| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Davies said quietly [quietly]" |
| | dialogueSentences | 37 | | tagDensity | 0.459 | | leniency | 0.919 | | rawRatio | 0.059 | | effectiveRatio | 0.054 | |
| 92.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1394 | | 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) | |
| 78.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1394 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "flickered" | | 1 | "pulse" | | 2 | "traced" | | 3 | "etched" | | 4 | "trembled" |
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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 | 79 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 79 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 99 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 13 | | totalWords | 1394 | | ratio | 0.009 | | matches | | 0 | "look closer, Quinn, the evidence doesn't care what you want it to mean" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 98.98% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 980 | | uniqueNames | 8 | | maxNameDensity | 1.02 | | worstName | "Davies" | | maxWindowNameDensity | 2 | | worstWindowName | "Davies" | | discoveredNames | | Camden | 2 | | TfL | 1 | | Davies | 10 | | Quinn | 7 | | Tuesday | 1 | | Shade | 1 | | Veil | 1 | | Market | 1 |
| | persons | | | places | | | globalScore | 0.99 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | 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 | 1394 | | matches | (empty) | |
| 99.33% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 99 | | matches | | 0 | "kept that file" | | 1 | "rolling, that someone" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 31.68 | | std | 27.18 | | cv | 0.858 | | sampleLengths | | 0 | 13 | | 1 | 103 | | 2 | 17 | | 3 | 56 | | 4 | 42 | | 5 | 29 | | 6 | 28 | | 7 | 11 | | 8 | 62 | | 9 | 38 | | 10 | 82 | | 11 | 6 | | 12 | 42 | | 13 | 12 | | 14 | 23 | | 15 | 74 | | 16 | 7 | | 17 | 5 | | 18 | 56 | | 19 | 11 | | 20 | 52 | | 21 | 41 | | 22 | 66 | | 23 | 1 | | 24 | 6 | | 25 | 36 | | 26 | 24 | | 27 | 11 | | 28 | 72 | | 29 | 17 | | 30 | 35 | | 31 | 5 | | 32 | 33 | | 33 | 28 | | 34 | 37 | | 35 | 6 | | 36 | 5 | | 37 | 2 | | 38 | 82 | | 39 | 8 | | 40 | 5 | | 41 | 89 | | 42 | 9 | | 43 | 7 |
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| 74.17% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 79 | | matches | | 0 | "been placed" | | 1 | "been decommissioned" | | 2 | "been dragged" | | 3 | "were carved" | | 4 | "been pried" | | 5 | "was etched" | | 6 | "been found" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 170 | | matches | | 0 | "was waiting" | | 1 | "was rolling" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 99 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 982 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.035641547861507125 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.006109979633401222 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 99 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 99 | | mean | 14.08 | | std | 10.33 | | cv | 0.734 | | sampleLengths | | 0 | 13 | | 1 | 27 | | 2 | 24 | | 3 | 27 | | 4 | 4 | | 5 | 4 | | 6 | 17 | | 7 | 12 | | 8 | 1 | | 9 | 4 | | 10 | 7 | | 11 | 21 | | 12 | 28 | | 13 | 10 | | 14 | 5 | | 15 | 21 | | 16 | 6 | | 17 | 7 | | 18 | 9 | | 19 | 13 | | 20 | 18 | | 21 | 10 | | 22 | 11 | | 23 | 5 | | 24 | 26 | | 25 | 6 | | 26 | 25 | | 27 | 5 | | 28 | 15 | | 29 | 18 | | 30 | 29 | | 31 | 15 | | 32 | 20 | | 33 | 3 | | 34 | 3 | | 35 | 12 | | 36 | 6 | | 37 | 22 | | 38 | 20 | | 39 | 12 | | 40 | 23 | | 41 | 8 | | 42 | 23 | | 43 | 28 | | 44 | 5 | | 45 | 10 | | 46 | 7 | | 47 | 5 | | 48 | 26 | | 49 | 30 |
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| 72.39% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.46464646464646464 | | totalSentences | 99 | | uniqueOpeners | 46 | |
| 91.32% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 73 | | matches | | 0 | "Still had it, in the" | | 1 | "Somewhere beyond the reach of" |
| | ratio | 0.027 | |
| 61.10% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 73 | | matches | | 0 | "He was male, early thirties," | | 1 | "His eyes were open." | | 2 | "His mouth was open." | | 3 | "She pulled on her gloves" | | 4 | "He stood at the top" | | 5 | "He looked the way he" | | 6 | "She photographed it from three" | | 7 | "His shoes crunched on something," | | 8 | "She shifted onto her heels" | | 9 | "She looked around the platform." | | 10 | "She photographed them without touching," | | 11 | "She pushed the thought away" | | 12 | "She stood and crossed to" | | 13 | "She had kept that file." | | 14 | "She held up her phone," | | 15 | "She pointed at the victim" | | 16 | "She followed it with her" | | 17 | "He looked up from his" | | 18 | "She motioned him over." | | 19 | "He came, reluctant, and peered" |
| | ratio | 0.397 | |
| 14.79% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 73 | | matches | | 0 | "The bone token lay on" | | 1 | "Quinn crouched at the base" | | 2 | "The fluorescent strips overhead buzzed" | | 3 | "He was male, early thirties," | | 4 | "His eyes were open." | | 5 | "His mouth was open." | | 6 | "She pulled on her gloves" | | 7 | "Hours old, at least." | | 8 | "Davies's voice carried down the" | | 9 | "He stood at the top" | | 10 | "He looked the way he" | | 11 | "Quinn tilted the victim's head" | | 12 | "The tongue offered no resistance." | | 13 | "The bone token sat perfectly" | | 14 | "She photographed it from three" | | 15 | "Davies descended the last few" | | 16 | "His shoes crunched on something," | | 17 | "She shifted onto her heels" | | 18 | "Davies shrugged, a gesture that" | | 19 | "She looked around the platform." |
| | ratio | 0.89 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 37.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 5 | | matches | | 0 | "The fluorescent strips overhead buzzed and flickered, casting the scene in a sickly pallor that turned the victim's face the colour of wet plaster." | | 1 | "He was male, early thirties, sprawled on his back with his arms folded neatly across his chest, as though someone had arranged him after he stopped breathing." | | 2 | "Davies shrugged, a gesture that said he found the distinction academic." | | 3 | "The casing had a patina of verdigris that caught the fluorescent light, and its face was etched with protective sigils she could not read." | | 4 | "Quinn pocketed the compass and took one step toward the gap before a voice crackled from the radio on her shoulder, sharp and urgent, her sergeant's voice telli…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 37 | | tagDensity | 0.135 | | leniency | 0.27 | | rawRatio | 0.2 | | effectiveRatio | 0.054 | |