| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "The word landed like [like]" |
| | dialogueSentences | 31 | | tagDensity | 0.29 | | leniency | 0.581 | | rawRatio | 0.111 | | effectiveRatio | 0.065 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1649 | | 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) | |
| 48.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1649 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "scanned" | | 1 | "gleaming" | | 2 | "chaotic" | | 3 | "shimmered" | | 4 | "pulsed" | | 5 | "velvet" | | 6 | "familiar" | | 7 | "weight" | | 8 | "silence" | | 9 | "footsteps" | | 10 | "navigate" | | 11 | "echoed" | | 12 | "vibrated" | | 13 | "pulse" |
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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 | 138 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 138 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 158 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1651 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1398 | | uniqueNames | 20 | | maxNameDensity | 0.79 | | worstName | "Herrera" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Chalk | 1 | | Farm | 1 | | Road | 1 | | Friday-night | 1 | | Camden | 3 | | Tomás | 1 | | Herrera | 11 | | Morris | 4 | | Rotherhithe | 2 | | Town | 1 | | Transport | 1 | | London | 3 | | Victorian | 1 | | Tottenham | 1 | | Saint | 1 | | Christopher | 1 | | Seville | 1 | | Silence | 2 | | Quinn | 10 | | Three | 3 |
| | persons | | 0 | "Tomás" | | 1 | "Herrera" | | 2 | "Morris" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Quinn" |
| | places | | 0 | "Chalk" | | 1 | "Farm" | | 2 | "Road" | | 3 | "Camden" | | 4 | "Rotherhithe" | | 5 | "Town" | | 6 | "London" | | 7 | "Tottenham" | | 8 | "Seville" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | 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 | 1651 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 158 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 26.63 | | std | 25.7 | | cv | 0.965 | | sampleLengths | | 0 | 10 | | 1 | 74 | | 2 | 34 | | 3 | 3 | | 4 | 4 | | 5 | 8 | | 6 | 76 | | 7 | 7 | | 8 | 72 | | 9 | 15 | | 10 | 35 | | 11 | 6 | | 12 | 67 | | 13 | 6 | | 14 | 104 | | 15 | 66 | | 16 | 23 | | 17 | 87 | | 18 | 17 | | 19 | 4 | | 20 | 40 | | 21 | 10 | | 22 | 2 | | 23 | 24 | | 24 | 12 | | 25 | 45 | | 26 | 3 | | 27 | 6 | | 28 | 40 | | 29 | 81 | | 30 | 57 | | 31 | 8 | | 32 | 2 | | 33 | 27 | | 34 | 62 | | 35 | 3 | | 36 | 8 | | 37 | 36 | | 38 | 5 | | 39 | 25 | | 40 | 50 | | 41 | 56 | | 42 | 9 | | 43 | 8 | | 44 | 48 | | 45 | 5 | | 46 | 4 | | 47 | 22 | | 48 | 13 | | 49 | 31 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 138 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 216 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 158 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1408 | | adjectiveStacks | 1 | | stackExamples | | 0 | "safe, rain-blurred glow" |
| | adverbCount | 32 | | adverbRatio | 0.022727272727272728 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.002840909090909091 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 158 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 158 | | mean | 10.45 | | std | 8.53 | | cv | 0.816 | | sampleLengths | | 0 | 10 | | 1 | 16 | | 2 | 3 | | 3 | 12 | | 4 | 17 | | 5 | 19 | | 6 | 3 | | 7 | 4 | | 8 | 4 | | 9 | 10 | | 10 | 6 | | 11 | 9 | | 12 | 2 | | 13 | 3 | | 14 | 3 | | 15 | 4 | | 16 | 3 | | 17 | 3 | | 18 | 2 | | 19 | 29 | | 20 | 9 | | 21 | 38 | | 22 | 7 | | 23 | 3 | | 24 | 46 | | 25 | 5 | | 26 | 18 | | 27 | 9 | | 28 | 5 | | 29 | 1 | | 30 | 9 | | 31 | 2 | | 32 | 2 | | 33 | 22 | | 34 | 6 | | 35 | 12 | | 36 | 6 | | 37 | 24 | | 38 | 4 | | 39 | 21 | | 40 | 6 | | 41 | 17 | | 42 | 4 | | 43 | 19 | | 44 | 26 | | 45 | 17 | | 46 | 15 | | 47 | 6 | | 48 | 26 | | 49 | 12 |
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| 60.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.4177215189873418 | | totalSentences | 158 | | uniqueOpeners | 66 | |
| 53.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 124 | | matches | | 0 | "Then she squeezed through the" | | 1 | "Then, faint, from deep inside" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 124 | | matches | | 0 | "She lost him at the" | | 1 | "She scanned the road." | | 2 | "Her radio crackled." | | 3 | "She ignored it." | | 4 | "She pushed off the wall" | | 5 | "It came in sheets now," | | 6 | "She glanced back at the" | | 7 | "She reached the bottom and" | | 8 | "She carried a jar of" | | 9 | "Her warrant card sat in" | | 10 | "Her collapsible baton on her" | | 11 | "She spotted Herrera thirty metres" | | 12 | "He stopped at a stall" | | 13 | "He wore a threadbare school" | | 14 | "he asked, though his tone" | | 15 | "He sipped his drink" | | 16 | "His warm brown eyes went" | | 17 | "She shoved through the crowd" | | 18 | "She pulled her phone out." | | 19 | "He'd followed her." |
| | ratio | 0.226 | |
| 48.71% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 102 | | totalSentences | 124 | | matches | | 0 | "She lost him at the" | | 1 | "One second, the figure in" | | 2 | "The next, gone." | | 3 | "Quinn pressed her back against" | | 4 | "The knees, though." | | 5 | "The knees had opinions." | | 6 | "She scanned the road." | | 7 | "A kebab shop throwing greasy" | | 8 | "A row of shuttered market" | | 9 | "Her radio crackled." | | 10 | "She ignored it." | | 11 | "Dispatch could wait." | | 12 | "The kind of cases that" | | 13 | "She pushed off the wall" | | 14 | "The rain intensified." | | 15 | "It came in sheets now," | | 16 | "Someone had passed through here." | | 17 | "Quinn pulled her coat tighter" | | 18 | "She glanced back at the" | | 19 | "The stairs descended in a" |
| | ratio | 0.823 | |
| 40.32% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 124 | | matches | | 0 | "Now the padlocked gate at" |
| | ratio | 0.008 | |
| 53.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 6 | | matches | | 0 | "Three weeks she'd tracked the former paramedic through a web of off-the-books medical records, whispered favours, and patients who healed too fast from injuries…" | | 1 | "She glanced back at the street behind her, at the safe, rain-blurred glow of Camden's nightlife, at the world that made sense." | | 2 | "The stalls blurred past in a rush of strange merchandise, jars of teeth, bundles of dried herbs that smoked without fire, a taxidermied raven with three heads t…" | | 3 | "A display of ceramic bowls crashed to the ground behind her, and the vendor's curse followed her down the platform in a gust of heat that singed the back of her…" | | 4 | "The darkness ahead was total, thick and textured, the kind of dark that felt solid against your skin." | | 5 | "Three years of dead ends and classified files and colleagues who changed the subject when she brought up Rotherhithe." |
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| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 1 | | matches | | 0 | "he asked, though his tone suggested he already knew" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.097 | | leniency | 0.194 | | rawRatio | 0 | | effectiveRatio | 0 | |