| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.231 | | leniency | 0.462 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1319 | | totalAiIsmAdverbs | 4 | | 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) | |
| 20.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1319 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "echoing" | | 1 | "measured" | | 2 | "fractured" | | 3 | "gloom" | | 4 | "pulse" | | 5 | "glinting" | | 6 | "electric" | | 7 | "echoes" | | 8 | "footsteps" | | 9 | "echoed" | | 10 | "silence" | | 11 | "trembled" | | 12 | "whisper" | | 13 | "fluttered" | | 14 | "glint" | | 15 | "pulsed" | | 16 | "weight" | | 17 | "flickered" |
| |
| 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 | 153 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 153 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 162 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1303 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 60.79% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 1177 | | uniqueNames | 12 | | maxNameDensity | 1.78 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 21 | | Soho | 1 | | Desmond | 1 | | Morris | 4 | | Raven | 1 | | Nest | 1 | | London | 2 | | Tube | 1 | | Detective | 2 | | Europe | 1 | | Didn | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Desmond" | | 3 | "Morris" | | 4 | "Tube" | | 5 | "Detective" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "London" | | 3 | "Europe" |
| | globalScore | 0.608 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 80 | | glossingSentenceCount | 1 | | matches | | |
| 46.51% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.535 | | wordCount | 1303 | | matches | | 0 | "no bullet holes but" | | 1 | "not just damp concrete, but something electric, like ozone after a storm" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 162 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 35.22 | | std | 18.18 | | cv | 0.516 | | sampleLengths | | 0 | 64 | | 1 | 77 | | 2 | 55 | | 3 | 50 | | 4 | 67 | | 5 | 44 | | 6 | 10 | | 7 | 26 | | 8 | 58 | | 9 | 52 | | 10 | 59 | | 11 | 47 | | 12 | 38 | | 13 | 29 | | 14 | 9 | | 15 | 55 | | 16 | 33 | | 17 | 27 | | 18 | 42 | | 19 | 19 | | 20 | 31 | | 21 | 34 | | 22 | 32 | | 23 | 19 | | 24 | 33 | | 25 | 48 | | 26 | 33 | | 27 | 20 | | 28 | 15 | | 29 | 34 | | 30 | 12 | | 31 | 48 | | 32 | 23 | | 33 | 36 | | 34 | 9 | | 35 | 12 | | 36 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 153 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 201 | | matches | | 0 | "was already swinging" | | 1 | "was already rounding" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 17 | | semicolonCount | 0 | | flaggedSentences | 16 | | totalSentences | 162 | | ratio | 0.099 | | matches | | 0 | "Rain slashed down in silver sheets, turning neon signs into bleeding smears of color—blue, red, the occasional flash of sickly green from a distant pub sign." | | 1 | "She recognized the coat—belonged to someone from the clique Desmond had mentioned six months ago during that botched raid at the textile warehouse." | | 2 | "Quinn’s torch beam cut through the gloom, illuminating graffiti—some fresh, some faded by decades of damp." | | 3 | "The backroom door was already swinging shut—the same one that led to the hidden space behind the bookshelf." | | 4 | "Maps hung crooked on walls—some of London, some of places she didn’t recognize." | | 5 | "The air smelled different here—not just damp concrete, but something electric, like ozone after a storm." | | 6 | "A draft whispered up the stairwell, carrying voices—or echoes of ones she couldn’t catch." | | 7 | "Not with electricity—with something older." | | 8 | "A whisper—too distant to understand." | | 9 | "Brass would love this—Detective Quinn chasing a suspect into a supernatural black market." | | 10 | "A figure stood beneath a hanging light fixture—bare bulb swinging slightly, casting erratic shadows." | | 11 | "The light caught a glint—bone." | | 12 | "The suspect laughed—a dry, cracked sound." | | 13 | "The tunnel entrance flickered—like heat haze—then steadied." | | 14 | "Human face—almost." | | 15 | "She thought of Morris’s body—chest caved in, ribs spread like broken wings." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1197 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 45 | | adverbRatio | 0.03759398496240601 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.007518796992481203 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 162 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 162 | | mean | 8.04 | | std | 5.32 | | cv | 0.661 | | sampleLengths | | 0 | 16 | | 1 | 26 | | 2 | 5 | | 3 | 17 | | 4 | 17 | | 5 | 11 | | 6 | 3 | | 7 | 23 | | 8 | 23 | | 9 | 7 | | 10 | 9 | | 11 | 10 | | 12 | 11 | | 13 | 18 | | 14 | 8 | | 15 | 16 | | 16 | 7 | | 17 | 11 | | 18 | 5 | | 19 | 3 | | 20 | 4 | | 21 | 3 | | 22 | 14 | | 23 | 17 | | 24 | 9 | | 25 | 14 | | 26 | 3 | | 27 | 3 | | 28 | 3 | | 29 | 19 | | 30 | 15 | | 31 | 7 | | 32 | 10 | | 33 | 4 | | 34 | 10 | | 35 | 12 | | 36 | 4 | | 37 | 18 | | 38 | 5 | | 39 | 6 | | 40 | 18 | | 41 | 7 | | 42 | 10 | | 43 | 13 | | 44 | 18 | | 45 | 11 | | 46 | 9 | | 47 | 8 | | 48 | 16 | | 49 | 5 |
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| 53.83% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.3416149068322981 | | totalSentences | 161 | | uniqueOpeners | 55 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 8 | | totalSentences | 137 | | matches | | 0 | "Then a door slammed." | | 1 | "Too many secrets in this" | | 2 | "Just empty space." | | 3 | "Just silence and the distant" | | 4 | "Then a sound." | | 5 | "Only a sliver of movement." | | 6 | "Just the hollow drop of" | | 7 | "Just watched her." |
| | ratio | 0.058 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 137 | | matches | | 0 | "Her breath came steady, measured." | | 1 | "They moved with purpose, shoulders" | | 2 | "She recognized the coat—belonged to" | | 3 | "She didn’t pause." | | 4 | "She sprinted the last twenty" | | 5 | "She didn’t slow." | | 6 | "He jerked his chin toward" | | 7 | "She moved through the crowded" | | 8 | "She pushed through before it" | | 9 | "She followed it down rickety" | | 10 | "Her torch beam probed the" | | 11 | "Her palm rested on the" | | 12 | "She checked her watch again." | | 13 | "She tightened her grip on" | | 14 | "Her torch trembled slightly." | | 15 | "She stepped forward." | | 16 | "Her fingers brushed the wall." | | 17 | "She could call for backup." | | 18 | "Her jaw worked side to" | | 19 | "She didn’t need their permission." |
| | ratio | 0.234 | |
| 84.09% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 103 | | totalSentences | 137 | | matches | | 0 | "Detective Harlow Quinn's shoes slapped" | | 1 | "Rain slashed down in silver" | | 2 | "Her breath came steady, measured." | | 3 | "The figure ahead wore a" | | 4 | "They moved with purpose, shoulders" | | 5 | "Quinn’s jaw tightened." | | 6 | "She recognized the coat—belonged to" | | 7 | "The one where Morris’s body" | | 8 | "Quinn’s gloved fingers flexed around" | | 9 | "Streetlamps buzzed overhead, one flickering" | | 10 | "The suspect glanced back, eyes" | | 11 | "Recognition flashed across their face" | | 12 | "Quinn cursed under her breath" | | 13 | "The alley narrowed, slick brick" | | 14 | "Quinn’s torch beam cut through" | | 15 | "The suspect’s coat disappeared around" | | 16 | "Quinn rounded it too fast," | | 17 | "Paint peeled under her fingers." | | 18 | "She didn’t pause." | | 19 | "Quinn’s pulse spiked." |
| | ratio | 0.752 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 137 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 1 | | matches | | 0 | "Quinn cursed under her breath and followed, boots splashing through puddles that blurred neon reflections into fractured chaos." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |