Appendix·auto-generated

The catalog

Every rule the engine watches for. 49 deterministic, 19 LLM-judged. Built from the source on every deploy.

Deterministic

49 rules, no LLM, milliseconds per file

Each phrase-based rule lists every phrase it scans for. Density rules report only when their threshold is crossed; structural rules examine sentence and paragraph shape.

AI phrasebank 7

idsevwhat it catches
ai-tell-phrasebank error Phrases that overwhelmingly indicate AI-generated prose. Replace with concrete, specific language.
61 phrases
  • delve into
  • dive into
  • navigate the landscape
  • navigate the complexities
  • navigate the intricacies
  • navigating complex ecosystems
  • embark on a journey
  • rich tapestry
  • vibrant tapestry
  • tapestry of
  • in the realm of
  • stands as a testament
  • a testament to
  • is a testament to
  • serves as a testament
  • plays a crucial role
  • plays a pivotal role
  • plays a vital role
  • plays a key role
  • in todays fast paced world
  • in todays digital age
  • in todays digital landscape
  • in this fast paced digital
  • in the ever evolving landscape
  • ever evolving
  • ever changing
  • at the heart of
  • in the heart of
  • the world of
  • in the world of
  • treasure trove
  • intricate dance
  • intricate web
  • intricate tapestry
  • multifaceted
  • look no further
  • paramount importance
  • pivotal moment
  • key turning point
  • load bearing
  • valuable insights
  • gain valuable insights
  • deeply rooted
  • indelible mark
  • setting the stage
  • diverse array
  • imagine a world
  • at its core
  • in essence
  • buckle up
  • thats only half the story
  • heres the kicker
  • heres the truth
  • real talk
  • the truth is
  • underscoring its
  • underscores its
  • highlights its
  • reflects broader
  • a beacon of
  • a symphony of
overused-words info Single words that show up disproportionately in AI prose. Any one may be defensible in context, but in aggregate they form a recognizable AI accent. Matched via stem, so morphological variants (e.g., 'unleashes', 'fostering') are caught.
52 phrases
  • transformative
  • groundbreaking
  • revolutionary
  • unleash
  • harness
  • elevate
  • demystify
  • myriad
  • plethora
  • seamless
  • cutting-edge
  • scalable
  • underscore
  • foster
  • ignite
  • empower
  • uncover
  • vibrant
  • beacon
  • symphony
  • showcase
  • boast
  • garner
  • meticulous
  • nuanced
  • enduring
  • bolster
  • streamline
  • encompass
  • renowned
  • robust
  • future-ready
  • future-proof
  • best-in-class
  • world-class
  • highlight
  • enhance
  • emphasize
  • cultivate
  • align
  • pivotal
  • vital
  • crucial
  • realm
  • ecosystem
  • paradigm
  • landscape
  • tapestry
  • mosaic
  • endeavor
  • labyrinth
  • kaleidoscope
antithesis-cadence warning The 'It's not X, it's Y' / 'Not just X but Y' rhythm is a signature AI structural tell. One instance is fine; the cadence becomes a fingerprint when it repeats.
throat-clearing-openers warning Sentences that start with filler delay the real opening. Cut the opener; lead with substance.
21 phrases
  • it is important to note
  • it is important to consider
  • it is worth mentioning
  • it is worth noting
  • when it comes to
  • in todays world
  • first and foremost
  • needless to say
  • it should be noted
  • let us examine
  • let us explore
  • without a doubt
  • as a matter of fact
  • generally speaking
  • while it is true
  • it could be argued that
  • picture this
  • as a business owner you know
  • lets dive in
  • lets explore
  • imagine for a moment
cliche-closers warning Boilerplate openers in closing paragraphs. Trust the reader; don't announce you're concluding.
13 phrases
  • in conclusion
  • in summary
  • to sum up
  • to summarize
  • all in all
  • all things considered
  • at the end of the day
  • ultimately
  • one thing is clear
  • the future looks bright
  • the possibilities are endless
  • the future of
  • it remains to be seen
meta-discourse info Talking about the writing instead of writing. Cut self-reference; just say the thing.
23 phrases
  • as i mentioned
  • as discussed above
  • as discussed earlier
  • as previously noted
  • as i said
  • as we shall see
  • as we will see
  • we will see
  • this section will
  • in the following
  • in this section
  • this article will
  • this post will
  • this essay will
  • in this article
  • in this post
  • let me break this down
  • let me walk you through
  • let me explain
  • lets break it down
  • lets walk through
  • before we dive in
  • without further ado
copula-dodge warning AI prose substitutes plain "is/are" with inflated verbs ("serves as", "stands as", "marks", "represents"). One is fine; in aggregate it's a tell.
16 phrases
  • serves as a
  • serves as the
  • stands as a
  • stands as the
  • marks a
  • marks the
  • represents a
  • represents the
  • boasts a
  • boasts the
  • embodies the
  • exemplifies the
  • constitutes a
  • constitutes the
  • remains a
  • remains the

AI fossils 4

idsevwhat it catches
signoff-chatbot error Chat-style closing lines leaked from an assistant reply into prose. Cut entirely.
12 phrases
  • i hope this helps
  • hope this helps
  • let me know if
  • feel free to ask
  • feel free to reach out
  • if you have any questions
  • happy to provide more details
  • happy to clarify
  • happy to help
  • hope this finds you well
  • i hope this clarifies
  • i hope you find this useful
sycophant-opener error Flattering acknowledgements ("Great question!", "Absolutely!") that praise the prompt or reader instead of starting. Cut.
12 phrases
  • great question
  • what a great question
  • what a brilliant question
  • wonderful question
  • fantastic question
  • excellent question
  • absolutely
  • of course
  • certainly
  • you raise an interesting point
  • thats a great point
  • wonderful
disclaimer-tail error Verbatim AI self-disclosure or refusal language leaked into prose. Always delete.
14 phrases
  • as an ai language model
  • as an ai assistant
  • as a large language model
  • as an ai
  • i do not have personal
  • i dont have personal
  • i cannot provide
  • i am unable to
  • my training data
  • my knowledge cutoff
  • i dont have access to
  • i do not have access to
  • as of my last update
  • as of my knowledge cutoff
citation-artifact error Raw citation / tool-call tokens left over from LLM output (turn0search0, oaicite, contentReference, …). Always delete.

Phrase 6

idsevwhat it catches
corporate-cliche warning Boardroom jargon hides meaning. Use the plain word the jargon replaced.
17 phrases
  • moving forward
  • low hanging fruit
  • circle back
  • touch base
  • synergy
  • synergies
  • stakeholders
  • actionable
  • deep dive
  • on the same page
  • ducks in a row
  • think outside the box
  • boil the ocean
  • move the needle
  • north star
  • leverage
  • leveraging
cliche-list warning Tired phrases the reader skims past. Replace with a fresh image or plain statement.
15 phrases
  • game changer
  • paradigm shift
  • needle in a haystack
  • silver lining
  • once in a blue moon
  • only time will tell
  • double edged sword
  • tip of the iceberg
  • elephant in the room
  • perfect storm
  • from the ground up
  • back to the drawing board
  • the new normal
  • raise the bar
  • wake up call
wordy-phrases warning Multi-word phrases that compress to a single word without losing meaning.
16 replacements
  • in order toto
  • due to the fact thatbecause
  • in spite of the fact thatalthough
  • at this point in timenow
  • at the present timenow
  • in the event thatif
  • for the purpose offor
  • with regard toabout
  • with respect toabout
  • in light of the fact thatbecause
  • a large number ofmany
  • a majority ofmost
  • a small number ofa few
  • the fact thatthat
  • have the ability tocan
  • has the ability tocan
redundant-pairs warning One word already means what the pair means together. Drop the redundant modifier.
18 replacements
  • added bonusbonus
  • free giftgift
  • past historyhistory
  • end resultresult
  • final outcomeoutcome
  • absolute necessitynecessity
  • completely fullfull
  • totally uniqueunique
  • very uniqueunique
  • close proximityproximity
  • exact samesame
  • future plansplans
  • unexpected surprisesurprise
  • advance warningwarning
  • honest truthtruth
  • new innovationinnovation
  • personal opinionopinion
  • true factfact
weasel-hedges warning Hedges weaken claims without naming real uncertainty. Make the claim or name the doubt.
25 phrases
  • arguably
  • perhaps
  • some say
  • it could be argued
  • many believe
  • it has been suggested
  • it is said that
  • often
  • generally
  • typically
  • frequently
  • occasionally
  • in many cases
  • in some cases
  • more or less
  • kind of
  • sort of
  • experts argue
  • experts agree
  • industry reports
  • observers have cited
  • it is widely believed
  • it is widely accepted
  • many people think
  • several sources suggest
vague-quantifiers info 'Many', 'several', 'a number of' all dodge specifics. If you have a number, name it; if you don't, name what you do know.
11 phrases
  • many
  • some
  • several
  • various
  • numerous
  • a number of
  • a variety of
  • a range of
  • a lot of
  • lots of
  • a few

Density 8

idsevwhat it catches
em-dash-density warning Em-dashes used too frequently. AI prose leans on em-dashes for any pause; vary with commas, semicolons, or full stops.
adverb-density info High -ly adverb count. Adverbs usually mark a weak verb. Strengthen the verb and the adverb falls out.
nominalization-density info Heavy use of -tion / -ment / -ity nouns. Turn nominalizations back into the verbs they hide.
boosters info Intensifiers that add no information. Cut them; the sentence almost always survives.
12 phrases
  • very
  • really
  • actually
  • literally
  • basically
  • definitely
  • totally
  • absolutely
  • completely
  • obviously
  • clearly
  • extremely
passive-voice info Passive constructions hide the actor. Recast in active voice where the agent matters.
pronoun-density-low info First- and second-person pronouns are absent. Prose reads as detached corporate-speak. Address the reader; own the claim.
parenthetical-aside-density info Parentheticals used as breath-marks ("(yes, really)", "(more on that below)"). A few are fine; many is an AI rhythm.
inline-bold-emphasis warning Compulsive **bolding** of key terms inside running prose. Vary emphasis or trust the reader.

Cadence 12

idsevwhat it catches
sentence-length-monotony warning Sentences of similar length lull the reader. Vary the rhythm: short sentences for impact, long ones for thinking.
sentence-too-long warning Sentences over 40 words usually carry too many clauses. Break or cut.
paragraph-monotony info Many consecutive paragraphs of similar length give the page a wall-of-text feel. Vary paragraph weight.
parallel-triplet-density info AI prose leans on the 'A, B, and C' triplet for rhythm. A few are fine; many in succession is a tell.
transition-stacking warning Three or more consecutive sentences starting with Moreover/Furthermore/etc. reads as machine-generated. Vary openings.
repeated-words-window info Same content word three times in five sentences. Vary diction.
noun-stacking info Long chains of complex nouns/adjectives crush comprehension. Break with prepositions or verbs.
anaphora-cadence warning Three or more consecutive sentences open with the same content word. Vary the rhythm.
fragment-cadence warning Three or more consecutive paragraphs that are each a single short sentence. Punchy-fragment rhythm reads as AI marketing.
hero-tagline-imperative error Cross-sentence imperative-verb tricolon ("Ship faster. Build smarter. Scale forever."). The single most recognizable AI marketing rhythm.
from-x-to-y warning Sentence-initial "From X to Y, …" manufactures a survey-of-the-field tone. Lead with the specific case.
present-participle-tail warning Sentences ending in ", highlighting/emphasizing/underscoring …" tack on faux-analysis. Cut the tail or replace with a specific consequence.

Consistency 3

idsevwhat it catches
dash-style-inconsistency warning Document mixes em-dash, en-dash, and double-hyphen for parenthetical breaks. Pick one and use it consistently.
quote-style-inconsistency info Document mixes straight ASCII quotes (") with curly quotes (“/”). Pick one and normalize.
oxford-comma-inconsistency info Document uses Oxford comma in some 3-item lists but not others. Pick one style.

Weak constructions 4

idsevwhat it catches
there-is-there-are info Sentences that open with 'There is/are' bury the subject. Recast so the real subject is at the front.
expletives info Sentences opening with a bare 'This is the...', 'That was a...', or 'It is the...' delay the real subject.
negation-of-negation info 'Not unimportant', 'not impossible' — double negatives make the reader work to extract a simple positive.
pronoun-it-vague info Sentences opening with 'It is/was/seems' use 'It' as a placeholder. Name what 'it' refers to.

Markdown shape 5

idsevwhat it catches
bullet-bold-lead warning Bullet lists where most items start with a `**Bold label:**` followed by an explanation. Signature AI-assistant markdown shape.
title-case-headers info Markdown headings written in Title Case. Sentence case is the modern default; Title Case in headings is a recognizable AI tic.
colon-headline info Most headings shaped "Topic: Descriptor". A recognizable AI-listicle / mock-bookstore-spine template.
decorative-emoji info Emoji used as decoration in headings or bullets (🚀, ✨, 📌, 💡). A recognizable AI-marketing tic; remove or replace with words.
false-precision-headline warning Listicle / faux-precise headings ("5 Reasons …", "10x Faster …"). Cheap manufactured concreteness.

LLM-judged

19 higher-level patterns

Patterns regex can’t catch. The engine ships these as a prompt the model evaluates; the model returns structured findings in the same shape the deterministic engine uses.

idsevwhat it catches
buried-lede error The piece's most important claim or finding is not in the first paragraph. The opening warms up instead of starting.
Examples

Good Our migration cut p99 latency by 42%. Here's how. (Lede first.)

Bad In today's fast-paced world, systems face many demands. Teams must consider many factors. We undertook a migration. (Real news buried four paragraphs in.)

voice-consistency warning Voice/persona drifts between sections — formal opening, conversational middle, technical closing — with no narrative reason.
Examples

Good A piece that maintains the same register from start to finish, or shifts register only at clear narrative beats.

Bad Section 1 opens with academic-detached prose; section 2 reads like a Slack message; section 3 switches to corporate-marketing voice. No structural reason for the shifts.

mixed-metaphor warning Two or more incompatible metaphors used together — picture-bending images that collide rather than reinforce.
Examples

Good The plan was a tightrope: one wrong step and the whole team fell.

Bad The plan was a tightrope, and we had to keep all the plates spinning while pushing the ball down the field.

claim-without-support error A non-trivial factual or evaluative claim is asserted without evidence, reasoning, citation, or example.
Examples

Good Our cache hit ratio jumped from 71% to 94% (Grafana, week of March 12).

Bad This is the best architecture for scale. (No data, no comparison, no reasoning.)

missing-stakes warning The reader cannot answer 'so what / who cares / what changes' after reading. The piece describes without naming consequence.
Examples

Good If we miss this deadline, the holiday launch slips and we lose the Q4 revenue we already booked.

Bad We discussed the trade-offs and reviewed the options thoroughly. (Reader has no idea what was at stake.)

distinctive-vs-generic warning Prose could have been written by anyone (or any model). No specific detail, no authorial fingerprint, no opinion the writer would defend.
Examples

Good Specific names, dates, numbers, judgments, and a recognizable narrator stance.

Bad Abstract claims about 'organizations', 'solutions', and 'best practices' without anyone, any date, or any number.

abstract-without-concrete warning Extended abstract reasoning runs for paragraphs without a grounding example, scene, number, or sensory detail.
Examples

Good After three paragraphs of theory, an example: 'Here's what this looked like for the payments team last quarter.'

Bad Six paragraphs of 'systems', 'processes', and 'frameworks' with no concrete instance.

showing-vs-telling info Narrative tells the reader what to feel or conclude instead of showing the evidence that produces the feeling/conclusion.
Examples

Good She left the meeting without speaking and the door clicked behind her.

Bad She was furious and everyone could feel the tension.

transition-coherence warning Paragraphs do not logically connect — abrupt topic jumps, missing causal/temporal links, or 'list of points' structure where prose should flow.
Examples

Good Each paragraph picks up a thread from the previous one and advances it.

Bad Paragraph 1 about caching. Paragraph 2 about team morale. Paragraph 3 about cost. No connective tissue.

register-mismatch info Formal and casual constructions sit side-by-side without intent — signals an untuned voice or AI-generated mash-up.
Examples

Good Voice is consistently casual or consistently formal, with deliberate shifts.

Bad 'Furthermore, the implementation leverages a robust caching layer (it's basically just Redis, lol).' — two registers smashed together.

excessive-balance warning Every claim earns a 'but' / 'however' / 'on the other hand'. Faux-balance flattens the piece's point and signals AI hedging.
Examples

Good The writer takes a position and sticks with it, naming real counterarguments where they bite.

Bad Each paragraph proposes a view, then immediately walks it back with 'however'. By the end the reader has no idea what the writer thinks.

redundant-thesis info The opening and closing restate the same thesis in nearly identical words — a hallmark of AI structure-by-template.
Examples

Good The opening sets a hook; the closing lands a different beat (a surprise, a stake, a call to action).

Bad Opening: 'AI is changing how we write.' Closing: 'In conclusion, AI is changing how we write.'

marketing-template-cadence warning Stock AI hero-line shape: imperative fragment then tricolon expansion ("Ship X. A Y, a Z, and N things for Q."). The template is the tell — content specificity doesn't redeem it.
Examples

Good A prose linter. 49 deterministic rules, 19 LLM-judged ones. Detection-only.

Bad Mark up prose before it ships. A skill, a CLI, and forty-four rules for catching AI tells and writing-quality issues.

sycophantic-tone warning Whole-passage flattery: praising the reader, the prompt, the topic, or itself before delivering. Distinct from a single opener.
Examples

Good Here's what we tried, what worked, and what didn't.

Bad What a fantastic topic — this is going to be such a rich and rewarding exploration of an area that truly matters.

stakes-inflation warning World-historical or paradigm-shifting stakes attached to small features or routine changes. Inverse of missing-stakes.
Examples

Good The new filter saved support ~20 tickets/week.

Bad This new sort filter is fundamentally reshaping how humanity interacts with information.

false-reframe warning The 'It's not X, it's Y' move performed without semantic content — Y is a paraphrase of X, or both are empty. Catches the rhetoric even when antithesis-cadence misses the surface form.
Examples

Good Cutting build time from 11 min to 90 sec changed who shipped — the on-call eng now ships during the on-call.

Bad This isn't just about efficiency. It's about transformation.

invented-concept-label info A Capitalized Compound ("The Engagement Doom Loop", "The Velocity Trap") referred to as if established, without rigorous definition or citation.
Examples

Good A coined term defined precisely on first use, then used consistently and supported with evidence.

Bad This is what I call the Engagement Doom Loop. The Engagement Doom Loop happens whenever teams …

listicle-disguise info Structurally a numbered list but flowed into paragraphs — each paragraph one item, all parallel shape, thin connective veneer.
Examples

Good Argument paragraphs that build on each other and advance a position.

Bad The first thing is X. The second thing is Y. The third thing is Z. Each as a separate one-sentence paragraph.

one-point-dilution info A single idea restated under multiple framings instead of advancing the argument or supplying evidence.
Examples

Good Each paragraph either adds evidence, raises an objection, or moves to the next claim.

Bad Five paragraphs that each say 'X is important' with different metaphors and no new fact.