| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1187 | | 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) | |
| 83.15% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1187 | | totalAiIsms | 4 | | found | | 0 | | word | "practiced ease" | | count | 1 |
| | 1 | | | 2 | | | 3 | |
| | highlights | | 0 | "practiced ease" | | 1 | "familiar" | | 2 | "grave" | | 3 | "echoing" |
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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 | 134 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 134 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 135 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 33 | | totalWords | 1185 | | ratio | 0.028 | | matches | | 0 | "Morris." | | 1 | "Think, Harlow." | | 2 | "You don't follow without backup. You don't follow without knowing what's down there. You call it in, you wait for support, and you do it by the book." | | 3 | "Coincidence." | | 4 | "Shh." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 1183 | | uniqueNames | 13 | | maxNameDensity | 0.51 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Herrera" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 2 | | Tomás | 1 | | Herrera | 5 | | Underground | 2 | | Morris | 4 | | Deptford | 1 | | English | 1 | | London | 1 | | Saint | 1 | | Christopher | 1 | | Quinn | 6 |
| | persons | | 0 | "Tomás" | | 1 | "Herrera" | | 2 | "Morris" | | 3 | "English" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Quinn" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Deptford" | | 3 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 51.32% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 76 | | glossingSentenceCount | 3 | | matches | | 0 | "quite decipher" | | 1 | "looked like a maintenance entrance for th" | | 2 | "seemed wrong for an Underground station" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.844 | | wordCount | 1185 | | matches | | 0 | "Not gradually but all at once, as if she'd walked through an invisible barrier" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 135 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 24.18 | | std | 17.37 | | cv | 0.718 | | sampleLengths | | 0 | 29 | | 1 | 21 | | 2 | 2 | | 3 | 5 | | 4 | 54 | | 5 | 26 | | 6 | 27 | | 7 | 39 | | 8 | 7 | | 9 | 53 | | 10 | 1 | | 11 | 51 | | 12 | 43 | | 13 | 29 | | 14 | 27 | | 15 | 35 | | 16 | 9 | | 17 | 54 | | 18 | 35 | | 19 | 2 | | 20 | 42 | | 21 | 5 | | 22 | 35 | | 23 | 32 | | 24 | 22 | | 25 | 45 | | 26 | 3 | | 27 | 36 | | 28 | 9 | | 29 | 1 | | 30 | 5 | | 31 | 56 | | 32 | 31 | | 33 | 28 | | 34 | 52 | | 35 | 12 | | 36 | 45 | | 37 | 14 | | 38 | 33 | | 39 | 16 | | 40 | 1 | | 41 | 26 | | 42 | 31 | | 43 | 4 | | 44 | 3 | | 45 | 19 | | 46 | 1 | | 47 | 26 | | 48 | 3 |
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| 94.79% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 134 | | matches | | 0 | "was gone" | | 1 | "been soaked" | | 2 | "been sealed" | | 3 | "been led" |
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| 59.65% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 190 | | matches | | 0 | "was slowing" | | 1 | "was explaining" | | 2 | "was crossing" | | 3 | "was heading" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 135 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1185 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 38 | | adverbRatio | 0.032067510548523206 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.008438818565400843 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 135 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 135 | | mean | 8.78 | | std | 6.57 | | cv | 0.749 | | sampleLengths | | 0 | 12 | | 1 | 17 | | 2 | 2 | | 3 | 16 | | 4 | 3 | | 5 | 2 | | 6 | 2 | | 7 | 3 | | 8 | 16 | | 9 | 9 | | 10 | 2 | | 11 | 6 | | 12 | 21 | | 13 | 1 | | 14 | 2 | | 15 | 12 | | 16 | 11 | | 17 | 3 | | 18 | 1 | | 19 | 23 | | 20 | 10 | | 21 | 16 | | 22 | 13 | | 23 | 7 | | 24 | 3 | | 25 | 19 | | 26 | 5 | | 27 | 14 | | 28 | 12 | | 29 | 1 | | 30 | 5 | | 31 | 1 | | 32 | 15 | | 33 | 30 | | 34 | 9 | | 35 | 8 | | 36 | 1 | | 37 | 3 | | 38 | 22 | | 39 | 2 | | 40 | 4 | | 41 | 5 | | 42 | 18 | | 43 | 5 | | 44 | 9 | | 45 | 1 | | 46 | 1 | | 47 | 11 | | 48 | 6 | | 49 | 10 |
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| 71.11% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.4666666666666667 | | totalSentences | 135 | | uniqueOpeners | 63 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 112 | | matches | | 0 | "Even the fit ones tired" | | 1 | "Just a flash of his" | | 2 | "Then he was gone, swallowed" | | 3 | "Then he looked up." | | 4 | "Directly at the stairwell." | | 5 | "Directly at her." | | 6 | "Then he smiled, and the" |
| | ratio | 0.063 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 112 | | matches | | 0 | "They never did." | | 1 | "She yanked the earpiece out" | | 2 | "He was slowing." | | 3 | "Her watch face caught the" | | 4 | "She'd earned every line on" | | 5 | "She shoved the thought aside." | | 6 | "She'd seen them through the" | | 7 | "She squeezed through, the metal" | | 8 | "Her third favourite." | | 9 | "She knew the stories." | | 10 | "His shoulder hit the maintenance" | | 11 | "It groaned open, spilling weak" | | 12 | "She stopped at the entrance." | | 13 | "Her torch beam cut through" | | 14 | "*You don't follow without backup." | | 15 | "You don't follow without knowing" | | 16 | "You call it in, you" | | 17 | "She unholstered her radio again." | | 18 | "Her mobile showed no service." | | 19 | "Her torch found something on" |
| | ratio | 0.277 | |
| 49.29% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 92 | | totalSentences | 112 | | matches | | 0 | "The man in the grey" | | 1 | "Quinn's boots hit the wet" | | 2 | "This one wouldn't." | | 3 | "They never did." | | 4 | "The Soho crowds parted for" | | 5 | "A woman's shopping bag burst" | | 6 | "Quinn hurdled them without breaking" | | 7 | "The grey coat ducked left" | | 8 | "This close to the old" | | 9 | "She yanked the earpiece out" | | 10 | "He was slowing." | | 11 | "The alley opened onto a" | | 12 | "Warehouses lined both sides, their" | | 13 | "Symbols that looked almost familiar," | | 14 | "The grey coat disappeared around" | | 15 | "Quinn pushed harder." | | 16 | "Her watch face caught the" | | 17 | "She'd earned every line on" | | 18 | "Morris used to tell her" | | 19 | "She shoved the thought aside." |
| | ratio | 0.821 | |
| 44.64% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 112 | | matches | | 0 | "As if the water couldn't" |
| | ratio | 0.009 | |
| 35.04% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 8 | | matches | | 0 | "Symbols that looked almost familiar, the way a word sounds when you're half-asleep." | | 1 | "She'd seen them through the window, heads bent together, the medic's hands moving in that precise way he had when he was explaining something he shouldn't be di…" | | 2 | "The kind of stories that ended with officers transferred to desk duty or, worse, transferred to psychiatric evaluations." | | 3 | "Running from something that terrified him more than a detective's wrath." | | 4 | "Her torch beam cut through the darkness, illuminating a spiral staircase that descended far deeper than any maintenance entrance should." | | 5 | "Everything else outside had been soaked by the rain that had started falling an hour ago, but these steps were bone dry." | | 6 | "Not gradually but all at once, as if she'd walked through an invisible barrier." | | 7 | "The grey coat was crossing the market, weaving between stalls with the ease of someone who'd done this before." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |