| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 1 | | adverbTags | | 0 | "Then he plunged [Then]" |
| | dialogueSentences | 9 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.25 | | effectiveRatio | 0.222 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 985 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 54.31% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 985 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "pounding" | | 1 | "streaming" | | 2 | "symphony" | | 3 | "flickered" | | 4 | "pulsed" | | 5 | "depths" | | 6 | "chaotic" | | 7 | "whisper" | | 8 | "familiar" |
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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 | 1 | | narrationSentences | 87 | | matches | | |
| 93.60% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 87 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 93 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 981 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 902 | | uniqueNames | 21 | | maxNameDensity | 0.89 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 8 | | Dean | 1 | | Street | 1 | | Morris | 2 | | Tottenham | 1 | | Court | 1 | | Road | 2 | | Charing | 1 | | Cross | 1 | | Herrera | 5 | | Raven | 1 | | Nest | 1 | | Covent | 1 | | Garden | 1 | | Bloomsbury | 1 | | Saint | 1 | | Christopher | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Herrera" | | 4 | "Raven" | | 5 | "Saint" | | 6 | "Christopher" |
| | places | | 0 | "Soho" | | 1 | "Dean" | | 2 | "Street" | | 3 | "Tottenham" | | 4 | "Court" | | 5 | "Road" | | 6 | "Charing" | | 7 | "Cross" | | 8 | "Covent" | | 9 | "Garden" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 3.058 | | wordCount | 981 | | matches | | 0 | "not with fear, but with a frantic urgency" | | 1 | "not in surrender, but as if to ward her off" | | 2 | "not a room, but a descending staircase, lit by a faint, sourceless greenish" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 93 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 26 | | mean | 37.73 | | std | 22.73 | | cv | 0.602 | | sampleLengths | | 0 | 64 | | 1 | 76 | | 2 | 47 | | 3 | 3 | | 4 | 44 | | 5 | 58 | | 6 | 61 | | 7 | 43 | | 8 | 3 | | 9 | 49 | | 10 | 51 | | 11 | 66 | | 12 | 7 | | 13 | 29 | | 14 | 18 | | 15 | 26 | | 16 | 2 | | 17 | 73 | | 18 | 28 | | 19 | 51 | | 20 | 35 | | 21 | 58 | | 22 | 10 | | 23 | 47 | | 24 | 23 | | 25 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 87 | | matches | | |
| 97.44% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 130 | | matches | | 0 | "was heading" | | 1 | "was tiring" |
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| 19.97% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 93 | | ratio | 0.043 | | matches | | 0 | "The figure—male, lean, wearing a dark hoodie—glanced back, his face a pale oval under the streetlamp before he vanished into an alleyway." | | 1 | "Instead of answering, he yanked something from his pocket—a small, pale object." | | 2 | "A wave of air washed out—cold, carrying the scent of ozone, exotic spices, and something metallic, like old blood." | | 3 | "From the depths, she heard a murmur—the distant, chaotic buzz of a crowd, the clink of glass, a low, melodic chant that raised the hairs on her arms." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 164 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 1 | | adverbRatio | 0.006097560975609756 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 93 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 93 | | mean | 10.55 | | std | 6.58 | | cv | 0.624 | | sampleLengths | | 0 | 20 | | 1 | 23 | | 2 | 21 | | 3 | 9 | | 4 | 14 | | 5 | 2 | | 6 | 32 | | 7 | 19 | | 8 | 22 | | 9 | 19 | | 10 | 4 | | 11 | 2 | | 12 | 3 | | 13 | 15 | | 14 | 12 | | 15 | 14 | | 16 | 3 | | 17 | 12 | | 18 | 11 | | 19 | 8 | | 20 | 8 | | 21 | 7 | | 22 | 8 | | 23 | 4 | | 24 | 15 | | 25 | 10 | | 26 | 24 | | 27 | 12 | | 28 | 10 | | 29 | 2 | | 30 | 2 | | 31 | 15 | | 32 | 14 | | 33 | 3 | | 34 | 8 | | 35 | 9 | | 36 | 11 | | 37 | 3 | | 38 | 14 | | 39 | 4 | | 40 | 8 | | 41 | 17 | | 42 | 4 | | 43 | 9 | | 44 | 5 | | 45 | 8 | | 46 | 11 | | 47 | 16 | | 48 | 13 | | 49 | 9 |
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| 54.12% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3763440860215054 | | totalSentences | 93 | | uniqueOpeners | 35 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 79 | | matches | | 0 | "Then he ran faster." | | 1 | "Instead of answering, he yanked" | | 2 | "Then he plunged down the" |
| | ratio | 0.038 | |
| 78.23% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 79 | | matches | | 0 | "She pushed harder, the muscles" | | 1 | "Her worn leather watch strap" | | 2 | "She shoved the memory down," | | 3 | "She didn’t draw it." | | 4 | "Her command was swallowed by" | | 5 | "He slipped through." | | 6 | "She reached the gate, shoved" | | 7 | "He was heading north, towards" | | 8 | "She followed, her mind mapping" | | 9 | "He was moving with purpose," | | 10 | "He cut across the traffic" | | 11 | "She caught a better glimpse" | | 12 | "He faltered for a half-step," | | 13 | "Their eyes met across thirty" | | 14 | "His were wide, not with" | | 15 | "He didn’t stop." | | 16 | "He raised a hand, not" | | 17 | "Her clothes were a second" | | 18 | "He ducked into the brick" | | 19 | "He spun, his back against" |
| | ratio | 0.354 | |
| 29.62% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 79 | | matches | | 0 | "The rain fell in relentless," | | 1 | "Detective Harlow Quinn’s breath came" | | 2 | "She pushed harder, the muscles" | | 3 | "Her worn leather watch strap" | | 4 | "She shoved the memory down," | | 5 | "The figure—male, lean, wearing a" | | 6 | "Quinn skidded around the corner," | | 7 | "She didn’t draw it." | | 8 | "Her command was swallowed by" | | 9 | "The alley was a canyon" | | 10 | "The suspect was already at" | | 11 | "He slipped through." | | 12 | "Quinn sprinted, rainwater streaming from" | | 13 | "She reached the gate, shoved" | | 14 | "He was heading north, towards" | | 15 | "She followed, her mind mapping" | | 16 | "He was moving with purpose," | | 17 | "This was a route." | | 18 | "He cut across the traffic" | | 19 | "Quinn wove through the stalled" |
| | ratio | 0.861 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 2 | | matches | | 0 | "Detective Harlow Quinn’s breath came in sharp clouds, her boots slapping against the wet concrete with a rhythm that matched her pounding heart." | | 1 | "From the depths, she heard a murmur—the distant, chaotic buzz of a crowd, the clink of glass, a low, melodic chant that raised the hairs on her arms." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 38.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 9 | | tagDensity | 0.111 | | leniency | 0.222 | | rawRatio | 1 | | effectiveRatio | 0.222 | |