| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.03 | | leniency | 0.061 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1508 | | 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) | |
| 86.74% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1508 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "footfall" | | 1 | "fluttered" | | 2 | "jaw clenched" | | 3 | "pulsed" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "jaw clenched" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 204 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 204 | | 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 | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1513 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 58.73% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 52 | | wordCount | 1260 | | uniqueNames | 24 | | maxNameDensity | 1.83 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 23 | | Greek | 1 | | Street | 1 | | Vice | 2 | | Raven | 1 | | Nest | 1 | | Home | 1 | | Office | 1 | | Silas | 1 | | Met | 1 | | Shaftesbury | 1 | | Avenue | 1 | | Underground | 1 | | Veil | 1 | | Market | 2 | | Tube | 1 | | Camden | 2 | | Morris | 1 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Silas" | | 4 | "Market" | | 5 | "Morris" | | 6 | "Herrera" | | 7 | "Saint" | | 8 | "Christopher" | | 9 | "Tomás" |
| | places | | 0 | "Soho" | | 1 | "Greek" | | 2 | "Street" | | 3 | "Shaftesbury" | | 4 | "Avenue" | | 5 | "Underground" |
| | globalScore | 0.587 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 94 | | 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 | 1513 | | 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 | 100 | | mean | 15.13 | | std | 14.19 | | cv | 0.938 | | sampleLengths | | 0 | 6 | | 1 | 17 | | 2 | 27 | | 3 | 20 | | 4 | 3 | | 5 | 9 | | 6 | 36 | | 7 | 78 | | 8 | 29 | | 9 | 10 | | 10 | 4 | | 11 | 7 | | 12 | 10 | | 13 | 4 | | 14 | 3 | | 15 | 5 | | 16 | 32 | | 17 | 39 | | 18 | 32 | | 19 | 10 | | 20 | 16 | | 21 | 3 | | 22 | 31 | | 23 | 3 | | 24 | 39 | | 25 | 5 | | 26 | 18 | | 27 | 5 | | 28 | 34 | | 29 | 18 | | 30 | 8 | | 31 | 24 | | 32 | 19 | | 33 | 4 | | 34 | 5 | | 35 | 6 | | 36 | 4 | | 37 | 25 | | 38 | 21 | | 39 | 5 | | 40 | 11 | | 41 | 19 | | 42 | 4 | | 43 | 13 | | 44 | 15 | | 45 | 6 | | 46 | 3 | | 47 | 14 | | 48 | 25 | | 49 | 29 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 204 | | matches | | 0 | "was supposed" | | 1 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 222 | | matches | (empty) | |
| 94.43% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 236 | | ratio | 0.017 | | matches | | 0 | "Her informant told her the back room - hidden behind a bookshelf - moved product that didn't exist on any Home Office list." | | 1 | "Not a station entrance - a service door left ajar by a maintenance crew." | | 2 | "A sign read: NO ENTRY - TRACK WORKS." | | 3 | "Something inside clinked - glass vials." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1262 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 22 | | adverbRatio | 0.017432646592709985 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.001584786053882726 | |
| 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 | 6.41 | | std | 4.72 | | cv | 0.736 | | sampleLengths | | 0 | 6 | | 1 | 6 | | 2 | 11 | | 3 | 11 | | 4 | 5 | | 5 | 6 | | 6 | 5 | | 7 | 14 | | 8 | 1 | | 9 | 2 | | 10 | 3 | | 11 | 3 | | 12 | 4 | | 13 | 5 | | 14 | 6 | | 15 | 13 | | 16 | 1 | | 17 | 12 | | 18 | 4 | | 19 | 9 | | 20 | 1 | | 21 | 3 | | 22 | 19 | | 23 | 13 | | 24 | 23 | | 25 | 10 | | 26 | 10 | | 27 | 19 | | 28 | 10 | | 29 | 4 | | 30 | 7 | | 31 | 3 | | 32 | 7 | | 33 | 4 | | 34 | 3 | | 35 | 3 | | 36 | 2 | | 37 | 9 | | 38 | 2 | | 39 | 3 | | 40 | 2 | | 41 | 8 | | 42 | 8 | | 43 | 4 | | 44 | 3 | | 45 | 20 | | 46 | 2 | | 47 | 3 | | 48 | 7 | | 49 | 9 |
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| 55.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 22 | | diversityRatio | 0.3888888888888889 | | totalSentences | 234 | | uniqueOpeners | 91 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 161 | | matches | | 0 | "Then the kid emerged with" | | 1 | "Then at the wall." | | 2 | "Too many eyes." | | 3 | "Then at the satchel in" | | 4 | "Then at the faces closing" |
| | ratio | 0.031 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 161 | | matches | | 0 | "It soaked the pavements and" | | 1 | "Her coat clung to her." | | 2 | "Her closely cropped salt-and-pepper hair" | | 3 | "He hit the ground running." | | 4 | "Her worn leather watch on" | | 5 | "She'd pulled his jacket from" | | 6 | "Her informant told her the" | | 7 | "He glanced back." | | 8 | "He didn't answer." | | 9 | "He ducked into an entry" | | 10 | "He burst out the other" | | 11 | "He cut down into the" | | 12 | "Her shoes slapped on metal" | | 13 | "Her hand found the rail." | | 14 | "He chest heaved." | | 15 | "He clutched the satchel." | | 16 | "He stared at her." | | 17 | "Her breath sawed." | | 18 | "She let her hand rest" | | 19 | "He shook his head." |
| | ratio | 0.23 | |
| 46.96% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 133 | | totalSentences | 161 | | matches | | 0 | "The rain hammered Soho in" | | 1 | "Water ran black in the" | | 2 | "It soaked the pavements and" | | 3 | "Detective Harlow Quinn kept her" | | 4 | "Her coat clung to her." | | 5 | "Her closely cropped salt-and-pepper hair" | | 6 | "Breath burned in her chest." | | 7 | "The kid didn't stop." | | 8 | "He hit the ground running." | | 9 | "Quinn cut left into Greek" | | 10 | "Her worn leather watch on" | | 11 | "She'd pulled his jacket from" | | 12 | "The Raven's Nest." | | 13 | "The bar with the distinctive" | | 14 | "The walls inside were covered" | | 15 | "Her informant told her the" | | 16 | "The kid was supposed to" | | 17 | "Quinn had waited three hours" | | 18 | "Quinn closed the gap." | | 19 | "He glanced back." |
| | ratio | 0.826 | |
| 31.06% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 161 | | matches | | | ratio | 0.006 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 3 | | matches | | 0 | "The bar with the distinctive green neon sign above the entrance that buzzed even when the power was out." | | 1 | "Her informant told her the back room - hidden behind a bookshelf - moved product that didn't exist on any Home Office list." | | 2 | "The platform stretched long and empty behind her, a throat that led nowhere." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "he whispered (whisper)" |
| | dialogueSentences | 33 | | tagDensity | 0.03 | | leniency | 0.061 | | rawRatio | 1 | | effectiveRatio | 0.061 | |