| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 1 | | adverbTags | | 0 | "Harlow advanced slowly [slowly]" |
| | dialogueSentences | 38 | | tagDensity | 0.263 | | leniency | 0.526 | | rawRatio | 0.1 | | effectiveRatio | 0.053 | |
| 92.07% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1261 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 56.38% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1261 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "flicked" | | 1 | "chill" | | 2 | "wavered" | | 3 | "grave" | | 4 | "whisper" | | 5 | "echo" | | 6 | "anticipation" | | 7 | "footsteps" | | 8 | "silence" | | 9 | "echoing" | | 10 | "dancing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "sent a shiver through" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 115 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 115 | | filterMatches | (empty) | | hedgeMatches | | 0 | "happened to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 143 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1253 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 62.01% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 966 | | uniqueNames | 13 | | maxNameDensity | 1.76 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Morris" | | discoveredNames | | Quinn | 1 | | Veil | 3 | | Market | 3 | | Harlow | 17 | | London | 2 | | Camden | 1 | | West | 1 | | End | 1 | | Morris | 10 | | Transport | 1 | | Voices | 1 | | Silence | 1 | | Three | 4 |
| | persons | | 0 | "Quinn" | | 1 | "Market" | | 2 | "Harlow" | | 3 | "Morris" | | 4 | "Transport" | | 5 | "Voices" |
| | places | | | globalScore | 0.62 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 1 | | matches | | 0 | "shadows that seemed to move of their own accord" |
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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 | 1253 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 143 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 64 | | mean | 19.58 | | std | 15.49 | | cv | 0.791 | | sampleLengths | | 0 | 34 | | 1 | 2 | | 2 | 45 | | 3 | 36 | | 4 | 32 | | 5 | 4 | | 6 | 6 | | 7 | 16 | | 8 | 58 | | 9 | 6 | | 10 | 15 | | 11 | 38 | | 12 | 51 | | 13 | 38 | | 14 | 15 | | 15 | 20 | | 16 | 7 | | 17 | 22 | | 18 | 7 | | 19 | 12 | | 20 | 17 | | 21 | 41 | | 22 | 71 | | 23 | 8 | | 24 | 10 | | 25 | 1 | | 26 | 3 | | 27 | 28 | | 28 | 40 | | 29 | 3 | | 30 | 13 | | 31 | 38 | | 32 | 11 | | 33 | 24 | | 34 | 40 | | 35 | 18 | | 36 | 1 | | 37 | 38 | | 38 | 38 | | 39 | 14 | | 40 | 33 | | 41 | 4 | | 42 | 7 | | 43 | 4 | | 44 | 28 | | 45 | 4 | | 46 | 23 | | 47 | 12 | | 48 | 13 | | 49 | 25 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 115 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 167 | | matches | | 0 | "was listening" | | 1 | "were talking" |
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| 62.94% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 143 | | ratio | 0.028 | | matches | | 0 | "The crowd—a strange assortment of cloaked figures and too-smooth faces—parted like water around a stone." | | 1 | "Fear warred with something else in his eyes—desperation, maybe." | | 2 | "The rational part of her brain— the part that had kept her alive for eighteen years—screamed about ambushes, about traps, about the thousand ways this could go wrong." | | 3 | "The tunnel behind them— the way out—filled with footsteps." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 974 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.03182751540041068 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004106776180698152 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 143 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 143 | | mean | 8.76 | | std | 6.27 | | cv | 0.716 | | sampleLengths | | 0 | 15 | | 1 | 15 | | 2 | 4 | | 3 | 2 | | 4 | 15 | | 5 | 3 | | 6 | 5 | | 7 | 22 | | 8 | 4 | | 9 | 13 | | 10 | 19 | | 11 | 16 | | 12 | 16 | | 13 | 4 | | 14 | 6 | | 15 | 7 | | 16 | 9 | | 17 | 1 | | 18 | 18 | | 19 | 16 | | 20 | 23 | | 21 | 6 | | 22 | 7 | | 23 | 8 | | 24 | 5 | | 25 | 23 | | 26 | 10 | | 27 | 5 | | 28 | 5 | | 29 | 3 | | 30 | 17 | | 31 | 11 | | 32 | 10 | | 33 | 13 | | 34 | 11 | | 35 | 14 | | 36 | 6 | | 37 | 9 | | 38 | 2 | | 39 | 1 | | 40 | 6 | | 41 | 9 | | 42 | 2 | | 43 | 7 | | 44 | 13 | | 45 | 9 | | 46 | 7 | | 47 | 12 | | 48 | 8 | | 49 | 1 |
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| 68.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.46153846153846156 | | totalSentences | 143 | | uniqueOpeners | 66 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 95 | | matches | | 0 | "Too late, Harlow understood." | | 1 | "Then laughter, soft and cold," | | 2 | "Then a dozen, flickering to" |
| | ratio | 0.032 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 95 | | matches | | 0 | "She didn't slow down." | | 1 | "She thought of DS Morris." | | 2 | "He'd believed his badge and" | | 3 | "Her suspect stood at the" | | 4 | "He knew the word." | | 5 | "He shook his head, hair" | | 6 | "His voice cracked" | | 7 | "He complied, fingers threading through" | | 8 | "Her other hand reached for" | | 9 | "she said, close enough now" | | 10 | "He looked back at her," | | 11 | "They climbed together, her suspect" | | 12 | "They always killed you if" | | 13 | "Her radio crackled with static." | | 14 | "she called out, her voice" | | 15 | "They were talking about Morris." | | 16 | "He looked exactly like DS" |
| | ratio | 0.179 | |
| 70.53% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 95 | | matches | | 0 | "The suspect vaulted the market" | | 1 | "Harlow Quinn followed, badge bouncing" | | 2 | "She didn't slow down." | | 3 | "The crowd—a strange assortment of" | | 4 | "Eyes followed her pursuit through" | | 5 | "The clique operated in shadows," | | 6 | "The suspect ducked left into" | | 7 | "Harlow rounded the corner and" | | 8 | "The woman's eyes flicked past" | | 9 | "The word sent a chill" | | 10 | "The Veil Market shifted every" | | 11 | "This month it occupied an" | | 12 | "The woman shrugged, her smile" | | 13 | "Harlow's hand found her radio." | | 14 | "Backup was twenty minutes out," | | 15 | "She thought of DS Morris." | | 16 | "The case three years ago." | | 17 | "The unexplained circumstances." | | 18 | "The supernatural origins she'd refused" | | 19 | "Morris had gone into something" |
| | ratio | 0.779 | |
| 52.63% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 95 | | matches | | | ratio | 0.011 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 3 | | matches | | 0 | "Three weeks of following breadcrumbs that led to nowhere and everywhere at once." | | 1 | "Then a dozen, flickering to life along the tunnel walls, casting dancing shadows that seemed to move of their own accord." | | 2 | "Something wearing Morris's face, wearing his smile, wearing the memory of her partner like a mask." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 3 | | matches | | 0 | "Harlow advanced slowly, her shoes splashing through accumulated puddles" | | 1 | "He shook, hair sticking to his forehead" | | 2 | "she called out, her voice steady despite the hammering of her heart" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "she called out (call out)" |
| | dialogueSentences | 38 | | tagDensity | 0.079 | | leniency | 0.158 | | rawRatio | 0.333 | | effectiveRatio | 0.053 | |