| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 21 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1132 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "sharply" | | 1 | "warily" | | 2 | "really" |
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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) | |
| 20.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1132 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "reminder" | | 1 | "beacon" | | 2 | "pounding" | | 3 | "footsteps" | | 4 | "echoed" | | 5 | "shimmered" | | 6 | "pulse" | | 7 | "quickened" | | 8 | "racing" | | 9 | "echoing" | | 10 | "rhythmic" | | 11 | "otherworldly" | | 12 | "trembled" | | 13 | "porcelain" | | 14 | "loomed" | | 15 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 97 | | matches | | 0 | "filled with fear" | | 1 | "d with fear" |
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| 98.67% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 97 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 2 | | totalWords | 1119 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 67.72% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1033 | | uniqueNames | 11 | | maxNameDensity | 1.65 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 17 | | Soho | 1 | | Raven | 1 | | Nest | 1 | | London | 1 | | Morris | 2 | | Tube | 1 | | Camden | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Morris" | | 5 | "Camden" |
| | places | | | globalScore | 0.677 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 80 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1119 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 109 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 31.08 | | std | 22.62 | | cv | 0.728 | | sampleLengths | | 0 | 83 | | 1 | 10 | | 2 | 72 | | 3 | 59 | | 4 | 56 | | 5 | 10 | | 6 | 10 | | 7 | 64 | | 8 | 7 | | 9 | 74 | | 10 | 40 | | 11 | 54 | | 12 | 23 | | 13 | 41 | | 14 | 13 | | 15 | 13 | | 16 | 11 | | 17 | 10 | | 18 | 14 | | 19 | 15 | | 20 | 18 | | 21 | 38 | | 22 | 16 | | 23 | 12 | | 24 | 9 | | 25 | 10 | | 26 | 65 | | 27 | 34 | | 28 | 7 | | 29 | 42 | | 30 | 37 | | 31 | 47 | | 32 | 49 | | 33 | 31 | | 34 | 6 | | 35 | 19 |
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| 98.03% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 97 | | matches | | 0 | "were lined" | | 1 | "been closed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 194 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 109 | | ratio | 0.055 | | matches | | 0 | "Ahead, the suspect—a wiry figure in a dark hood—darted through the maze of Soho alleyways, weaving between overflowing bins and startled pedestrians." | | 1 | "She hesitated for a fraction of a second—enough to let the suspect gain ground." | | 2 | "Inside, the air changed—cooler, heavier." | | 3 | "The third stall was a ramshackle setup, its vendor—a wiry man with greasy hair—eyeing her warily." | | 4 | "The suspect stumbled, their face finally exposed—a young man, barely out of his teens, his wide eyes filled with fear and something else." | | 5 | "Quinn felt it before she saw it—the pressure, the pull." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1046 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.028680688336520075 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.0124282982791587 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 10.27 | | std | 5.31 | | cv | 0.517 | | sampleLengths | | 0 | 16 | | 1 | 22 | | 2 | 15 | | 3 | 13 | | 4 | 17 | | 5 | 10 | | 6 | 15 | | 7 | 20 | | 8 | 21 | | 9 | 14 | | 10 | 2 | | 11 | 15 | | 12 | 18 | | 13 | 8 | | 14 | 18 | | 15 | 14 | | 16 | 17 | | 17 | 18 | | 18 | 7 | | 19 | 10 | | 20 | 9 | | 21 | 1 | | 22 | 13 | | 23 | 10 | | 24 | 5 | | 25 | 15 | | 26 | 21 | | 27 | 7 | | 28 | 9 | | 29 | 9 | | 30 | 8 | | 31 | 6 | | 32 | 4 | | 33 | 2 | | 34 | 17 | | 35 | 11 | | 36 | 8 | | 37 | 9 | | 38 | 11 | | 39 | 17 | | 40 | 3 | | 41 | 15 | | 42 | 14 | | 43 | 3 | | 44 | 12 | | 45 | 10 | | 46 | 10 | | 47 | 13 | | 48 | 9 | | 49 | 6 |
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| 48.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3486238532110092 | | totalSentences | 109 | | uniqueOpeners | 38 | |
| 36.23% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 92 | | matches | | | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 92 | | matches | | 0 | "She didn’t need to see" | | 1 | "she barked, her voice slicing" | | 2 | "She hesitated for a fraction" | | 3 | "She surged forward, her heart" | | 4 | "She yanked it open, her" | | 5 | "She shot him a look," | | 6 | "she hissed, yanking it open" | | 7 | "Her mind flashed to DS" | | 8 | "She descended the stairs, her" | | 9 | "She’d heard rumors of this" | | 10 | "She didn’t have a bone" | | 11 | "She didn’t even know what" | | 12 | "she said, flashing her badge" | | 13 | "She clenched her teeth, her" | | 14 | "She moved swiftly, her boots" | | 15 | "she ordered, her hand resting" | | 16 | "She caught a glimpse of" | | 17 | "Her hand closed around the" | | 18 | "Her instincts screamed at her" | | 19 | "His voice rose, the words" |
| | ratio | 0.25 | |
| 8.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 92 | | matches | | 0 | "Detective Harlow Quinn’s boots splashed" | | 1 | "Quinn clenched her jaw, her" | | 2 | "She didn’t need to see" | | 3 | "The battered leather watch on" | | 4 | "she barked, her voice slicing" | | 5 | "The hooded figure glanced over" | | 6 | "Quinn cursed under her breath," | | 7 | "The suspect veered sharply into" | | 8 | "She hesitated for a fraction" | | 9 | "She surged forward, her heart" | | 10 | "The alley opened up into" | | 11 | "Quinn reached it just as" | | 12 | "She yanked it open, her" | | 13 | "The air inside was thick" | | 14 | "The walls were lined with" | | 15 | "The bar stretched out before" | | 16 | "Quinn didn’t have time for" | | 17 | "the bartender muttered, his voice" | | 18 | "She shot him a look," | | 19 | "The hidden door stood behind" |
| | ratio | 0.902 | |
| 54.35% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 92 | | matches | | 0 | "Before she could react, the" |
| | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 3 | | matches | | 0 | "She surged forward, her heart pounding in sync with her boots hitting the wet pavement." | | 1 | "Stalls lined the tracks, their vendors hawking goods that shimmered unnaturally in the low light." | | 2 | "The creature loomed over him, its form shifting and writhing, a mass of darkness with eyes that burned like embers." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 5 | | matches | | 0 | "she barked, her voice slicing through the storm" | | 1 | "the bartender muttered, his voice low and gravelly" | | 2 | "Quinn said, her voice steady despite the adrenaline coursing through her veins" | | 3 | "she ordered, her hand resting on her weapon" | | 4 | "Quinn said, her grip tightening" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 4 | | fancyTags | | 0 | "she barked (bark)" | | 1 | "the bartender muttered (mutter)" | | 2 | "she hissed (hiss)" | | 3 | "she ordered (order)" |
| | dialogueSentences | 21 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0.444 | | effectiveRatio | 0.381 | |