| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.34% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1580 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
| | 2 | |
| | highlights | | 0 | "carefully" | | 1 | "deliberately" | | 2 | "very" |
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| 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) | |
| 58.86% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1580 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "measured" | | 1 | "echoed" | | 2 | "weight" | | 3 | "aligned" | | 4 | "methodical" | | 5 | "etched" | | 6 | "trembled" | | 7 | "magnetic" | | 8 | "fragmented" | | 9 | "shattered" | | 10 | "flickered" |
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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 | 182 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 182 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "try to" | | 2 | "tried to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 182 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1580 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 14 | | matches | | 0 | "There is no ash line, Quinn said, her voice level, stripped of inflection." | | 1 | "Bone ash, Eva corrected, stepping carefully over a length of yellow tape." | | 2 | "Folklore does not leave thermal anomalies, Eva said quietly." | | 3 | "Veil Compass, Eva said." | | 4 | "It is a broken antique, Quinn said, though the words felt thin in her mouth." | | 5 | "Check his coat pocket, Eva urged." | | 6 | "He was a buyer, Quinn said, turning the bone token over." | | 7 | "He made it inside, Eva corrected." | | 8 | "Your thermal drop, Quinn said, pointing to the infrared camera mounted on a tripod." | | 9 | "I am tracking it like a crime scene, Quinn said." | | 10 | "He tried to leave, Quinn murmured." | | 11 | "No, Quinn said." | | 12 | "You need to bag the compass in lead lined evidence wrap, Quinn said, her voice cutting through the damp air." | | 13 | "I am going to find who set the perimeter, Quinn said." |
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| 73.95% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 63 | | wordCount | 1578 | | uniqueNames | 22 | | maxNameDensity | 1.52 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | Tube | 1 | | Quinn | 24 | | Metropolitan | 1 | | Police | 1 | | Detective | 2 | | Kowalski | 2 | | Met | 1 | | British | 1 | | Museum | 1 | | Oxford | 2 | | Ancient | 1 | | History | 1 | | Eva | 10 | | Compass | 1 | | Shade | 1 | | Morris | 2 | | Docklands | 1 | | Veil | 2 | | Market | 1 | | Harlow | 2 | | You | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Kowalski" | | 2 | "Museum" | | 3 | "Eva" | | 4 | "Morris" | | 5 | "Market" | | 6 | "Harlow" | | 7 | "You" |
| | places | | 0 | "British" | | 1 | "Oxford" | | 2 | "Ancient" | | 3 | "Compass" | | 4 | "Docklands" |
| | globalScore | 0.74 | | windowScore | 0.833 | |
| 83.63% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 113 | | glossingSentenceCount | 3 | | matches | | 0 | "as if expecting the shadows to bite" | | 1 | "sigils that seemed to shift if she stared too long" | | 2 | "something like this before" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.633 | | wordCount | 1580 | | matches | | 0 | "not in a death grip, but in a deliberate arrangement" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 182 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 56.43 | | std | 38.13 | | cv | 0.676 | | sampleLengths | | 0 | 122 | | 1 | 96 | | 2 | 7 | | 3 | 144 | | 4 | 19 | | 5 | 42 | | 6 | 56 | | 7 | 26 | | 8 | 111 | | 9 | 23 | | 10 | 97 | | 11 | 8 | | 12 | 91 | | 13 | 20 | | 14 | 57 | | 15 | 105 | | 16 | 49 | | 17 | 13 | | 18 | 62 | | 19 | 61 | | 20 | 45 | | 21 | 10 | | 22 | 80 | | 23 | 57 | | 24 | 23 | | 25 | 39 | | 26 | 97 | | 27 | 20 |
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| 87.91% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 9 | | totalSentences | 182 | | matches | | 0 | "been sealed" | | 1 | "been condemned" | | 2 | "were curled" | | 3 | "was etched" | | 4 | "was thrown" | | 5 | "is broken" | | 6 | "been placed" | | 7 | "is localized" | | 8 | "been caught" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 282 | | matches | | 0 | "was bleeding" | | 1 | "was carrying" | | 2 | "was not just trading" | | 3 | "were leaving" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 182 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 807 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.01486988847583643 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007434944237918215 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 182 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 182 | | mean | 8.68 | | std | 6.52 | | cv | 0.751 | | sampleLengths | | 0 | 16 | | 1 | 29 | | 2 | 16 | | 3 | 31 | | 4 | 10 | | 5 | 3 | | 6 | 17 | | 7 | 20 | | 8 | 3 | | 9 | 3 | | 10 | 16 | | 11 | 26 | | 12 | 4 | | 13 | 19 | | 14 | 3 | | 15 | 2 | | 16 | 7 | | 17 | 6 | | 18 | 25 | | 19 | 18 | | 20 | 28 | | 21 | 13 | | 22 | 12 | | 23 | 27 | | 24 | 15 | | 25 | 13 | | 26 | 6 | | 27 | 12 | | 28 | 7 | | 29 | 5 | | 30 | 12 | | 31 | 6 | | 32 | 5 | | 33 | 39 | | 34 | 6 | | 35 | 6 | | 36 | 9 | | 37 | 13 | | 38 | 4 | | 39 | 2 | | 40 | 12 | | 41 | 16 | | 42 | 5 | | 43 | 2 | | 44 | 2 | | 45 | 3 | | 46 | 9 | | 47 | 14 | | 48 | 2 | | 49 | 26 |
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| 54.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.36813186813186816 | | totalSentences | 182 | | uniqueOpeners | 67 | |
| 59.88% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 167 | | matches | | 0 | "Just a man in his" | | 1 | "Just scuff marks and spilled" | | 2 | "Just a kind you do" |
| | ratio | 0.018 | |
| 97.84% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 51 | | totalSentences | 167 | | matches | | 0 | "She checked the worn leather" | | 1 | "She had seen death in" | | 2 | "It felt staged." | | 3 | "Her curly red hair had" | | 4 | "It is a binding perimeter." | | 5 | "I have a dead man" | | 6 | "I do not need folklore," | | 7 | "I need a cause of" | | 8 | "She knelt, keeping a respectful" | | 9 | "Its casing wore a thick" | | 10 | "It trembled, then swung hard" | | 11 | "It does not track magnetic" | | 12 | "It tracks rifts." | | 13 | "It is a broken antique," | | 14 | "She had seen something like" | | 15 | "She had spent thirty six" | | 16 | "Her fingers brushed cold, porous" | | 17 | "She drew out a disk" | | 18 | "She had read the intercepted" | | 19 | "He was a buyer, Quinn" |
| | ratio | 0.305 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 111 | | totalSentences | 167 | | matches | | 0 | "The air in the disused" | | 1 | "Harlow Quinn descended the cracked" | | 2 | "The platform had been sealed" | | 3 | "She checked the worn leather" | | 4 | "The night shift was bleeding" | | 5 | "A body lay near the" | | 6 | "Quinn's sharp jaw tightened." | | 7 | "She had seen death in" | | 8 | "It felt staged." | | 9 | "The voice echoed from the" | | 10 | "Eva Kowalski stepped into the" | | 11 | "Her curly red hair had" | | 12 | "Freckles stood out against her" | | 13 | "Eva officially consulted for the" | | 14 | "Quinn still wasn't sure whether" | | 15 | "Bone ash, Eva corrected, stepping" | | 16 | "It is a binding perimeter." | | 17 | "Quinn exhaled through her nose." | | 18 | "I have a dead man" | | 19 | "I do not need folklore," |
| | ratio | 0.665 | |
| 89.82% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 167 | | matches | | 0 | "Whoever laid this down did" | | 1 | "If this market moves every" | | 2 | "If the rift has not" |
| | ratio | 0.018 | |
| 35.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 9 | | matches | | 0 | "Harlow Quinn descended the cracked service stairs, her boots striking each step with the measured cadence of a woman who had spent eighteen years walking into o…" | | 1 | "The platform had been sealed since the late nineties, yet the space hummed with a subsonic frequency that made her molars ache and the fine hairs on her arms st…" | | 2 | "A body lay near the platform edge, draped in a heavy wool coat that smelled of woodsmoke and oxidized copper." | | 3 | "Two uniformed officers stood guard near the ticket barrier, looking pale and jumpy, their hands hovering near their batons as if expecting the shadows to bite." | | 4 | "Round glasses magnified green eyes that held none of the usual civilian tremor." | | 5 | "I have a dead man with no trauma, a station that has been condemned for thirty years, and a forensics team that cannot explain why the ambient temperature drops…" | | 6 | "Its casing wore a thick patina of verdigris, and the face was etched with interlocking geometric sigils that seemed to shift if she stared too long." | | 7 | "A supernatural black market that moved locations every full moon, trading in enchanted goods and banned alchemical substances." | | 8 | "But the returning prints were deeper, spaced wider, as if the person was carrying dead weight." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |