| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 65 | | tagDensity | 0.185 | | leniency | 0.369 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2157 | | 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) | |
| 81.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2157 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "footsteps" | | 1 | "fractured" | | 2 | "etched" | | 3 | "throbbed" | | 4 | "weight" | | 5 | "lurched" |
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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 | 205 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 205 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 258 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2157 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 23.18% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 95 | | wordCount | 1853 | | uniqueNames | 10 | | maxNameDensity | 2.54 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 47 | | Camden | 1 | | High | 1 | | Street | 1 | | Herrera | 35 | | Christopher | 2 | | Underground | 1 | | Saint | 2 | | Rain | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Christopher" | | 4 | "Saint" | | 5 | "Rain" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0.232 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 145 | | glossingSentenceCount | 1 | | matches | | 0 | "something close to it, polished smooth at the ed" |
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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 | 2157 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 258 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 147 | | mean | 14.67 | | std | 13.98 | | cv | 0.952 | | sampleLengths | | 0 | 18 | | 1 | 10 | | 2 | 7 | | 3 | 23 | | 4 | 7 | | 5 | 1 | | 6 | 10 | | 7 | 31 | | 8 | 42 | | 9 | 33 | | 10 | 2 | | 11 | 42 | | 12 | 19 | | 13 | 24 | | 14 | 1 | | 15 | 6 | | 16 | 32 | | 17 | 17 | | 18 | 2 | | 19 | 6 | | 20 | 7 | | 21 | 35 | | 22 | 41 | | 23 | 27 | | 24 | 4 | | 25 | 5 | | 26 | 38 | | 27 | 5 | | 28 | 5 | | 29 | 4 | | 30 | 9 | | 31 | 9 | | 32 | 17 | | 33 | 5 | | 34 | 18 | | 35 | 9 | | 36 | 8 | | 37 | 41 | | 38 | 9 | | 39 | 5 | | 40 | 2 | | 41 | 5 | | 42 | 7 | | 43 | 11 | | 44 | 2 | | 45 | 5 | | 46 | 1 | | 47 | 28 | | 48 | 15 | | 49 | 37 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 205 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 316 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 258 | | ratio | 0.004 | | matches | | 0 | "Beside him, a woman chopped something on a board with a cleaver; she paused long enough to glare at Quinn, then resumed." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1856 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.013469827586206896 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 258 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 258 | | mean | 8.36 | | std | 5.05 | | cv | 0.604 | | sampleLengths | | 0 | 18 | | 1 | 10 | | 2 | 7 | | 3 | 15 | | 4 | 8 | | 5 | 7 | | 6 | 1 | | 7 | 10 | | 8 | 12 | | 9 | 19 | | 10 | 6 | | 11 | 19 | | 12 | 6 | | 13 | 11 | | 14 | 9 | | 15 | 14 | | 16 | 10 | | 17 | 2 | | 18 | 10 | | 19 | 19 | | 20 | 13 | | 21 | 6 | | 22 | 13 | | 23 | 11 | | 24 | 6 | | 25 | 1 | | 26 | 6 | | 27 | 1 | | 28 | 6 | | 29 | 12 | | 30 | 5 | | 31 | 15 | | 32 | 7 | | 33 | 10 | | 34 | 2 | | 35 | 6 | | 36 | 7 | | 37 | 10 | | 38 | 12 | | 39 | 13 | | 40 | 4 | | 41 | 12 | | 42 | 6 | | 43 | 19 | | 44 | 11 | | 45 | 13 | | 46 | 3 | | 47 | 4 | | 48 | 5 | | 49 | 6 |
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| 49.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.2868217054263566 | | totalSentences | 258 | | uniqueOpeners | 74 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 192 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 192 | | matches | | 0 | "She dropped the bag on" | | 1 | "His footsteps splashed beyond the" | | 2 | "She grabbed his ankle." | | 3 | "He kicked down, catching her" | | 4 | "Her leather watch snagged on" | | 5 | "Her hands shook against the" | | 6 | "He crouched beside her despite" | | 7 | "He pressed both palms over" | | 8 | "he told the woman" | | 9 | "He pulled a packet from" | | 10 | "She did, then ended the" | | 11 | "Its lid flew open, spilling" | | 12 | "She cleared the bin and" | | 13 | "They came out onto a" | | 14 | "She pulled free." | | 15 | "She snatched the disc from" | | 16 | "She slipped it into her" | | 17 | "Her shoulder throbbed where Herrera" | | 18 | "He turned and ran." | | 19 | "She examined it beneath the" |
| | ratio | 0.188 | |
| 6.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 174 | | totalSentences | 192 | | matches | | 0 | "The man in the pharmacy" | | 1 | "Detective Harlow Quinn stepped out" | | 2 | "Herrera looked at her warrant" | | 3 | "Rain dripped from his curls" | | 4 | "Quinn moved to the edge" | | 5 | "Herrera took two steps toward" | | 6 | "The driver leaned on his" | | 7 | "Quinn vaulted the low chain" | | 8 | "A metal buckle struck her" | | 9 | "She dropped the bag on" | | 10 | "Herrera cut between a bus" | | 11 | "Quinn followed the flash of" | | 12 | "A cyclist swore and dragged" | | 13 | "A man outside a kebab" | | 14 | "Herrera ducked under his arm," | | 15 | "The scooter clipped the kerb" | | 16 | "Quinn gained ground at the" | | 17 | "Herrera glanced back, saw her" | | 18 | "A red smear marked the" | | 19 | "Quinn touched it with two" |
| | ratio | 0.906 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 192 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 85 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn ordered (order)" | | 1 | "Quinn shouted (shout)" |
| | dialogueSentences | 65 | | tagDensity | 0.185 | | leniency | 0.369 | | rawRatio | 0.167 | | effectiveRatio | 0.062 | |