| 94.74% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "He shifted back [back]" |
| | dialogueSentences | 19 | | tagDensity | 0.474 | | leniency | 0.947 | | rawRatio | 0.111 | | effectiveRatio | 0.105 | |
| 97.30% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1849 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 43.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1849 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "wavered" | | 1 | "glistening" | | 2 | "flicker" | | 3 | "echoing" | | 4 | "sentinels" | | 5 | "pulse" | | 6 | "glinting" | | 7 | "echoed" | | 8 | "weight" | | 9 | "familiar" | | 10 | "etched" | | 11 | "pulsed" | | 12 | "dancing" | | 13 | "flickered" | | 14 | "methodical" | | 15 | "beacon" | | 16 | "testament" | | 17 | "spectral" | | 18 | "glint" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 140 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 140 | | filterMatches | | | hedgeMatches | | |
| 98.85% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 150 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0.007 | | matches | | 0 | "Rain sloshed under Harlow Quinn’s boots as she sprinted downスタッフォード Street, her leather watch slipping against her wrist, the seconds ticking like a grenade hidden in her palm." |
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| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 26 | | markdownWords | 90 | | totalWords | 1838 | | ratio | 0.049 | | matches | | 0 | "Unexplained" | | 1 | "Two more blocks, then the maze of alleyways." | | 2 | "thud" | | 3 | "former paramedic" | | 4 | "he’s fleeing like a man, not fighting like one" | | 5 | "healed" | | 6 | "wait" | | 7 | "flesh" | | 8 | "services" | | 9 | "one second." | | 10 | "The Raven’s Nest" | | 11 | "thud" | | 12 | "I can handle a man." | | 13 | "in a hospital I once knew, in a body I watched fail" | | 14 | "For Resuscitation Only" | | 15 | "her" | | 16 | "Artemis" | | 17 | "transplanted human livers from unwilling donors." | | 18 | "you’re" | | 19 | "me." | | 20 | "he’d treated a cabaret singer for a consumption that wasn’t from lungs" | | 21 | "transplant" | | 22 | "pleasure" | | 23 | "your partner’s" | | 24 | "Counteracts the after effects of transplantation. Not mine to make." | | 25 | "already be coming." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 77 | | wordCount | 1616 | | uniqueNames | 22 | | maxNameDensity | 1.61 | | worstName | "Herrera" | | maxWindowNameDensity | 3 | | worstWindowName | "Herrera" | | discoveredNames | | Harlow | 16 | | Quinn | 1 | | Street | 1 | | Herrera | 26 | | Morris | 3 | | Raven | 2 | | Nest | 2 | | Soho | 1 | | Saint | 2 | | Christopher | 2 | | Tube | 2 | | Tomás | 3 | | Veil | 2 | | Market | 2 | | Camden | 1 | | Smithfield | 1 | | Morans | 5 | | King | 1 | | Cross | 1 | | Resuscitation | 1 | | Seville | 1 | | Guilt | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Morris" | | 4 | "Raven" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Tomás" | | 8 | "Market" | | 9 | "Morans" | | 10 | "King" | | 11 | "Cross" |
| | places | | 0 | "Soho" | | 1 | "Smithfield" | | 2 | "Seville" |
| | globalScore | 0.696 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 108 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.544 | | wordCount | 1838 | | matches | | 0 | "not the sound of a magician, but of a man" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 150 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 59.29 | | std | 31.96 | | cv | 0.539 | | sampleLengths | | 0 | 102 | | 1 | 92 | | 2 | 67 | | 3 | 80 | | 4 | 133 | | 5 | 79 | | 6 | 99 | | 7 | 3 | | 8 | 85 | | 9 | 11 | | 10 | 81 | | 11 | 36 | | 12 | 51 | | 13 | 63 | | 14 | 103 | | 15 | 90 | | 16 | 54 | | 17 | 30 | | 18 | 106 | | 19 | 52 | | 20 | 42 | | 21 | 28 | | 22 | 36 | | 23 | 18 | | 24 | 59 | | 25 | 55 | | 26 | 48 | | 27 | 57 | | 28 | 21 | | 29 | 46 | | 30 | 11 |
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| 95.24% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 140 | | matches | | 0 | "was made" | | 1 | "were sanded" | | 2 | "was dedicated" | | 3 | "made" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 260 | | matches | | 0 | "was backing" | | 1 | "wasn’t giving" | | 2 | "was shouting" | | 3 | "was impossibly hanging" | | 4 | "were dancing" | | 5 | "was slipping" | | 6 | "were closing" | | 7 | "were already turning" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 13 | | totalSentences | 150 | | ratio | 0.087 | | matches | | 0 | "She’d read it in the file buried in her drawer, the one marked *Unexplained*—DS Morris’s final case." | | 1 | "The Raven’s Nest was a dive even for Soho—a smoky dive, if the stench of burnt incense and stale beer through the seam of the door was any indication." | | 2 | "Harlow tracked Herrera’s path through the haze—a man in a olive coat, retreating toward the shelves of ammonites and vials of liquid moonlight behind the bar." | | 3 | "This was no magical stalker, no wraith—*he’s fleeing like a man, not fighting like one*." | | 4 | "Herrera’s silhouette was already halfway down, his Saint Christopher medallion glinting on his chest—a fool’s token given the kind of people he’d been treating off the books." | | 5 | "The bookings analyst, the cabaret host, the violinist who played in a catacomb—quarantine, that was the term Harlow had dug up in files she wasn’t permitted to see." | | 6 | "Herrera’s breath echoed ahead, but the scent of rain was backing off, replaced by something older—burnt hair and rhubarb, the stink of alchemical accidents." | | 7 | "Herrera waded ahead, his shirt soaked and clinging to the scar on his forearm—a long, pale caterpillar on his skin from some knife attack last year." | | 8 | "Harlow’s mind snapped back to the morgue photo—DS Morris’s body cut open with a blade that’d singsed the tissue as if it were leather." | | 9 | "Stalls jutted out like necrotic teeth—blackthorned vendors hawking snake molars and vials of starlight." | | 10 | "He yelped—not the sound of a magician, but of a man." | | 11 | "Herrera had that same look in his eyes—*in a hospital I once knew, in a body I watched fail*." | | 12 | "She saw the glint of Herrera’s own watch—silvery and new." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1632 | | adjectiveStacks | 1 | | stackExamples | | 0 | "narrow, curly-haired frame" |
| | adverbCount | 38 | | adverbRatio | 0.023284313725490197 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.004901960784313725 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 150 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 150 | | mean | 12.25 | | std | 8.02 | | cv | 0.655 | | sampleLengths | | 0 | 28 | | 1 | 21 | | 2 | 2 | | 3 | 6 | | 4 | 17 | | 5 | 28 | | 6 | 11 | | 7 | 1 | | 8 | 10 | | 9 | 36 | | 10 | 22 | | 11 | 12 | | 12 | 29 | | 13 | 8 | | 14 | 6 | | 15 | 16 | | 16 | 8 | | 17 | 7 | | 18 | 22 | | 19 | 25 | | 20 | 26 | | 21 | 5 | | 22 | 15 | | 23 | 7 | | 24 | 8 | | 25 | 4 | | 26 | 15 | | 27 | 15 | | 28 | 27 | | 29 | 28 | | 30 | 9 | | 31 | 22 | | 32 | 24 | | 33 | 13 | | 34 | 20 | | 35 | 11 | | 36 | 26 | | 37 | 5 | | 38 | 24 | | 39 | 8 | | 40 | 8 | | 41 | 17 | | 42 | 3 | | 43 | 10 | | 44 | 22 | | 45 | 17 | | 46 | 25 | | 47 | 11 | | 48 | 7 | | 49 | 4 |
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| 50.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.32666666666666666 | | totalSentences | 150 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 126 | | matches | (empty) | | ratio | 0 | |
| 99.37% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 126 | | matches | | 0 | "She’d read it in the" | | 1 | "He’d missed a step, tottering" | | 2 | "Her fingers tightened around the" | | 3 | "She pushed the door open" | | 4 | "He ducked behind the bookshelf." | | 5 | "She heard the shift in" | | 6 | "She slipped into the secret" | | 7 | "He’d taken a left turn" | | 8 | "Her boots hit the end" | | 9 | "His narrow, curly-haired frame pushed" | | 10 | "She knew its myths long" | | 11 | "She stepped onto the platform." | | 12 | "It was longer than any" | | 13 | "They had *flesh*, thick curling" | | 14 | "Her revolver felt heavier with" | | 15 | "She’d kept it for the" | | 16 | "She stepped down onto the" | | 17 | "Her eyes caught on a" | | 18 | "They’d etched a crossroads into" | | 19 | "She recognized the photograph of" |
| | ratio | 0.302 | |
| 51.27% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 103 | | totalSentences | 126 | | matches | | 0 | "Rain sloshed under Harlow Quinn’s" | | 1 | "The name clenched in her" | | 2 | "She’d read it in the" | | 3 | "The one Harlow had spent" | | 4 | "He’d missed a step, tottering" | | 5 | "Her fingers tightened around the" | | 6 | "Harlow skidded into the alcove" | | 7 | "The entrance swallowed him whole," | | 8 | "The Raven’s Nest was a" | | 9 | "Harlow pressed her ear against" | | 10 | "Voices murmured inside, low as" | | 11 | "She pushed the door open" | | 12 | "The bar was a nest" | | 13 | "Harlow tracked Herrera’s path through" | | 14 | "He ducked behind the bookshelf." | | 15 | "She heard the shift in" | | 16 | "Harlow’s pulse hammered against her" | | 17 | "The file said he was" | | 18 | "This was no magical stalker," | | 19 | "She slipped into the secret" |
| | ratio | 0.817 | |
| 79.37% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 126 | | matches | | 0 | "Now, the watch was slipping" | | 1 | "Even if it wasn’t the" |
| | ratio | 0.016 | |
| 57.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 67 | | technicalSentenceCount | 8 | | matches | | 0 | "The one Harlow had spent three years clawing away at with both hands, bleeding her way through dead ends and whispered rumors of things that didn’t make sense." | | 1 | "*Two more blocks, then the maze of alleyways.* But Herrera was fast, his breath coming in ragged bursts as he veered left, disappearing into a doorway marked on…" | | 2 | "The bookings analyst, the cabaret host, the violinist who played in a catacomb—quarantine, that was the term Harlow had dug up in files she wasn’t permitted to …" | | 3 | "Harlow’s mind snapped back to the morgue photo—DS Morris’s body cut open with a blade that’d singsed the tissue as if it were leather." | | 4 | "His narrow, curly-haired frame pushed into a station platform that hadn’t existed before he stumbled into it." | | 5 | "A place that slid between locations every full moon, this time anchored in the belly of an abandoned Tube station beneath Camden." | | 6 | "They had *flesh*, thick curling tendons that twitched under her eyes." | | 7 | "The bar she’d just left, *The Raven’s Nest*, was impossibly hanging in the air above a meat locker, its neon glinting like a promise." |
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| 13.89% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 2 | | matches | | 0 | "one growled, though the words were sanded down too smooth to be human" | | 1 | "He shifted back, his scar a red beacon in the dark" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 3 | | fancyTags | | 0 | "one growled (growl)" | | 1 | "he laughed (laugh)" | | 2 | "she growled (growl)" |
| | dialogueSentences | 19 | | tagDensity | 0.211 | | leniency | 0.421 | | rawRatio | 0.75 | | effectiveRatio | 0.316 | |