| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 131 | | tagDensity | 0.069 | | leniency | 0.137 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2603 | | 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) | |
| 84.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2603 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "silk" | | 1 | "perfect" | | 2 | "weight" | | 3 | "scanned" | | 4 | "silence" | | 5 | "traced" |
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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 | 211 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 211 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 333 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 62 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2603 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 77 | | wordCount | 1751 | | uniqueNames | 9 | | maxNameDensity | 1.94 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 34 | | Camden | 1 | | London | 1 | | Martin | 1 | | Bell | 26 | | Patel | 8 | | Compass | 1 | | One | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Martin" | | 3 | "Bell" | | 4 | "Patel" | | 5 | "Compass" |
| | places | | | globalScore | 0.529 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 140 | | 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 | 2603 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 333 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 218 | | mean | 11.94 | | std | 13.63 | | cv | 1.142 | | sampleLengths | | 0 | 63 | | 1 | 26 | | 2 | 2 | | 3 | 39 | | 4 | 8 | | 5 | 6 | | 6 | 7 | | 7 | 4 | | 8 | 4 | | 9 | 4 | | 10 | 4 | | 11 | 21 | | 12 | 3 | | 13 | 7 | | 14 | 1 | | 15 | 9 | | 16 | 3 | | 17 | 53 | | 18 | 14 | | 19 | 4 | | 20 | 26 | | 21 | 2 | | 22 | 5 | | 23 | 51 | | 24 | 6 | | 25 | 3 | | 26 | 5 | | 27 | 5 | | 28 | 37 | | 29 | 33 | | 30 | 4 | | 31 | 6 | | 32 | 4 | | 33 | 13 | | 34 | 5 | | 35 | 6 | | 36 | 4 | | 37 | 60 | | 38 | 50 | | 39 | 8 | | 40 | 3 | | 41 | 18 | | 42 | 3 | | 43 | 1 | | 44 | 3 | | 45 | 10 | | 46 | 4 | | 47 | 5 | | 48 | 38 | | 49 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 211 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 284 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 333 | | ratio | 0.003 | | matches | | 0 | "“One person with a foot that size wouldn’t carry a man of his build without setting him down. The wet knees tell us he knelt somewhere. The dry cuffs tell us he didn’t kneel on this platform; the floor here is wet enough to soak the hems. Grey grit on his sleeve, but black grit under his shoes. He died somewhere else.”" |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1754 | | adjectiveStacks | 2 | | stackExamples | | 0 | "dense, ink-black pools." | | 1 | "single black-red droplet" |
| | adverbCount | 23 | | adverbRatio | 0.013112884834663626 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.002280501710376283 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 333 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 333 | | mean | 7.82 | | std | 6.42 | | cv | 0.822 | | sampleLengths | | 0 | 25 | | 1 | 11 | | 2 | 8 | | 3 | 19 | | 4 | 8 | | 5 | 5 | | 6 | 6 | | 7 | 7 | | 8 | 2 | | 9 | 6 | | 10 | 13 | | 11 | 20 | | 12 | 8 | | 13 | 6 | | 14 | 6 | | 15 | 1 | | 16 | 4 | | 17 | 4 | | 18 | 4 | | 19 | 4 | | 20 | 21 | | 21 | 3 | | 22 | 7 | | 23 | 1 | | 24 | 9 | | 25 | 3 | | 26 | 5 | | 27 | 8 | | 28 | 19 | | 29 | 2 | | 30 | 19 | | 31 | 9 | | 32 | 5 | | 33 | 4 | | 34 | 26 | | 35 | 2 | | 36 | 5 | | 37 | 16 | | 38 | 8 | | 39 | 9 | | 40 | 18 | | 41 | 6 | | 42 | 3 | | 43 | 5 | | 44 | 5 | | 45 | 16 | | 46 | 8 | | 47 | 13 | | 48 | 19 | | 49 | 7 |
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| 63.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.4036144578313253 | | totalSentences | 332 | | uniqueOpeners | 134 | |
| 17.18% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 194 | | matches | | 0 | "Then the screen caught the" |
| | ratio | 0.005 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 194 | | matches | | 0 | "She passed beneath the gate." | | 1 | "YOUR TRUE NAME, SPOKEN ONCE." | | 2 | "His sandy hair clung to" | | 3 | "His chin rested against his" | | 4 | "He wore a charcoal suit," | | 5 | "She lifted the bag without" | | 6 | "It held there, trembling." | | 7 | "She moved the bag to" | | 8 | "She gave the compass to" | | 9 | "He had removed nothing." | | 10 | "She moved around the powder" | | 11 | "Its width varied." | | 12 | "He examined the grooves." | | 13 | "His scene suit crackled." | | 14 | "He looked at the specimen" | | 15 | "She returned to the dead" | | 16 | "Her right hand pointed past" | | 17 | "Its needle strained towards the" | | 18 | "She turned the Compass, watching" |
| | ratio | 0.098 | |
| 88.87% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 144 | | totalSentences | 194 | | matches | | 0 | "Detective Harlow Quinn descended into" | | 1 | "The stairwell swallowed the noise" | | 2 | "Someone had painted over the" | | 3 | "Tar, perhaps, mixed with ground" | | 4 | "The black letters gleamed beneath" | | 5 | "The entrance should not have" | | 6 | "Quinn checked her worn leather" | | 7 | "The constable’s mouth tightened." | | 8 | "The second constable rubbed his" | | 9 | "Quinn looked through the gate." | | 10 | "Hundreds of objects hung from" | | 11 | "The air carried burnt sugar," | | 12 | "the first constable added" | | 13 | "Quinn signed the log." | | 14 | "She passed beneath the gate." | | 15 | "Stalls crowded the curving corridor," | | 16 | "A glass cabinet held silver" | | 17 | "YOUR TRUE NAME, SPOKEN ONCE." | | 18 | "The police lamps exposed every" | | 19 | "Shadows collected under tables in" |
| | ratio | 0.742 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 194 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 67 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | 5 | | fancyCount | 3 | | fancyTags | | 0 | "the first constable added (add)" | | 1 | "Patel murmured (murmur)" | | 2 | "Quinn murmured (murmur)" |
| | dialogueSentences | 131 | | tagDensity | 0.038 | | leniency | 0.076 | | rawRatio | 0.6 | | effectiveRatio | 0.046 | |