| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 58 | | tagDensity | 0.328 | | leniency | 0.655 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1650 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "perfectly" | | 2 | "really" | | 3 | "carefully" | | 4 | "very" |
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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) | |
| 63.64% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1650 | | totalAiIsms | 12 | | found | | 0 | | | 1 | | | 2 | | word | "carried the weight" | | count | 1 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | |
| | highlights | | 0 | "familiar" | | 1 | "echoed" | | 2 | "carried the weight" | | 3 | "standard" | | 4 | "shattered" | | 5 | "aligned" | | 6 | "traced" | | 7 | "footsteps" | | 8 | "flickered" | | 9 | "pumping" | | 10 | "etched" |
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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 | 124 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 124 | | filterMatches | (empty) | | hedgeMatches | | |
| 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 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 10 | | totalWords | 1648 | | ratio | 0.006 | | matches | | 0 | "exsanguination" | | 1 | "impossible wound geometry" | | 2 | "MIDNIGHT STANDARD" | | 3 | "dried" | | 4 | "KOWALSKI" | | 5 | "MIDNIGHT STANDARD" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1109 | | uniqueNames | 9 | | maxNameDensity | 1.62 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Quinn | 18 | | London | 1 | | Dawes | 5 | | Eva | 17 | | Aurora | 3 | | Morris | 2 | | Which | 1 | | Maglite | 2 | | Tube | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Dawes" | | 2 | "Eva" | | 3 | "Morris" | | 4 | "Which" |
| | places | | | globalScore | 0.688 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | 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 | 1648 | | matches | (empty) | |
| 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 | 77 | | mean | 21.4 | | std | 16.68 | | cv | 0.779 | | sampleLengths | | 0 | 47 | | 1 | 19 | | 2 | 3 | | 3 | 44 | | 4 | 12 | | 5 | 23 | | 6 | 8 | | 7 | 38 | | 8 | 62 | | 9 | 9 | | 10 | 54 | | 11 | 4 | | 12 | 6 | | 13 | 12 | | 14 | 63 | | 15 | 5 | | 16 | 20 | | 17 | 23 | | 18 | 63 | | 19 | 3 | | 20 | 3 | | 21 | 46 | | 22 | 12 | | 23 | 36 | | 24 | 7 | | 25 | 40 | | 26 | 8 | | 27 | 20 | | 28 | 20 | | 29 | 29 | | 30 | 10 | | 31 | 3 | | 32 | 32 | | 33 | 43 | | 34 | 7 | | 35 | 36 | | 36 | 3 | | 37 | 21 | | 38 | 6 | | 39 | 19 | | 40 | 20 | | 41 | 18 | | 42 | 1 | | 43 | 26 | | 44 | 45 | | 45 | 10 | | 46 | 12 | | 47 | 17 | | 48 | 29 | | 49 | 15 |
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| 99.60% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 124 | | matches | | 0 | "been cleaned" | | 1 | "was clenched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 188 | | matches | (empty) | |
| 72.31% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 162 | | ratio | 0.025 | | matches | | 0 | "The cuts on his chest had bled heavily, but the blood had pooled strangely — thick around the torso, thin and watery around the neck and head." | | 1 | "Not unless—" | | 2 | "And yet—" | | 3 | "But the memory of Morris, the impossible wound geometry, the clean edges and dried skin—the same pattern she'd seen on his body, burned into her mind during the night shift she still couldn't shake." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1111 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.0279027902790279 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.008100810081008101 | |
| 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 | 10.17 | | std | 6.96 | | cv | 0.684 | | sampleLengths | | 0 | 14 | | 1 | 16 | | 2 | 17 | | 3 | 6 | | 4 | 13 | | 5 | 3 | | 6 | 8 | | 7 | 21 | | 8 | 15 | | 9 | 12 | | 10 | 5 | | 11 | 6 | | 12 | 12 | | 13 | 8 | | 14 | 27 | | 15 | 11 | | 16 | 1 | | 17 | 6 | | 18 | 23 | | 19 | 32 | | 20 | 9 | | 21 | 11 | | 22 | 10 | | 23 | 6 | | 24 | 27 | | 25 | 4 | | 26 | 6 | | 27 | 12 | | 28 | 18 | | 29 | 20 | | 30 | 12 | | 31 | 5 | | 32 | 8 | | 33 | 4 | | 34 | 1 | | 35 | 20 | | 36 | 10 | | 37 | 13 | | 38 | 6 | | 39 | 12 | | 40 | 7 | | 41 | 15 | | 42 | 13 | | 43 | 10 | | 44 | 3 | | 45 | 3 | | 46 | 8 | | 47 | 2 | | 48 | 20 | | 49 | 4 |
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| 59.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3950617283950617 | | totalSentences | 162 | | uniqueOpeners | 64 | |
| 63.49% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 105 | | matches | | 0 | "Of course Eva would be" | | 1 | "Already she'd noted the curled" |
| | ratio | 0.019 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 105 | | matches | | 0 | "She adjusted the leather strap" | | 1 | "She followed it past defunct" | | 2 | "His overcoat was open, the" | | 3 | "She pulled on nitrile gloves," | | 4 | "She took out her own" | | 5 | "She leaned closer to the" | | 6 | "They didn't look like a" | | 7 | "She'd seen knife wounds, gunshot" | | 8 | "She'd never seen skin that" | | 9 | "She pressed her gloved finger" | | 10 | "She stood, stepped back, and" | | 11 | "She traced the halo's boundary" | | 12 | "She touched the victim's cheek." | | 13 | "She heard footsteps, quick and" | | 14 | "She clutched her leather satchel" | | 15 | "She tucked a strand behind" | | 16 | "She knelt opposite Quinn, her" | | 17 | "She pushed the thought aside" | | 18 | "She looked at the wound" | | 19 | "She carefully pried the fingers" |
| | ratio | 0.267 | |
| 55.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 85 | | totalSentences | 105 | | matches | | 0 | "Harlow Quinn killed the torch" | | 1 | "The tunnel breathed damp and" | | 2 | "She adjusted the leather strap" | | 3 | "Water dripped somewhere to her" | | 4 | "A train rumbled overhead, distant," | | 5 | "PC Dawes's voice echoed from" | | 6 | "She followed it past defunct" | | 7 | "A blue tarpaulin caught her" | | 8 | "Dawes held up his phone," | | 9 | "The soles had been cleaned" | | 10 | "His overcoat was open, the" | | 11 | "Quinn crouched, not touching anything" | | 12 | "Dawes's tone carried the weight" | | 13 | "Quinn had known her for" | | 14 | "She pulled on nitrile gloves," | | 15 | "The body lay supine, arms" | | 16 | "The cuts on his chest" | | 17 | "Something didn't add up." | | 18 | "She took out her own" | | 19 | "Brickwork, pipework, a graffiti tag" |
| | ratio | 0.81 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 105 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 1 | | matches | | 0 | "Brickwork, pipework, a graffiti tag that read *MIDNIGHT STANDARD* in curling script." |
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| 19.74% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 4 | | matches | | 0 | "Quinn crouched, not touching anything" | | 1 | "Eva stepped, her expression shifting from anxiety to something analytical" | | 2 | "She knelt, her satchel resting on her thigh" | | 3 | "Quinn stood, her joints cracking" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 58 | | tagDensity | 0.19 | | leniency | 0.379 | | rawRatio | 0 | | effectiveRatio | 0 | |