| 91.89% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 2 | | adverbTags | | 0 | "He glanced around [around]" | | 1 | "Herrera said quietly [quietly]" |
| | dialogueSentences | 37 | | tagDensity | 0.324 | | leniency | 0.649 | | rawRatio | 0.167 | | effectiveRatio | 0.108 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1326 | | 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) | |
| 43.44% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1326 | | totalAiIsms | 15 | | found | | 0 | | word | "practiced ease" | | count | 1 |
| | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | |
| | highlights | | 0 | "practiced ease" | | 1 | "gloom" | | 2 | "standard" | | 3 | "vibrated" | | 4 | "fascinating" | | 5 | "footsteps" | | 6 | "echoed" | | 7 | "desire" | | 8 | "stomach" | | 9 | "lurch" | | 10 | "velvet" | | 11 | "whisper" | | 12 | "flickered" | | 13 | "flicked" |
| |
| 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 | 166 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 166 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 189 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1320 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1100 | | uniqueNames | 16 | | maxNameDensity | 0.91 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Herrera" | | discoveredNames | | London | 1 | | Camden | 3 | | November | 1 | | Morris | 6 | | High | 1 | | Street | 1 | | Town | 1 | | Met | 2 | | Greek | 1 | | Footsteps | 1 | | Quinn | 10 | | Tube | 1 | | St | 1 | | Herrera | 9 | | Movement | 1 | | Three | 4 |
| | persons | | 0 | "Morris" | | 1 | "Met" | | 2 | "Footsteps" | | 3 | "Quinn" | | 4 | "Herrera" | | 5 | "Movement" |
| | places | | 0 | "London" | | 1 | "Camden" | | 2 | "High" | | 3 | "Street" | | 4 | "Town" | | 5 | "St" |
| | globalScore | 1 | | windowScore | 0.167 | |
| 88.27% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like shadow given form" | | 1 | "felt like minutes or hours, time stretc" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.758 | | wordCount | 1320 | | matches | | 0 | "Not the ordinary absence of light, but something thicker" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 189 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 72 | | mean | 18.33 | | std | 14.2 | | cv | 0.774 | | sampleLengths | | 0 | 44 | | 1 | 5 | | 2 | 13 | | 3 | 6 | | 4 | 65 | | 5 | 32 | | 6 | 35 | | 7 | 56 | | 8 | 15 | | 9 | 1 | | 10 | 39 | | 11 | 14 | | 12 | 29 | | 13 | 7 | | 14 | 30 | | 15 | 14 | | 16 | 8 | | 17 | 3 | | 18 | 11 | | 19 | 14 | | 20 | 10 | | 21 | 15 | | 22 | 6 | | 23 | 21 | | 24 | 25 | | 25 | 15 | | 26 | 40 | | 27 | 3 | | 28 | 32 | | 29 | 32 | | 30 | 27 | | 31 | 14 | | 32 | 23 | | 33 | 7 | | 34 | 32 | | 35 | 12 | | 36 | 35 | | 37 | 24 | | 38 | 2 | | 39 | 35 | | 40 | 53 | | 41 | 10 | | 42 | 45 | | 43 | 16 | | 44 | 11 | | 45 | 4 | | 46 | 9 | | 47 | 20 | | 48 | 18 | | 49 | 8 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 166 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 190 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 189 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1106 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.03345388788426763 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.0081374321880651 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 189 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 189 | | mean | 6.98 | | std | 5.09 | | cv | 0.729 | | sampleLengths | | 0 | 12 | | 1 | 15 | | 2 | 17 | | 3 | 3 | | 4 | 2 | | 5 | 13 | | 6 | 3 | | 7 | 3 | | 8 | 12 | | 9 | 2 | | 10 | 1 | | 11 | 15 | | 12 | 2 | | 13 | 9 | | 14 | 3 | | 15 | 11 | | 16 | 10 | | 17 | 9 | | 18 | 7 | | 19 | 2 | | 20 | 14 | | 21 | 8 | | 22 | 3 | | 23 | 8 | | 24 | 10 | | 25 | 6 | | 26 | 7 | | 27 | 13 | | 28 | 10 | | 29 | 2 | | 30 | 2 | | 31 | 22 | | 32 | 4 | | 33 | 2 | | 34 | 2 | | 35 | 7 | | 36 | 1 | | 37 | 16 | | 38 | 7 | | 39 | 2 | | 40 | 2 | | 41 | 12 | | 42 | 2 | | 43 | 2 | | 44 | 10 | | 45 | 9 | | 46 | 15 | | 47 | 5 | | 48 | 7 | | 49 | 3 |
| |
| 80.78% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.5291005291005291 | | totalSentences | 189 | | uniqueOpeners | 100 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 129 | | matches | | 0 | "Just a small recess near" | | 1 | "Just smooth darkness where features" | | 2 | "Then the sensation vanished, leaving" | | 3 | "Then Herrera looked up." | | 4 | "Too many limbs." |
| | ratio | 0.039 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 129 | | matches | | 0 | "He went left." | | 1 | "He didn't stop." | | 2 | "They never did." | | 3 | "Her legs burned as she" | | 4 | "She hadn't known this entrance" | | 5 | "Her torch beam cut through" | | 6 | "She checked her holster." | | 7 | "She yanked her hand back." | | 8 | "Her torch beam caught nothing." | | 9 | "She thought of Morris." | | 10 | "His terrible taste in takeaway." | | 11 | "Her fingers brushed bone." | | 12 | "Her suspect stood twenty feet" | | 13 | "She knew that face from" | | 14 | "His face went pale." | | 15 | "Her name left his mouth" | | 16 | "She ignored the voice." | | 17 | "He glanced around, nervous" | | 18 | "His scarred forearm caught the" | | 19 | "He pointed towards the tunnel." |
| | ratio | 0.163 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 92 | | totalSentences | 129 | | matches | | 0 | "The man in the grey" | | 1 | "Quinn followed, her boots hitting" | | 2 | "He went left." | | 3 | "The words tore from her" | | 4 | "He didn't stop." | | 5 | "They never did." | | 6 | "Her legs burned as she" | | 7 | "The worn leather watch on" | | 8 | "An embroidered raven." | | 9 | "The alley spat them out" | | 10 | "The suspect dodged between two" | | 11 | "Quinn skidded to a halt" | | 12 | "Camden Town station." | | 13 | "The sign hung crooked, half" | | 14 | "She hadn't known this entrance" | | 15 | "Her torch beam cut through" | | 16 | "Graffiti covered the walls, tags" | | 17 | "Things that looked uncomfortably like" | | 18 | "She checked her holster." | | 19 | "The stairs ended at a" |
| | ratio | 0.713 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 129 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 2 | | matches | | 0 | "Things that looked uncomfortably like the markings she'd found in Morris's case file, the ones the Met had dismissed as gang signs." | | 1 | "The stairs wound down for what felt like minutes or hours, time stretching and compressing in ways that made her stomach lurch." |
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| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 2 | | matches | | 0 | "He glanced around, nervous" | | 1 | "Herrera's hand went, fingers pressing the metal flat against his chest" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 37 | | tagDensity | 0.054 | | leniency | 0.108 | | rawRatio | 0 | | effectiveRatio | 0 | |