| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.448 | | leniency | 0.897 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 81.80% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1099 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "gently" | | 1 | "completely" | | 2 | "suddenly" | | 3 | "lazily" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 54.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1099 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "echoed" | | 1 | "tinged" | | 2 | "tracing" | | 3 | "gloom" | | 4 | "etched" | | 5 | "efficient" | | 6 | "weight" | | 7 | "raced" | | 8 | "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 | 73 | | matches | (empty) | |
| 64.58% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 73 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 88 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1089 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 96.60% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 749 | | uniqueNames | 11 | | maxNameDensity | 1.07 | | worstName | "Carter" | | maxWindowNameDensity | 2 | | worstWindowName | "Carter" | | discoveredNames | | Camden | 1 | | Tube | 1 | | Harlow | 1 | | Quinn | 5 | | Sergeant | 1 | | Will | 1 | | Carter | 8 | | Morris | 2 | | Holloway | 2 | | Eva | 1 | | Kowalski | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Will" | | 4 | "Carter" | | 5 | "Morris" | | 6 | "Holloway" | | 7 | "Eva" | | 8 | "Kowalski" |
| | places | (empty) | | globalScore | 0.966 | | windowScore | 1 | |
| 98.98% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like flecks of old, green-tinged b" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.918 | | wordCount | 1089 | | matches | | 0 | "not over his wallet, but over what was in his hand" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 88 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 40.33 | | std | 20.26 | | cv | 0.502 | | sampleLengths | | 0 | 60 | | 1 | 25 | | 2 | 68 | | 3 | 22 | | 4 | 72 | | 5 | 44 | | 6 | 21 | | 7 | 69 | | 8 | 35 | | 9 | 15 | | 10 | 56 | | 11 | 5 | | 12 | 10 | | 13 | 60 | | 14 | 51 | | 15 | 9 | | 16 | 34 | | 17 | 65 | | 18 | 32 | | 19 | 49 | | 20 | 22 | | 21 | 25 | | 22 | 43 | | 23 | 71 | | 24 | 43 | | 25 | 53 | | 26 | 30 |
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| 95.65% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 73 | | matches | | 0 | "was frozen" | | 1 | "was clenched" |
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| 84.06% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 115 | | matches | | 0 | "were peeling" | | 1 | "was shimmering" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 88 | | ratio | 0.011 | | matches | | 0 | "The compass on her wrist, the one she’d taken from a evidence locker after the Morris case—a small brass thing with a patina of verdigris and a face etched with strange symbols—suddenly grew warm against her skin." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 757 | | adjectiveStacks | 1 | | stackExamples | | 0 | "old, green-tinged brass." |
| | adverbCount | 22 | | adverbRatio | 0.02906208718626156 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007926023778071334 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 88 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 88 | | mean | 12.38 | | std | 9.41 | | cv | 0.761 | | sampleLengths | | 0 | 20 | | 1 | 21 | | 2 | 19 | | 3 | 20 | | 4 | 5 | | 5 | 22 | | 6 | 12 | | 7 | 31 | | 8 | 3 | | 9 | 22 | | 10 | 13 | | 11 | 7 | | 12 | 11 | | 13 | 5 | | 14 | 13 | | 15 | 1 | | 16 | 12 | | 17 | 2 | | 18 | 8 | | 19 | 7 | | 20 | 37 | | 21 | 10 | | 22 | 11 | | 23 | 18 | | 24 | 5 | | 25 | 12 | | 26 | 13 | | 27 | 9 | | 28 | 12 | | 29 | 9 | | 30 | 20 | | 31 | 6 | | 32 | 9 | | 33 | 6 | | 34 | 13 | | 35 | 10 | | 36 | 14 | | 37 | 11 | | 38 | 8 | | 39 | 5 | | 40 | 2 | | 41 | 8 | | 42 | 5 | | 43 | 37 | | 44 | 18 | | 45 | 13 | | 46 | 30 | | 47 | 4 | | 48 | 1 | | 49 | 3 |
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| 71.97% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4659090909090909 | | totalSentences | 88 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 47.69% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 65 | | matches | | 0 | "Her partner, Sergeant Will Carter," | | 1 | "She snapped on a pair" | | 2 | "Her sharp jaw was set," | | 3 | "She played her light over" | | 4 | "His right hand was clenched." | | 5 | "She used a pen from" | | 6 | "It looked like flecks of" | | 7 | "she said, her voice flat" | | 8 | "She stood up, her light" | | 9 | "Her beam caught on something" | | 10 | "She walked over, her bearing" | | 11 | "She bagged it without a" | | 12 | "Her light continued its path," | | 13 | "It was shimmering, indistinct, like" | | 14 | "She ignored him, stepping closer." | | 15 | "Its needle, which had been" | | 16 | "She looked from the compass" | | 17 | "she said, her voice low" | | 18 | "She held up the evidence" | | 19 | "Her mind raced, pieces clicking" |
| | ratio | 0.431 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 65 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn’s boots echoed" | | 2 | "The place was a tomb," | | 3 | "Her partner, Sergeant Will Carter," | | 4 | "She snapped on a pair" | | 5 | "Her sharp jaw was set," | | 6 | "The body lay sprawled near" | | 7 | "Quinn crouched, the worn leather" | | 8 | "She played her light over" | | 9 | "Holloway’s face was frozen in" | | 10 | "His right hand was clenched." | | 11 | "She used a pen from" | | 12 | "It looked like flecks of" | | 13 | "she said, her voice flat" | | 14 | "Carter shrugged, his bulky frame" | | 15 | "She stood up, her light" | | 16 | "The scene was too contained." | | 17 | "A single pool of blood," | | 18 | "The killer had been close," | | 19 | "Her beam caught on something" |
| | ratio | 0.969 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 98.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 2 | | matches | | 0 | "Carter laughed, a short, harsh sound that echoed in the cavernous space." | | 1 | "He yanked his hand back with a sharp gasp, staring at it as if it belonged to someone else." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 5 | | matches | | 0 | "She snapped on, her movements economical, practiced" | | 1 | "she said, her voice flat" | | 2 | "she said, her voice low" | | 3 | "Quinn repeated, turning to face him" | | 4 | "Quinn said, the deduction solidifying into cold certainty" |
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| 46.55% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 3 | | fancyTags | | 0 | "She snapped on (snap on)" | | 1 | "Her light continued (continue)" | | 2 | "Quinn repeated (repeat)" |
| | dialogueSentences | 29 | | tagDensity | 0.276 | | leniency | 0.552 | | rawRatio | 0.375 | | effectiveRatio | 0.207 | |