| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said softly [softly]" |
| | dialogueSentences | 17 | | tagDensity | 0.588 | | leniency | 1 | | rawRatio | 0.1 | | effectiveRatio | 0.1 | |
| 91.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1111 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 73.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1111 | | totalAiIsms | 6 | | found | | 0 | | | 1 | | | 2 | | word | "down her spine" | | count | 1 |
| | 3 | | | 4 | | | 5 | |
| | highlights | | 0 | "calculating" | | 1 | "glint" | | 2 | "down her spine" | | 3 | "flickered" | | 4 | "pulsed" | | 5 | "comfortable" |
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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 | 75 | | matches | (empty) | |
| 66.67% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 75 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 67 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1118 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 935 | | uniqueNames | 13 | | maxNameDensity | 0.53 | | worstName | "Quinn" | | maxWindowNameDensity | 1 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | High | 1 | | Street | 1 | | Harlow | 1 | | Quinn | 5 | | Herrera | 1 | | Morris | 3 | | Transport | 1 | | London | 2 | | Seville | 1 | | Veil | 1 | | Market | 1 | | Tomás | 5 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Morris" | | 4 | "Tomás" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "London" | | 4 | "Seville" |
| | globalScore | 1 | | windowScore | 1 | |
| 98.98% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 1 | | matches | | 0 | "fabrics that seemed to drink the glow rather than reflect it" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1118 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 26 | | mean | 43 | | std | 35.14 | | cv | 0.817 | | sampleLengths | | 0 | 55 | | 1 | 87 | | 2 | 11 | | 3 | 6 | | 4 | 96 | | 5 | 65 | | 6 | 12 | | 7 | 90 | | 8 | 42 | | 9 | 28 | | 10 | 49 | | 11 | 12 | | 12 | 51 | | 13 | 44 | | 14 | 4 | | 15 | 4 | | 16 | 30 | | 17 | 6 | | 18 | 130 | | 19 | 106 | | 20 | 65 | | 21 | 9 | | 22 | 53 | | 23 | 38 | | 24 | 21 | | 25 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 75 | | matches | | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 142 | | matches | | 0 | "was making" | | 1 | "was just running" | | 2 | "was running" | | 3 | "was breathing" | | 4 | "was singing" | | 5 | "was waiting" |
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| 3.48% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 82 | | ratio | 0.049 | | matches | | 0 | "Eighteen years on the job had taught Quinn the geometry of a foot chase — when to cut a corner, when to commit, when a runner was making for somewhere specific and when he was just running scared." | | 1 | "The alley spat her out into a dead-end yard — and there, against the far wall, was the thing she'd been chasing toward without knowing it." | | 2 | "\"You don't understand what's down here.\" He held up the thing in his hand — small, pale, the size of a domino." | | 3 | "Through the widening gap she could see it — a platform, the old tiled walls still clinging to fragments of advertisements for soap and cigarettes, and stalls." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 645 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.023255813953488372 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.006201550387596899 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 13.63 | | std | 11.53 | | cv | 0.846 | | sampleLengths | | 0 | 26 | | 1 | 29 | | 2 | 4 | | 3 | 4 | | 4 | 32 | | 5 | 4 | | 6 | 30 | | 7 | 13 | | 8 | 9 | | 9 | 2 | | 10 | 3 | | 11 | 3 | | 12 | 38 | | 13 | 3 | | 14 | 13 | | 15 | 4 | | 16 | 38 | | 17 | 21 | | 18 | 13 | | 19 | 1 | | 20 | 7 | | 21 | 23 | | 22 | 7 | | 23 | 5 | | 24 | 26 | | 25 | 2 | | 26 | 31 | | 27 | 14 | | 28 | 17 | | 29 | 15 | | 30 | 27 | | 31 | 12 | | 32 | 10 | | 33 | 6 | | 34 | 25 | | 35 | 24 | | 36 | 5 | | 37 | 2 | | 38 | 5 | | 39 | 22 | | 40 | 4 | | 41 | 7 | | 42 | 18 | | 43 | 13 | | 44 | 4 | | 45 | 27 | | 46 | 4 | | 47 | 4 | | 48 | 7 | | 49 | 4 |
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| 91.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5853658536585366 | | totalSentences | 82 | | uniqueOpeners | 48 | |
| 99.50% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 67 | | matches | | 0 | "Then he was gone again," | | 1 | "Somewhere a voice was singing" |
| | ratio | 0.03 | |
| 88.66% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 67 | | matches | | 0 | "She'd give him that." | | 1 | "He glanced back once." | | 2 | "Her voice tore loose, swallowed" | | 3 | "He didn't stop." | | 4 | "They never did." | | 5 | "He had a destination." | | 6 | "He'd led her off the" | | 7 | "She pushed harder, lungs burning," | | 8 | "Her partner used to joke" | | 9 | "She didn't let herself think" | | 10 | "He turned, saw her at" | | 11 | "His accent rounded the words," | | 12 | "He was breathing hard, one" | | 13 | "She came down two steps," | | 14 | "He held up the thing" | | 15 | "He went very still." | | 16 | "he said softly" | | 17 | "She hadn't said it." | | 18 | "She was certain she hadn't" | | 19 | "She got to the bottom" |
| | ratio | 0.328 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 48 | | totalSentences | 67 | | matches | | 0 | "The rain came down like" | | 1 | "Detective Harlow Quinn ran through" | | 2 | "Tomás Herrera could move." | | 3 | "She'd give him that." | | 4 | "The former paramedic cut between" | | 5 | "He glanced back once." | | 6 | "Her voice tore loose, swallowed" | | 7 | "He didn't stop." | | 8 | "They never did." | | 9 | "Tomás wasn't scared." | | 10 | "That was what set the" | | 11 | "He had a destination." | | 12 | "He'd led her off the" | | 13 | "She pushed harder, lungs burning," | | 14 | "Her partner used to joke" | | 15 | "Morris, with his terrible coffee" | | 16 | "She didn't let herself think" | | 17 | "The alley spat her out" | | 18 | "Iron-railed, descending into the earth" | | 19 | "Tomás was at the bottom" |
| | ratio | 0.716 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 67 | | matches | (empty) | | ratio | 0 | |
| 75.89% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 3 | | matches | | 0 | "She pushed harder, lungs burning, the worn leather strap of her watch chafing against her wrist as she pumped her arms." | | 1 | "Iron-railed, descending into the earth beside a defunct ventilation grate, the kind of access shaft that belonged to one of the dozens of ghost stations buried …" | | 2 | "Warm air breathed out of the gap, carrying smells that didn't belong eighty feet under Camden: incense, and copper, and something floral and chemical that made …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.294 | | leniency | 0.588 | | rawRatio | 0 | | effectiveRatio | 0 | |