer, not a generic one.

Common Tasks

1. Full quality check — run both passes (pattern detection + scoring), return findings and verdict
2. Quick scan — pattern detection only, no scoring. For fast feedback during drafting.
3. Targeted revision — fix specific pattern categories (e.g., "fix only filler and structural patterns")
4. Score only — skip pattern detection, just rate on 5 dimensions. For content that's already been through pattern cleanup.
5. Voice calibration — analyze a writing sample and extract style fingerprint. Use when adapting content to a specific brand voice.

Tips

• Don't just remove bad patterns — inject personality. Copy that's merely "not AI-sounding" is still bland.
• Two items in a list always beat three. The rule of three is one of the strongest AI tells.
• Read the content aloud (mentally). If it sounds like a keynote speech, it's too polished.
• After cleaning up AI patterns, re-read the whole piece. Sometimes cleanup strips voice. Add it back.
• Some patterns are occasionally correct in context. An em dash can be fine in informal writing. A list of three can work if the items are genuinely distinct. Use judgment.

Gotchas

• Voice calibration can over-correct, making copy bland and lifeless. Always re-read after cleanup.
• The blanket adverb ban (rule 1) is aggressive. "Quickly" is usually cuttable, but "previously" is sometimes necessary. Apply with judgment.
• False agency (S4) is one of the strongest AI tells but also one of the hardest to fix without restructuring sentences significantly.
• Narrator-from-distance (S5) detection can false-positive on legitimate explanatory writing. Context matters.
• The 35/50 threshold is calibrated for marketing copy. Technical documentation may legitimately score lower on Rhythm and Authenticity dimensions without being "AI-sounding."

References

• references/banned-patterns.md — full 29-pattern catalog with detection signals, before/after examples, and fix guidance
• references/banned-phrases.md — categorized phrase lists: throat-clearing, emphasis crutches, jargon, adverbs, meta-commentary
• references/banned-structures.md — structural anti-patterns: binary contrasts, false agency, dramatic fragmentation
• references/scoring.md — 5-dimension rubric with detailed 1-10 descriptors and scoring examples