| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 97 | | tagDensity | 0.052 | | leniency | 0.103 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1678 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 76.16% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1678 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "churned" | | 1 | "electric" | | 2 | "silk" | | 3 | "velvet" | | 4 | "warmth" | | 5 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 144 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 144 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 236 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1678 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 26.87% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 69 | | wordCount | 1137 | | uniqueNames | 11 | | maxNameDensity | 2.46 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 28 | | Tube | 1 | | Camden | 2 | | Market | 1 | | Inspector | 1 | | Vale | 22 | | Bell | 8 | | Town | 1 | | Euston | 1 | | One | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Vale" | | 3 | "Bell" |
| | places | | 0 | "Camden" | | 1 | "Town" | | 2 | "Euston" | | 3 | "One" |
| | globalScore | 0.269 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 94 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a coin carved from bone" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1678 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 236 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 160 | | mean | 10.49 | | std | 11.02 | | cv | 1.051 | | sampleLengths | | 0 | 16 | | 1 | 28 | | 2 | 51 | | 3 | 6 | | 4 | 50 | | 5 | 9 | | 6 | 34 | | 7 | 6 | | 8 | 13 | | 9 | 6 | | 10 | 3 | | 11 | 6 | | 12 | 20 | | 13 | 12 | | 14 | 3 | | 15 | 22 | | 16 | 2 | | 17 | 9 | | 18 | 33 | | 19 | 4 | | 20 | 14 | | 21 | 5 | | 22 | 3 | | 23 | 7 | | 24 | 9 | | 25 | 11 | | 26 | 57 | | 27 | 11 | | 28 | 1 | | 29 | 7 | | 30 | 4 | | 31 | 2 | | 32 | 2 | | 33 | 8 | | 34 | 2 | | 35 | 4 | | 36 | 35 | | 37 | 2 | | 38 | 4 | | 39 | 6 | | 40 | 39 | | 41 | 4 | | 42 | 4 | | 43 | 4 | | 44 | 5 | | 45 | 14 | | 46 | 2 | | 47 | 23 | | 48 | 13 | | 49 | 38 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 144 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 201 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 236 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1141 | | adjectiveStacks | 1 | | stackExamples | | 0 | "lay upside down beside it." |
| | adverbCount | 17 | | adverbRatio | 0.014899211218229623 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0017528483786152498 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 236 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 236 | | mean | 7.11 | | std | 4.42 | | cv | 0.622 | | sampleLengths | | 0 | 16 | | 1 | 6 | | 2 | 15 | | 3 | 7 | | 4 | 5 | | 5 | 10 | | 6 | 12 | | 7 | 24 | | 8 | 6 | | 9 | 8 | | 10 | 15 | | 11 | 10 | | 12 | 8 | | 13 | 9 | | 14 | 9 | | 15 | 14 | | 16 | 12 | | 17 | 8 | | 18 | 6 | | 19 | 4 | | 20 | 9 | | 21 | 6 | | 22 | 3 | | 23 | 6 | | 24 | 5 | | 25 | 15 | | 26 | 12 | | 27 | 3 | | 28 | 22 | | 29 | 2 | | 30 | 9 | | 31 | 5 | | 32 | 5 | | 33 | 15 | | 34 | 8 | | 35 | 4 | | 36 | 4 | | 37 | 10 | | 38 | 5 | | 39 | 3 | | 40 | 7 | | 41 | 3 | | 42 | 6 | | 43 | 11 | | 44 | 9 | | 45 | 8 | | 46 | 18 | | 47 | 11 | | 48 | 11 | | 49 | 11 |
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| 51.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.326271186440678 | | totalSentences | 236 | | uniqueOpeners | 77 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 134 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 134 | | matches | | 0 | "He wore a charcoal suit," | | 1 | "His right hand rested open" | | 2 | "His left clutched a torn" | | 3 | "He had loosened his tie" | | 4 | "His shoes carried pale dust" | | 5 | "She stepped over the chalk" | | 6 | "His skull had split above" | | 7 | "He did not answer." | | 8 | "Her boots made no sound" | | 9 | "It looked like a coin" | | 10 | "He crouched beside her." | | 11 | "Its surface carried trays of" | | 12 | "She looked at the needle." | | 13 | "It pointed towards the tunnel." | | 14 | "She crossed the platform in" | | 15 | "She held her torch over" | | 16 | "She used a pen to" | | 17 | "He released her." | | 18 | "She pointed at Bell’s right" | | 19 | "She glanced at Vale’s rolled" |
| | ratio | 0.172 | |
| 19.70% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 118 | | totalSentences | 134 | | matches | | 0 | "Detective Harlow Quinn ducked beneath" | | 1 | "The tunnel swallowed the city’s" | | 2 | "Aboveground, Camden Market churned through" | | 3 | "Dust silvered the tiled walls." | | 4 | "A dead escalator descended into" | | 5 | "Someone had strung electric lamps" | | 6 | "Quinn stopped at the bottom" | | 7 | "A man lay beside the" | | 8 | "He wore a charcoal suit," | | 9 | "Blood had spread beneath his" | | 10 | "His right hand rested open" | | 11 | "His left clutched a torn" | | 12 | "Detective Inspector Vale waited near" | | 13 | "He had loosened his tie" | | 14 | "His shoes carried pale dust" | | 15 | "Quinn checked her watch." | | 16 | "The worn leather strap pressed" | | 17 | "Vale glanced at the corpse." | | 18 | "Quinn moved towards the body" | | 19 | "Quinn looked at the booth." |
| | ratio | 0.881 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 134 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 97 | | tagDensity | 0.052 | | leniency | 0.103 | | rawRatio | 0.2 | | effectiveRatio | 0.021 | |