| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 78 | | tagDensity | 0.115 | | leniency | 0.231 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1774 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 80.27% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1774 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "weight" | | 1 | "pristine" | | 2 | "etched" | | 3 | "trembled" | | 4 | "scanned" | | 5 | "traced" | | 6 | "flicked" |
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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 | 130 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 130 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 199 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1774 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 23 | | unquotedAttributions | 0 | | matches | (empty) | |
| 43.36% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 53 | | wordCount | 1219 | | uniqueNames | 6 | | maxNameDensity | 2.13 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 26 | | Sergeant | 1 | | Nisha | 1 | | Bell | 20 | | Orsini | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Nisha" | | 4 | "Bell" | | 5 | "Orsini" |
| | places | (empty) | | globalScore | 0.434 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 97 | | 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 | 1774 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 199 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 107 | | mean | 16.58 | | std | 16.08 | | cv | 0.97 | | sampleLengths | | 0 | 35 | | 1 | 45 | | 2 | 41 | | 3 | 13 | | 4 | 24 | | 5 | 26 | | 6 | 3 | | 7 | 30 | | 8 | 3 | | 9 | 7 | | 10 | 36 | | 11 | 5 | | 12 | 28 | | 13 | 19 | | 14 | 8 | | 15 | 10 | | 16 | 2 | | 17 | 41 | | 18 | 10 | | 19 | 7 | | 20 | 5 | | 21 | 6 | | 22 | 24 | | 23 | 22 | | 24 | 12 | | 25 | 6 | | 26 | 27 | | 27 | 12 | | 28 | 1 | | 29 | 65 | | 30 | 52 | | 31 | 8 | | 32 | 13 | | 33 | 6 | | 34 | 3 | | 35 | 3 | | 36 | 14 | | 37 | 42 | | 38 | 5 | | 39 | 1 | | 40 | 2 | | 41 | 7 | | 42 | 37 | | 43 | 36 | | 44 | 7 | | 45 | 3 | | 46 | 3 | | 47 | 19 | | 48 | 6 | | 49 | 6 |
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| 97.17% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 130 | | matches | | 0 | "been etched" | | 1 | "been poured" | | 2 | "been arranged" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 191 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 199 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1219 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.02543068088597211 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.003281378178835111 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 199 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 199 | | mean | 8.91 | | std | 5.5 | | cv | 0.616 | | sampleLengths | | 0 | 23 | | 1 | 12 | | 2 | 8 | | 3 | 20 | | 4 | 8 | | 5 | 9 | | 6 | 10 | | 7 | 15 | | 8 | 16 | | 9 | 13 | | 10 | 4 | | 11 | 20 | | 12 | 8 | | 13 | 18 | | 14 | 3 | | 15 | 30 | | 16 | 3 | | 17 | 7 | | 18 | 9 | | 19 | 7 | | 20 | 9 | | 21 | 11 | | 22 | 5 | | 23 | 28 | | 24 | 8 | | 25 | 5 | | 26 | 6 | | 27 | 8 | | 28 | 3 | | 29 | 7 | | 30 | 2 | | 31 | 3 | | 32 | 17 | | 33 | 15 | | 34 | 6 | | 35 | 4 | | 36 | 6 | | 37 | 7 | | 38 | 5 | | 39 | 6 | | 40 | 3 | | 41 | 7 | | 42 | 14 | | 43 | 10 | | 44 | 12 | | 45 | 12 | | 46 | 6 | | 47 | 4 | | 48 | 23 | | 49 | 12 |
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| 48.74% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3165829145728643 | | totalSentences | 199 | | uniqueOpeners | 63 | |
| 55.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 121 | | matches | | 0 | "Even the hem of his" | | 1 | "Only for a fraction of" |
| | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 121 | | matches | | 0 | "Their blue flames gave the" | | 1 | "His coat was fine wool," | | 2 | "His eyes remained open, fixed" | | 3 | "His right fist was closed." | | 4 | "She walked the edge of" | | 5 | "It carried no blood, no" | | 6 | "She knelt again and examined" | | 7 | "She checked the skin beneath" | | 8 | "They resisted, stiff but not" | | 9 | "His hand had closed after" | | 10 | "She slipped the compass into" | | 11 | "She scanned it for cracks," | | 12 | "she called to the photographer" | | 13 | "It shifted under the pressure," | | 14 | "Its owner, a narrow man" | | 15 | "Its base sat in a" | | 16 | "she told the photographer" | | 17 | "She looked at the guarded" |
| | ratio | 0.149 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 113 | | totalSentences | 121 | | matches | | 0 | "The station entrance sat behind" | | 1 | "Detective Harlow Quinn ducked beneath" | | 2 | "A train had not run" | | 3 | "Dust covered the rails, but" | | 4 | "Lanterns hung from hooks in" | | 5 | "Their blue flames gave the" | | 6 | "A man lay on his" | | 7 | "His coat was fine wool," | | 8 | "Blood streaked the tiles beneath" | | 9 | "Detective Sergeant Nisha Bell waited" | | 10 | "Quinn looked from the body" | | 11 | "The blood had run uphill," | | 12 | "Quinn unfastened her coat and" | | 13 | "The dead man’s face held" | | 14 | "His eyes remained open, fixed" | | 15 | "A thin strip of grey" | | 16 | "Quinn kept her eyes on" | | 17 | "His right fist was closed." | | 18 | "A constable had left it" | | 19 | "Bell’s brows tightened." |
| | ratio | 0.934 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 121 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 1 | | matches | | 0 | "The station entrance sat behind a locked door marked STAFF ONLY, down a service stairwell that smelled of wet stone and old electricity." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 78 | | tagDensity | 0.103 | | leniency | 0.205 | | rawRatio | 0 | | effectiveRatio | 0 | |