| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said quietly [quietly]" |
| | dialogueSentences | 34 | | tagDensity | 0.382 | | leniency | 0.765 | | rawRatio | 0.077 | | effectiveRatio | 0.059 | |
| 83.92% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2176 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "slowly" | | 1 | "softly" | | 2 | "really" | | 3 | "lazily" | | 4 | "suddenly" | | 5 | "carefully" |
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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) | |
| 58.64% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2176 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "etched" | | 1 | "velvet" | | 2 | "weight" | | 3 | "silence" | | 4 | "pulse" | | 5 | "fluttered" | | 6 | "standard" | | 7 | "database" | | 8 | "perfect" | | 9 | "unspoken" | | 10 | "traced" | | 11 | "echoed" | | 12 | "whisper" | | 13 | "vibrated" | | 14 | "warmth" | | 15 | "eyebrow" |
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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 | 158 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 158 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 179 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2164 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 70 | | wordCount | 1638 | | uniqueNames | 9 | | maxNameDensity | 1.89 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 2 | | Quinn | 31 | | Tube | 1 | | Ellis | 9 | | Kowalski | 2 | | Eva | 19 | | Three | 1 | | Morris | 3 | | Detective | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Ellis" | | 3 | "Kowalski" | | 4 | "Eva" | | 5 | "Morris" |
| | places | | | globalScore | 0.554 | | windowScore | 0.333 | |
| 84.21% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 114 | | glossingSentenceCount | 3 | | matches | | 0 | "something like recognition" | | 1 | "ulse fluttered visibly at her throat, but" | | 2 | "something like grief" | | 3 | "as if inviting her to step through and see what lay on the other side" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 0.924 | | wordCount | 2164 | | matches | | 0 | "not north, but toward the far tunnel mouth" | | 1 | "not waver, but inside, something long buried stirred" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 179 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 57 | | mean | 37.96 | | std | 20.09 | | cv | 0.529 | | sampleLengths | | 0 | 88 | | 1 | 33 | | 2 | 28 | | 3 | 70 | | 4 | 28 | | 5 | 70 | | 6 | 10 | | 7 | 18 | | 8 | 50 | | 9 | 66 | | 10 | 16 | | 11 | 54 | | 12 | 22 | | 13 | 41 | | 14 | 23 | | 15 | 64 | | 16 | 20 | | 17 | 48 | | 18 | 38 | | 19 | 63 | | 20 | 10 | | 21 | 45 | | 22 | 55 | | 23 | 5 | | 24 | 49 | | 25 | 17 | | 26 | 63 | | 27 | 69 | | 28 | 11 | | 29 | 23 | | 30 | 44 | | 31 | 5 | | 32 | 27 | | 33 | 30 | | 34 | 73 | | 35 | 12 | | 36 | 45 | | 37 | 13 | | 38 | 43 | | 39 | 54 | | 40 | 12 | | 41 | 30 | | 42 | 22 | | 43 | 47 | | 44 | 56 | | 45 | 36 | | 46 | 52 | | 47 | 29 | | 48 | 36 | | 49 | 48 |
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| 89.72% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 158 | | matches | | 0 | "been sealed" | | 1 | "was singed" | | 2 | "been scratched" | | 3 | "been positioned" | | 4 | "been ripped" | | 5 | "been scorched" | | 6 | "was prepared" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 268 | | matches | | 0 | "was beginning" | | 1 | "was leaving" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 3 | | flaggedSentences | 10 | | totalSentences | 179 | | ratio | 0.056 | | matches | | 0 | "A bone token—small, ivory, etched with a single rune—lay discarded on the bottom step." | | 1 | "Male, mid-forties, dressed in a long coat of peculiar cut—too many pockets, too much velvet." | | 2 | "She pressed two fingers against the victim’s jaw; the skin was cold, but the rigor had not yet locked the limbs." | | 3 | "The victim’s shoes—expensive, strange glyphs tooled into the leather—were clean." | | 4 | "Protective marks had been scratched there—fresh, by the whiteness of the grooves." | | 5 | "The beam revealed more symbols on the tunnel wall—identical to those on the compass face and to the ones carved beside the body." | | 6 | "Yet the victim had clearly been positioned after death; the neat arrangement of his arms suggested ritual, not robbery." | | 7 | "Eva’s nervous habit had returned; she kept tucking the same curl behind her ear though it refused to stay." | | 8 | "The pages contained meticulous drawings of the crime scene—drawn before the police had arrived." | | 9 | "The body in front of her, the compass in her hand, the journal in her pocket—all of them insisted otherwise." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1653 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 55 | | adverbRatio | 0.03327283726557774 | | lyAdverbCount | 22 | | lyAdverbRatio | 0.013309134906231096 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 179 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 179 | | mean | 12.09 | | std | 8.42 | | cv | 0.697 | | sampleLengths | | 0 | 18 | | 1 | 25 | | 2 | 26 | | 3 | 14 | | 4 | 5 | | 5 | 17 | | 6 | 12 | | 7 | 2 | | 8 | 2 | | 9 | 16 | | 10 | 12 | | 11 | 5 | | 12 | 21 | | 13 | 21 | | 14 | 15 | | 15 | 8 | | 16 | 10 | | 17 | 18 | | 18 | 5 | | 19 | 21 | | 20 | 6 | | 21 | 6 | | 22 | 21 | | 23 | 11 | | 24 | 10 | | 25 | 4 | | 26 | 14 | | 27 | 4 | | 28 | 7 | | 29 | 18 | | 30 | 10 | | 31 | 11 | | 32 | 11 | | 33 | 16 | | 34 | 6 | | 35 | 2 | | 36 | 24 | | 37 | 7 | | 38 | 3 | | 39 | 13 | | 40 | 11 | | 41 | 43 | | 42 | 3 | | 43 | 19 | | 44 | 7 | | 45 | 7 | | 46 | 22 | | 47 | 5 | | 48 | 12 | | 49 | 11 |
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| 51.58% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3463687150837989 | | totalSentences | 179 | | uniqueOpeners | 62 | |
| 23.15% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 144 | | matches | | 0 | "Somewhere in the dark behind" |
| | ratio | 0.007 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 144 | | matches | | 0 | "She pocketed it without comment." | | 1 | "Her brown eyes swept the" | | 2 | "She pressed two fingers against" | | 3 | "she said quietly" | | 4 | "Her gaze tracked outward in" | | 5 | "She clutched the strap of" | | 6 | "Her freckled face looked paler" | | 7 | "She studied Eva for a" | | 8 | "she told Eva, then jerked" | | 9 | "She led Eva twenty paces" | | 10 | "They matched nothing in any" | | 11 | "She had never believed it." | | 12 | "She turned back toward the" | | 13 | "It was warm, far warmer" | | 14 | "She rose and followed its" | | 15 | "Her pulse kicked up a" | | 16 | "She did not ask how" | | 17 | "She swept the torch along" | | 18 | "She stared at it." | | 19 | "She forced her mind back" |
| | ratio | 0.222 | |
| 57.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 116 | | totalSentences | 144 | | matches | | 0 | "Detective Harlow Quinn descended the" | | 1 | "The air thickened as she" | | 2 | "Camden’s abandoned Tube station had" | | 3 | "A bone token—small, ivory, etched" | | 4 | "She pocketed it without comment." | | 5 | "Floodlights stuttered on the platform" | | 6 | "Sergeant Ellis straightened from beside" | | 7 | "Quinn gave a curt nod." | | 8 | "Her brown eyes swept the" | | 9 | "The victim lay supine near" | | 10 | "A faint smell of ozone" | | 11 | "Ellis offered, voice pitched low" | | 12 | "Quinn crouched beside the corpse." | | 13 | "The coat fell open to" | | 14 | "She pressed two fingers against" | | 15 | "Time of death did not" | | 16 | "she said quietly" | | 17 | "Ellis shifted his weight." | | 18 | "Quinn did not answer." | | 19 | "Her gaze tracked outward in" |
| | ratio | 0.806 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 144 | | matches | | 0 | "Whoever he was, he had" | | 1 | "If this had been a" | | 2 | "Even if they tore apart" | | 3 | "Even if Eva Kowalski and" |
| | ratio | 0.028 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 65 | | technicalSentenceCount | 2 | | matches | | 0 | "Shelves had been ripped from the walls, but one object remained untouched: a slender glass vial containing a single drop of quicksilver that moved against gravi…" | | 1 | "The needle continued pointing toward the impossible crack in the wall, as if inviting her to step through and see what lay on the other side." |
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| 9.62% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 3 | | matches | | 0 | "Ellis offered, voice pitched low" | | 1 | "Quinn’s jaw tightened, the sharp line catching the light" | | 2 | "she called, voice carrying down the tunnel with calm authority" |
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| 91.18% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 2 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "Quinn murmured (murmur)" |
| | dialogueSentences | 34 | | tagDensity | 0.265 | | leniency | 0.529 | | rawRatio | 0.222 | | effectiveRatio | 0.118 | |