| 57.14% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva said quickly [quickly]" | | 1 | "Harlow echoed softly [softly]" |
| | dialogueSentences | 28 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0.167 | | effectiveRatio | 0.143 | |
| 63.77% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1656 | | totalAiIsmAdverbs | 12 | | found | | | highlights | | 0 | "nervously" | | 1 | "very" | | 2 | "quickly" | | 3 | "completely" | | 4 | "softly" | | 5 | "perfectly" | | 6 | "slightly" | | 7 | "utterly" | | 8 | "suddenly" | | 9 | "precisely" |
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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) | |
| 39.61% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1656 | | totalAiIsms | 20 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "measured" | | 1 | "rhythmic" | | 2 | "gloom" | | 3 | "imposing" | | 4 | "perfect" | | 5 | "familiar" | | 6 | "depths" | | 7 | "cataloged" | | 8 | "echoing" | | 9 | "echoed" | | 10 | "weight" | | 11 | "predictable" | | 12 | "macabre" | | 13 | "methodical" | | 14 | "etched" | | 15 | "magnetic" | | 16 | "firmly" | | 17 | "absolutely" | | 18 | "beacon" | | 19 | "facade" |
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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 | 99 | | matches | (empty) | |
| 99.57% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 99 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 115 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1646 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 61 | | wordCount | 1195 | | uniqueNames | 14 | | maxNameDensity | 2.43 | | worstName | "Harlow" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Harlow" | | discoveredNames | | Tube | 1 | | Camden | 2 | | Harlow | 29 | | Quinn | 1 | | Victorian | 1 | | Morris | 2 | | Metropolitan | 1 | | Police | 1 | | Kowalski | 1 | | Eva | 17 | | London | 2 | | God | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Morris" | | 4 | "Kowalski" | | 5 | "Eva" | | 6 | "God" |
| | places | | | globalScore | 0.287 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 84 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1646 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 115 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 51.44 | | std | 29.63 | | cv | 0.576 | | sampleLengths | | 0 | 95 | | 1 | 122 | | 2 | 68 | | 3 | 76 | | 4 | 105 | | 5 | 12 | | 6 | 24 | | 7 | 40 | | 8 | 12 | | 9 | 60 | | 10 | 41 | | 11 | 71 | | 12 | 26 | | 13 | 80 | | 14 | 16 | | 15 | 45 | | 16 | 84 | | 17 | 30 | | 18 | 35 | | 19 | 60 | | 20 | 17 | | 21 | 93 | | 22 | 25 | | 23 | 38 | | 24 | 3 | | 25 | 75 | | 26 | 38 | | 27 | 49 | | 28 | 59 | | 29 | 54 | | 30 | 72 | | 31 | 21 |
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| 98.17% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 99 | | matches | | 0 | "was involved" | | 1 | "were locked" |
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| 94.18% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 189 | | matches | | 0 | "was acting" | | 1 | "was pulling" | | 2 | "was hiding" |
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| 93.17% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 115 | | ratio | 0.017 | | matches | | 0 | "She knew the young archivist ran with a tight circle of friends—a deeply secretive clique that Harlow heavily suspected was involved in a whole string of unsolved, unnatural crimes across London." | | 1 | "The face was completely etched with dense, overlapping protective sigils—lines of geometry that made Harlow’s eyes water slightly just looking at them." |
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| 87.81% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1203 | | adjectiveStacks | 1 | | stackExamples | | 0 | "dense, overlapping protective sigils—" |
| | adverbCount | 43 | | adverbRatio | 0.03574397339983375 | | lyAdverbCount | 33 | | lyAdverbRatio | 0.02743142144638404 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 115 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 115 | | mean | 14.31 | | std | 9.64 | | cv | 0.673 | | sampleLengths | | 0 | 17 | | 1 | 24 | | 2 | 32 | | 3 | 22 | | 4 | 16 | | 5 | 17 | | 6 | 5 | | 7 | 12 | | 8 | 3 | | 9 | 8 | | 10 | 31 | | 11 | 8 | | 12 | 20 | | 13 | 2 | | 14 | 26 | | 15 | 15 | | 16 | 11 | | 17 | 16 | | 18 | 15 | | 19 | 26 | | 20 | 17 | | 21 | 18 | | 22 | 11 | | 23 | 5 | | 24 | 15 | | 25 | 23 | | 26 | 15 | | 27 | 5 | | 28 | 31 | | 29 | 12 | | 30 | 11 | | 31 | 13 | | 32 | 9 | | 33 | 31 | | 34 | 7 | | 35 | 5 | | 36 | 10 | | 37 | 50 | | 38 | 9 | | 39 | 13 | | 40 | 19 | | 41 | 4 | | 42 | 11 | | 43 | 56 | | 44 | 4 | | 45 | 11 | | 46 | 11 | | 47 | 12 | | 48 | 30 | | 49 | 29 |
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| 48.70% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3391304347826087 | | totalSentences | 115 | | uniqueOpeners | 39 | |
| 34.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 97 | | matches | | 0 | "Predictably, Eva’s right hand drifted" |
| | ratio | 0.01 | |
| 88.04% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 97 | | matches | | 0 | "She pushed a stray lock" | | 1 | "She paused at the bottom" | | 2 | "She was forty-one years old," | | 3 | "It was the young woman" | | 4 | "She stood five foot four," | | 5 | "Her bright green eyes flared" | | 6 | "It was a nervous habit" | | 7 | "She knew the young archivist" | | 8 | "She crouched beside the victim," | | 9 | "His neck was broken, yes," | | 10 | "She pointed a gloved finger" | | 11 | "She tucked another curl of" | | 12 | "She checked her watch again" | | 13 | "She knelt again, examining the" | | 14 | "His fingers were locked in" | | 15 | "She pulled a pen from" | | 16 | "It flipped over, revealing an" | | 17 | "She resumed her methodical grid" | | 18 | "She trusted her own eyes," | | 19 | "Her military bearing kept her" |
| | ratio | 0.33 | |
| 11.55% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 87 | | totalSentences | 97 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn descended the" | | 2 | "She pushed a stray lock" | | 3 | "She paused at the bottom" | | 4 | "The glow of her flashlight" | | 5 | "The moon phase complication on" | | 6 | "A full moon." | | 7 | "A familiar, hollow ache settled" | | 8 | "DS Morris had gone missing" | | 9 | "Harlow pushed the ghost of" | | 10 | "She was forty-one years old," | | 11 | "A body lay in the" | | 12 | "It was the young woman" | | 13 | "Eva Kowalski looked hopelessly out" | | 14 | "She stood five foot four," | | 15 | "The harsh work lights washed" | | 16 | "Harlow stepped onto the platform," | | 17 | "Eva turned at the sound." | | 18 | "Her bright green eyes flared" | | 19 | "It was a nervous habit" |
| | ratio | 0.897 | |
| 51.55% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 97 | | matches | | 0 | "Before Eva could sputter a" |
| | ratio | 0.01 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 3 | | matches | | 0 | "Predictably, Eva’s right hand drifted up, Her fingers catching a lock of curly red hair and tucking it securely behind her left ear." | | 1 | "The face was completely etched with dense, overlapping protective sigils—lines of geometry that made Harlow’s eyes water slightly just looking at them." | | 2 | "The structured market that evaporated precisely on the full moon." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 3 | | matches | | 0 | "Eva said, her voice echoing faintly off the curved ceiling" | | 1 | "Eva offered, her voice pitching slightly higher" | | 2 | "Harlow warned, her voice dropping to a dangerous register" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 28 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0.125 | | effectiveRatio | 0.071 | |