| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1278 | | 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) | |
| 88.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1278 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "pulse" | | 1 | "familiar" | | 2 | "flicker" |
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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 | 113 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 113 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1278 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 1228 | | uniqueNames | 18 | | maxNameDensity | 0.81 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 10 | | Bayham | 1 | | Street | 1 | | Camden | 1 | | Hackney | 1 | | Conversational | 1 | | Kentish | 1 | | Town | 1 | | Road | 1 | | Elliot | 1 | | Morris | 2 | | Deptford | 1 | | Underground | 1 | | Northern | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 1 | | Eighteen | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Elliot" | | 2 | "Morris" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Herrera" |
| | places | | 0 | "Bayham" | | 1 | "Street" | | 2 | "Hackney" | | 3 | "Kentish" | | 4 | "Town" | | 5 | "Road" | | 6 | "Deptford" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like they'd been carried down in p" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.782 | | wordCount | 1278 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 29.72 | | std | 25.79 | | cv | 0.868 | | sampleLengths | | 0 | 26 | | 1 | 41 | | 2 | 67 | | 3 | 6 | | 4 | 84 | | 5 | 11 | | 6 | 29 | | 7 | 36 | | 8 | 9 | | 9 | 29 | | 10 | 13 | | 11 | 49 | | 12 | 16 | | 13 | 52 | | 14 | 28 | | 15 | 7 | | 16 | 9 | | 17 | 5 | | 18 | 56 | | 19 | 1 | | 20 | 100 | | 21 | 15 | | 22 | 11 | | 23 | 9 | | 24 | 54 | | 25 | 14 | | 26 | 61 | | 27 | 34 | | 28 | 3 | | 29 | 36 | | 30 | 108 | | 31 | 38 | | 32 | 20 | | 33 | 43 | | 34 | 31 | | 35 | 1 | | 36 | 48 | | 37 | 7 | | 38 | 22 | | 39 | 6 | | 40 | 28 | | 41 | 2 | | 42 | 13 |
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| 89.74% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 113 | | matches | | 0 | "was frightened" | | 1 | "been scraped" | | 2 | "being swallowed" | | 3 | "been gutted" | | 4 | "been carried" |
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| 6.76% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 207 | | matches | | 0 | "was carrying" | | 1 | "was grinning" | | 2 | "was portioning" | | 3 | "wasn't even interesting" | | 4 | "was talking" | | 5 | "was pushing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 117 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1234 | | adjectiveStacks | 1 | | stackExamples | | 0 | "Warm, low, moving light," |
| | adverbCount | 29 | | adverbRatio | 0.023500810372771474 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004051863857374392 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 10.92 | | std | 10.76 | | cv | 0.985 | | sampleLengths | | 0 | 26 | | 1 | 4 | | 2 | 37 | | 3 | 2 | | 4 | 20 | | 5 | 31 | | 6 | 7 | | 7 | 4 | | 8 | 3 | | 9 | 6 | | 10 | 3 | | 11 | 28 | | 12 | 3 | | 13 | 23 | | 14 | 27 | | 15 | 2 | | 16 | 2 | | 17 | 7 | | 18 | 8 | | 19 | 1 | | 20 | 20 | | 21 | 25 | | 22 | 1 | | 23 | 5 | | 24 | 5 | | 25 | 9 | | 26 | 29 | | 27 | 2 | | 28 | 1 | | 29 | 10 | | 30 | 3 | | 31 | 4 | | 32 | 7 | | 33 | 35 | | 34 | 3 | | 35 | 13 | | 36 | 2 | | 37 | 8 | | 38 | 1 | | 39 | 41 | | 40 | 6 | | 41 | 3 | | 42 | 19 | | 43 | 2 | | 44 | 5 | | 45 | 9 | | 46 | 5 | | 47 | 25 | | 48 | 5 | | 49 | 3 |
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| 76.64% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.49572649572649574 | | totalSentences | 117 | | uniqueOpeners | 58 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 90 | | matches | | 0 | "Then he did the thing" | | 1 | "Almost like fingers checking." | | 2 | "Then she was through, and" |
| | ratio | 0.033 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 90 | | matches | | 0 | "Her boots found the grain" | | 1 | "She'd resoled them twice." | | 2 | "He hit the railings and" | | 3 | "He got one knee up," | | 4 | "She was forty-one and she'd" | | 5 | "She took the bins instead," | | 6 | "Her pulse hammered up under" | | 7 | "she called out" | | 8 | "It carried better than a" | | 9 | "He was thirty metres ahead," | | 10 | "He stopped at the shuttered" | | 11 | "It opened the way a" | | 12 | "He was grinning." | | 13 | "he said, and went down" | | 14 | "They'd written it up as" | | 15 | "She'd stopped believing the correct" | | 16 | "She turned her shoulder, went" | | 17 | "She went down." | | 18 | "She counted, because counting was" | | 19 | "She was a tourist." |
| | ratio | 0.278 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 90 | | matches | | 0 | "The suspect went left at" | | 1 | "Rain came sideways off the" | | 2 | "Her boots found the grain" | | 3 | "She'd resoled them twice." | | 4 | "He hit the railings and" | | 5 | "He got one knee up," | | 6 | "Quinn didn't vault." | | 7 | "She was forty-one and she'd" | | 8 | "She took the bins instead," | | 9 | "Her pulse hammered up under" | | 10 | "she called out" | | 11 | "It carried better than a" | | 12 | "He was thirty metres ahead," | | 13 | "Something pale in his hand." | | 14 | "He stopped at the shuttered" | | 15 | "The hoarding opened." | | 16 | "It opened the way a" | | 17 | "That was the part that" | | 18 | "Dozens of them, laughter, an" | | 19 | "The suspect glanced back at" |
| | ratio | 0.667 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 90 | | matches | (empty) | | ratio | 0 | |
| 35.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 6 | | matches | | 0 | "Left meant railings, wheelie bins, a dead end behind the chicken shop unless he could climb, and he was carrying something under his coat that swung heavy again…" | | 1 | "He got one knee up, hooked an arm, went over into the loading yard beyond with a clang that set the whole fence ringing like a struck bell." | | 2 | "Two sheets of chipboard covered in fly-posters, some club night in 2011, a missing cat, and they parted along a seam that hadn't existed a second earlier, and t…" | | 3 | "Dozens of them, laughter, an argument in a language that scraped, a bell, something that might have been a goat, all of it drifting up out of a hole in the grou…" | | 4 | "Wet tile and old smoke, that was the Underground, that was familiar." | | 5 | "A woman in a butcher's apron was portioning something that had far too many joints for a lamb." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 50.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 10 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0.333 | | effectiveRatio | 0.2 | |