AI Writing Anti-Patterns

What this skill carries — grep references/ for any subject the names below miss: !d=${CLAUDE_SKILL_DIR}; command -v skill-toc >/dev/null 2>&1 && exec skill-toc "$d"; s=$HOME/.claude/skills/plugin-utils/bin/skill-toc; [ -x "$s" ] && exec "$s" "$d"; echo "(skill-toc unavailable: references and scripts are NOT listed here — install the plugin-utils plugin, or start a new session so its bin/ reaches PATH)"

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:

Priority	Section	What to Check
1	ChatGPT Artifacts	turn0search0, oaicite, contentReference
2	Citation Problems	Hallucinated DOIs, dead links, non-existent sources
3	Prompt Refusals	"As an AI language model...", "I hope this helps"
4	Puffery	"stands as a testament to", "rich tapestry", "nestled"
5	Structure	Section summaries, "Despite challenges", rule of three
6	Mannered Prose	Metaphor where a literal phrase was available (see below)

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)

THE SHIPPED LIST IS ~/.claude/skills/ai-tic/linter/tics.yaml, NOT THIS TABLE. That file holds both halves — the tics that cleared the ~0-human-rate gate against 14,294,148 sentences, and a rejected: block naming the phrases that did not, so they are not re-proposed. Six phrases were listed here as AI tells while sitting in that rejected: block: serves as (141.35/M), it is important to note that (44.42/M), plays a crucial/vital/key role bare (21.94/M), delve into bare (11.69/M), underscores the importance (5.93/M), and Of course, (386.94/M). They are gone from the tables below and from every executable table in the repo. This is the same correction the User-Voice section thirty lines down already made for a different list — "Keep these as voice preferences if you like them … Do not present them as AI detection." — applied to this one. To check a phrase, run /ai-tic <phrase>; do not add a row here.

Puffery and Exaggeration (those that cleared the gate):

• "stands as a testament to"
• "rich tapestry of"
• "nestled in/among"
• "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:

phrase	finance	law	verdict
has bite / have more bite	1.9/M	5.2/M	human — incl. a law review title, "Do the SEC's New Rating Agency Rules Have Any Bite?"
the cut (regulatory reduction)	8.7/M	4.7/M	human — "the cut in the corporate tax rate"
Of course,	299.9/M	523.7/M	human
To be sure, ← this section used to recommend it	11.5/M	194.0/M	human, and 3× commoner in law reviews than what it replaces
Admittedly,	15.5/M	63.3/M	human
cuts against	0.9/M	13.1/M	human

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/bridge_repetition_check.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

AI Pattern	Human Alternative
"stands as a testament to"	"shows" or "demonstrates"
"rich tapestry of"	describe specifically what it contains
"nestled in the heart of"	"in" or "located in"

For Structure

AI Pattern	Human Alternative
Section summary of heading	Start with substance, not meta-commentary
"Despite challenges..."	State the reality directly without formula
Exactly three examples	Use the number that fits: 2, 4, 5, or just 1

For Mannered Prose

Definition (Anthropic guidance — quoted, do not paraphrase):

Mannered prose substitutes metaphor and flourish for direct statement. Instead of "a parameter worth varying," the mannered writer produces "a dial worth turning." Instead of "this point still matters," they write "this point earns its keep." The phrases exist to display the writer, not to convey the idea, and readers can tell. That is why mannered prose irritates: it makes the reader work harder so the writer can perform. It is also imprecise. Metaphors drag in connotations the writer did not choose and cannot control. The fix is to say what you mean. When a literal phrase is available, use it.

The short form — "Please remove all mannered prose" — works on its own and is often enough.

The mechanism is metaphor-for-literal substitution. That is narrower than "flourish" generally: the test is whether a literal phrase was available and passed over. "A dial worth turning" for "a parameter worth varying" is mannered; a long sentence is not, and an ornate one is purple, a different fault. Puffery inflates ("stands as a testament to"); mannered prose performs.

The imprecision is the load-bearing objection, not the irritation. A metaphor imports connotations the writer did not choose: "the bar routed around the holding" implies coordinated evasion, where "lawyers filed the same claims as mootness-fee requests" makes no claim about motive. Revising for taste alone misses that the mannered version often asserts something the writer cannot support.

The revision, in order:

1. Replace every mannered phrase with the literal thing it avoided.
2. Table each swap: the flourish, the plain version, and the connotation it smuggled in.
3. Name the habit the writer repeats most.

The three constraints — violating any makes the pass worse than not running it:

• Keep the meaning and the structure. A diction pass, not a rewrite.
• Leave direct sentences untouched. A sentence with no metaphor has nothing to swap.
• Don't shorten for its own sake. Literalness is the goal, not brevity. A plain replacement that runs longer than the flourish is still the right replacement.

Why the table is the deliverable, not just the edits. The third column is the point. Listing swaps without naming what each smuggled in hides the substantive change. And naming the repeated habit matters more than any single swap: individual metaphors are cheap to fix and recur immediately, while the habit is the thing the writer can act on.

A related failure, one level up (supporting research, not the definition). Density, not the device, is what makes rhetorical figures read as machine-written: "The problem is not that LLMs use these techniques: it's that they're so robotically consistent in how they use them that it becomes an abuse… What the LLM lacks is not technical ability, but taste" (Colin Gorrie, Why ChatGPT writes like that). The figures to watch are antithesis ("not X, but Y"), tricolon, isocolon, and unearned profundity. A balanced two-part closer at the end of every section is this failure, not metaphor substitution — so it is out of scope for the swap table above, and needs naming as a habit instead.

Model note. Claude Fable 5.1 writes denser prose than Fable 5 — longer sentences, fewer paragraph breaks. Defining the anti-pattern in a user message (preferred) or the system prompt is the documented mitigation.

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.

AI Pattern	Human Alternative
"a rate of 1.3771 percent"	"about one and a half percent"
"roughly ten times the 2.7361 percent rate"	"roughly ten times the abstention-wide rate"
"6,612 of 575,553 testable items — 1.15 percent — fall below"	"about one percent of testable items fall below"
"covering 85.63 percent of the testable universe"	"covering roughly six in seven of the testable universe"
"the 28.3328 percent figure"	"that figure"

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

AI Pattern	Human Alternative
"groundbreaking"	describe what it actually does
"revolutionary"	compare to what came before
"cutting-edge"	specify the technology
"transformative"	show the transformation with evidence

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.)

File	Contents	Enforced by
references/_index.md	Overview and quick screening guide	—
references/01-puffery-and-exaggeration.md	"Stands as", superficial analyses	wikipedia-puffery
references/02-promotional-language.md	"Rich tapestry", disclaimers	wikipedia-promotional
references/03-structural-patterns.md	Section summaries, negative parallelisms	wikipedia-structural
references/04-stylistic-quirks.md	Elegant variation, false ranges	reference only — regexable, but must clear the ai-tic corpus gate first
references/05-formatting-and-typography.md	Boldface, em dashes, emojis	emphasis, formatting, em-dash (boldface/emoji since v5.134.0); inline-header lists partly
references/06-communication-patterns.md	Subject lines, "I hope this helps"	wikipedia-communication
references/07-template-artifacts.md	Mad Libs patterns, placeholders	wikipedia-template-artifacts
references/08-markup-issues.md	Markdown vs wikitext confusion	reference only — wikitext-specific; no in-repo analogue
references/09-chatgpt-specific-artifacts.md	turn0search, oaicite	wikipedia-chatgpt-artifacts
references/10-citation-problems.md	Hallucinated DOIs, dead links	reference only — covered better by skills/cite-check + skills/source-verify and the cite-fidelity-* constraints, which check citations against sources rather than pattern-matching them
references/11-meta-indicators.md	Abrupt cutoffs, style discrepancies	reference only — judgement; lives in the user-agents/writing-reviewer.md rubric

Every named system is a ${CLAUDE_PLUGIN_ROOT}/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)