| 85.71% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said quietly [quietly]" | | 1 | "she asked quietly [quietly]" |
| | dialogueSentences | 35 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.143 | | effectiveRatio | 0.114 | |
| 83.15% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1780 | | totalAiIsmAdverbs | 6 | | found | | 0 | | | 1 | | | 2 | | adverb | "deliberately" | | count | 1 |
| | 3 | | | 4 | |
| | highlights | | 0 | "gently" | | 1 | "perfectly" | | 2 | "deliberately" | | 3 | "sharply" | | 4 | "completely" |
| |
| 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) | |
| 85.96% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1780 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "pristine" | | 1 | "etched" | | 2 | "database" | | 3 | "familiar" | | 4 | "echoed" |
| |
| 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 | 1 | | narrationSentences | 132 | | matches | | |
| 88.74% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 4 | | narrationSentences | 132 | | filterMatches | | | hedgeMatches | | 0 | "began to" | | 1 | "seemed to" | | 2 | "tended to" |
| |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 153 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1777 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 1374 | | uniqueNames | 15 | | maxNameDensity | 0.95 | | worstName | "McCarthy" | | maxWindowNameDensity | 2 | | worstWindowName | "McCarthy" | | discoveredNames | | Camden | 2 | | Town | 1 | | Harlow | 11 | | Quinn | 3 | | Detective | 2 | | Sergeant | 1 | | Paul | 1 | | McCarthy | 13 | | Oxfords | 1 | | Eva | 5 | | Kowalski | 2 | | Soho | 1 | | Morris | 3 | | Veil | 1 | | Compass | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Paul" | | 4 | "McCarthy" | | 5 | "Eva" | | 6 | "Kowalski" | | 7 | "Morris" | | 8 | "Compass" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 94.44% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 90 | | glossingSentenceCount | 2 | | matches | | 0 | "seemed thicker than it should, resisting the beams of their torches" | | 1 | "as if agreeing but her eyes remained fixed on the tunnel" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1777 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 153 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 32.91 | | std | 21.54 | | cv | 0.655 | | sampleLengths | | 0 | 74 | | 1 | 35 | | 2 | 11 | | 3 | 48 | | 4 | 25 | | 5 | 9 | | 6 | 16 | | 7 | 74 | | 8 | 54 | | 9 | 6 | | 10 | 28 | | 11 | 41 | | 12 | 41 | | 13 | 4 | | 14 | 15 | | 15 | 57 | | 16 | 47 | | 17 | 26 | | 18 | 28 | | 19 | 10 | | 20 | 13 | | 21 | 15 | | 22 | 38 | | 23 | 69 | | 24 | 2 | | 25 | 72 | | 26 | 42 | | 27 | 31 | | 28 | 73 | | 29 | 37 | | 30 | 10 | | 31 | 2 | | 32 | 65 | | 33 | 14 | | 34 | 28 | | 35 | 36 | | 36 | 77 | | 37 | 16 | | 38 | 20 | | 39 | 40 | | 40 | 39 | | 41 | 32 | | 42 | 26 | | 43 | 1 | | 44 | 57 | | 45 | 14 | | 46 | 50 | | 47 | 52 | | 48 | 35 | | 49 | 13 |
| |
| 86.66% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 132 | | matches | | 0 | "been cordoned" | | 1 | "was loosened" | | 2 | "was caved" | | 3 | "been delivered" | | 4 | "been placed" | | 5 | "been scratched" | | 6 | "been found" |
| |
| 46.39% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 217 | | matches | | 0 | "was still talking" | | 1 | "was remembering" | | 2 | "were crawling" | | 3 | "was pulling" | | 4 | "was speaking" |
| |
| 86.83% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 153 | | ratio | 0.02 | | matches | | 0 | "The abandoned Camden Town station smelled of wet concrete, ozone, and something sharper—like burnt copper left too long on a stove." | | 1 | "His clothing—a dark wool coat over a cashmere jumper—showed no tears, no signs of a struggle." | | 2 | "A thin silver chain had snapped around his neck; the pendant was missing." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1383 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 48 | | adverbRatio | 0.03470715835140998 | | lyAdverbCount | 19 | | lyAdverbRatio | 0.01373825018076645 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 153 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 153 | | mean | 11.61 | | std | 7.78 | | cv | 0.67 | | sampleLengths | | 0 | 21 | | 1 | 19 | | 2 | 17 | | 3 | 17 | | 4 | 4 | | 5 | 4 | | 6 | 7 | | 7 | 6 | | 8 | 14 | | 9 | 11 | | 10 | 7 | | 11 | 25 | | 12 | 16 | | 13 | 14 | | 14 | 11 | | 15 | 9 | | 16 | 2 | | 17 | 14 | | 18 | 8 | | 19 | 5 | | 20 | 15 | | 21 | 11 | | 22 | 15 | | 23 | 20 | | 24 | 5 | | 25 | 25 | | 26 | 24 | | 27 | 6 | | 28 | 28 | | 29 | 5 | | 30 | 3 | | 31 | 4 | | 32 | 16 | | 33 | 13 | | 34 | 9 | | 35 | 8 | | 36 | 24 | | 37 | 4 | | 38 | 4 | | 39 | 11 | | 40 | 9 | | 41 | 9 | | 42 | 10 | | 43 | 14 | | 44 | 15 | | 45 | 4 | | 46 | 7 | | 47 | 17 | | 48 | 11 | | 49 | 6 |
| |
| 58.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.39215686274509803 | | totalSentences | 153 | | uniqueOpeners | 60 | |
| 84.03% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 119 | | matches | | 0 | "Instead, he lay almost dead" | | 1 | "Instead, she walked the length" | | 2 | "Somewhere ahead, water dripped with" |
| | ratio | 0.025 | |
| 88.91% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 119 | | matches | | 0 | "She checked her watch." | | 1 | "He was younger than her" | | 2 | "His tie was loosened, and" | | 3 | "he said, offering her a" | | 4 | "She pulled the gloves on" | | 5 | "His eyes were open, fixed" | | 6 | "She crouched beside the corpse." | | 7 | "she asked without looking up" | | 8 | "His clothing—a dark wool coat" | | 9 | "She reached out and gently" | | 10 | "she said quietly" | | 11 | "She ignored him, rising to" | | 12 | "She climbed back up." | | 13 | "She photographed it, then followed" | | 14 | "She didn’t answer." | | 15 | "She crouched and pried it" | | 16 | "It was a small brass" | | 17 | "She turned it over." | | 18 | "She slipped the compass into" | | 19 | "She knew that satchel full" |
| | ratio | 0.328 | |
| 52.44% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 97 | | totalSentences | 119 | | matches | | 0 | "The abandoned Camden Town station" | | 1 | "Detective Harlow Quinn stepped off" | | 2 | "The platform had been cordoned" | | 3 | "Emergency lights on tall stands" | | 4 | "She checked her watch." | | 5 | "The call had come in" | | 6 | "a voice called from the" | | 7 | "Detective Sergeant Paul McCarthy waved" | | 8 | "He was younger than her" | | 9 | "His tie was loosened, and" | | 10 | "he said, offering her a" | | 11 | "She pulled the gloves on" | | 12 | "Harlow descended the metal stairs" | | 13 | "The air grew colder, heavier." | | 14 | "The body lay sprawled between" | | 15 | "A young man with a" | | 16 | "His eyes were open, fixed" | | 17 | "Blood had pooled beneath his" | | 18 | "She crouched beside the corpse." | | 19 | "The skull was caved in" |
| | ratio | 0.815 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 119 | | matches | | 0 | "If he’d fallen from the" | | 1 | "Now the same impossible details" | | 2 | "Now she intended to return" |
| | ratio | 0.025 | |
| 9.69% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 59 | | technicalSentenceCount | 11 | | matches | | 0 | "The platform had been cordoned off with police tape that looked absurdly bright against the mildew-stained walls." | | 1 | "He was younger than her by a decade, still carrying the eager posture of someone who believed the job could be won with enough enthusiasm." | | 2 | "The skull was caved in at the temple, a deep indentation that looked as though something blunt and heavy had struck him with tremendous force." | | 3 | "The edges of the crushed bone were smooth, as if the blow had been delivered by something designed for precision rather than brute force." | | 4 | "The black leather Oxfords were pristine except for the toes, which were scorched black." | | 5 | "Instead, she walked the length of the platform, counting her steps, noting every anomaly." | | 6 | "It was a small brass disc, no larger than a two-pound coin, its surface etched with strange symbols that hurt to look at directly." | | 7 | "The casing had a greenish patina, as though it had been underwater for years." | | 8 | "She’d seen Eva twice in the last month, once leaving an occult bookshop in Soho and again talking intently with a group of young people who looked far too well-…" | | 9 | "The same smell that had clung to Morris’s clothes the night they found him." | | 10 | "This was the edge of something vast and hidden, something that had been watching her since the night her partner died screaming in a language no human throat sh…" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 1 | | fancyTags | | 0 | "McCarthy suggested (suggest)" |
| | dialogueSentences | 35 | | tagDensity | 0.257 | | leniency | 0.514 | | rawRatio | 0.111 | | effectiveRatio | 0.057 | |