AI Writing Anti-Patterns

Field guide for detecting and revising AI-generated content indicators based on Wikipedia's "Signs of AI writing" guide.

When to Use

Invoke this skill:

• Before finalizing ANY AI-assisted writing
• When reviewing text for AI writing indicators
• When editing content to sound more natural
• After completing writing tasks (automatic via hooks)

The Iron Law

Check every piece of AI-assisted writing against these patterns before submission.

This is not optional. AI writing patterns are detectable and undermine credibility.

Quick Screening Order

Start with the most objective indicators:

Critical Patterns to Avoid

CRITICAL Severity (Immediate Revision Required)

These patterns are unambiguous AI artifacts:

ChatGPT-Specific Artifacts:

• turn0search0, turn1search2 (internal search references)
• oaicite:X (citation placeholders)
• contentReference[oaicite:X] (unresolved references)
• JSON attribution blocks in output

Prompt Refusals:

• "As an AI language model..."
• "I cannot provide..."
• "I hope this helps!"
• "I hope this email finds you well"

HIGH Severity (Strong Revision Recommended)

Puffery and Exaggeration:

• "stands as" (a testament/example/beacon)
• "plays a vital/crucial/pivotal role"
• "rich tapestry of"
• "nestled in/among"
• "it's important to note that"
• "delves into"
• "the landscape of"

Promotional Language:

• "groundbreaking", "transformative", "revolutionary"
• "unparalleled", "unprecedented"
• "cutting-edge", "state-of-the-art"

MEDIUM Severity (Review and Consider)

Structural Patterns:

• Section summaries that repeat the heading
• "Despite [challenge], [positive outcome]" formula
• Negative parallelisms: "However... Nevertheless..."
• Rule of three: exactly three examples every time
• Weasel wording: "some experts say", "it is believed"

Stylistic Quirks:

• False precision — a summarising figure carried to spurious decimal places

("a rate of 1.3771 percent", "covering 85.63 percent of the universe"). Prefer a high-level fraction in the abstract and introduction, where a figure summarises rather than reports; keep the exact value next to the exhibit that backs it. Enforced as style·false_precision.

• Elegant variation (synonym cycling to avoid repetition)
• False ranges ("from X to Y" without real data)
• Title Case In All Headings
• Em dash overuse (—)
• Excessive boldface for emphasis

User-Voice Preferences (NOT AI tells — corpus-checked 2026-08-05)

This section is a personal style preference, not a linter, and the name it used to carry ("User-Voice Lint") was doing real damage. Nothing here was ever in an executable table, so a writing-verify pass ran every scorer and knew none of these phrases — while the heading implied four enforced rules. Three of the four have now been measured against 14,294,148 sentences of human scholarship (8.73M finance/accounting + 5.56M law review) and they are normal human prose:

Keep these as voice preferences if you like them — they are unfalsifiable and that is fine. Do not present them as AI detection. Full record: docs/investigations/2026-08-05_emphasis-enforcement.md.

What DID survive the gate, and is now enforced as a span:

• ai-tic·sev3·rule-bites — "the reform should bite hardest". The verb is unattested

(1/14.29M, and that hit is a cited Financial Times headline in a footnote). The noun above is not. That noun/verb split is the whole rule.

• ai-tic·sev2·sharpest-version — "the sharpest version of the objection". 0/14.29M, while all

four hits of <superlative> version of are "the strongest version of" and the sharpest <noun> at large is 86 hits. The word is ordinary; the collocation is the tell.

Bridge repetitions remain the one genuinely enforced entry from the old list — skills/writing-verify/scripts/bridgerepetitioncheck.py, invoked from workflows/writing-verify.js. It is real logic over section openings, not a phrase table.

To check a phrase yourself: /ai-tic <phrase> — it runs the FP-hunt against both corpus halves and refuses to add anything over the eligibility gate.

How to Revise

For Puffery

For Structure

For False Precision

A figure in the abstract or introduction is SUMMARISING; a figure beside its table is REPORTING. Only the second earns its decimal places. Carrying four of them into a summary implies a precision the estimate does not have and reads as machine output.

Exceptions the rule already carries, and which must stay exceptions: exact values inside a table, figure caption, code block or footnote; years, statutory and rule cites, docket, page and version numbers; and money where the cents are the point.

For Promotional Language

Reference Files

For detailed patterns and extensive examples, consult:

THE "ENFORCED BY" COLUMN IS THE POINT OF THIS TABLE. Eleven chapters listed as reference material reads as eleven chapters of coverage; it is not. Four of them have no executable module and are marked reference-only here so nobody has to rediscover the gap by shipping a draft through a clean review pass. (That is exactly how chapter 05's boldface entry went unenforced until v5.134.0 — see docs/investigations/2026-08-05_emphasis-enforcement.md.)

Every named system is a scripts/prose-audit.py system, so a finding from it carries a span id. A chapter marked reference only produces no span, which by THE READER'S RULE means anything it surfaces is judgement, not a deterministic finding.

Automatic Detection

This plugin includes PostToolUse hooks that automatically scan Write/Edit output for anti-patterns. When patterns are detected:

1. Hook emits a warning with specific patterns found
2. Claude immediately revises the content
3. Revision removes or replaces flagged patterns

The hook checks for all CRITICAL and HIGH severity patterns automatically.

Review Facts

• A user's style request ("make it punchy", "professional tone") is a request for an outcome, not for AI-smell — delivering it with puffery, hedges, or bold-emphasis patterns intact ships text that reads as obviously AI-generated and damages the user's credibility.
• Skimming is not checking. The check is sentence-by-sentence against the pattern list; a skim that lets puffery pass because flagging it felt pedantic presents unreviewed text as reviewed — an unverified claim.

Key Principles

From Wikipedia's guide:

1. These are signs, not proof - Multiple indicators strengthen the case
2. Context matters - Some patterns appear in human writing too
3. Focus on deeper issues - Surface defects point to synthesis and quality problems
4. Don't rely on detection tools - Human judgment required

Related Skills

• /writing - Core writing principles from Elements of Style
• /writing-legal - Legal writing (Phase 2)
• /writing-econ - Economics writing (Phase 2)