| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 2 | | adverbTags | | 0 | "he gestured vaguely [vaguely]" | | 1 | "the phone had just [just]" |
| | dialogueSentences | 60 | | tagDensity | 0.35 | | leniency | 0.7 | | rawRatio | 0.095 | | effectiveRatio | 0.067 | |
| 79.66% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1229 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 71.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1229 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "flicker" | | 1 | "silk" | | 2 | "warmth" | | 3 | "silence" | | 4 | "encounter" | | 5 | "unreadable" |
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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 | 55 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 55 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 93 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 6 | | totalWords | 1229 | | ratio | 0.005 | | matches | | 0 | "you" | | 1 | "rock and roll" | | 2 | "amicable" | | 3 | "me" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 12 | | wordCount | 800 | | uniqueNames | 4 | | maxNameDensity | 0.63 | | worstName | "Silas" | | maxWindowNameDensity | 1 | | worstWindowName | "Dylan" | | discoveredNames | | Cardiff | 1 | | Dylan | 4 | | Silas | 5 | | Rory | 2 |
| | persons | | | places | | | globalScore | 1 | | windowScore | 1 | |
| 38.89% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite a laugh" | | 1 | "sounded like the boy she remembered instea" |
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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 | 1229 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 93 | | matches | | 0 | "mattered, that nothing" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 20.15 | | std | 17.2 | | cv | 0.853 | | sampleLengths | | 0 | 12 | | 1 | 41 | | 2 | 1 | | 3 | 23 | | 4 | 3 | | 5 | 35 | | 6 | 6 | | 7 | 23 | | 8 | 3 | | 9 | 65 | | 10 | 3 | | 11 | 6 | | 12 | 31 | | 13 | 45 | | 14 | 32 | | 15 | 3 | | 16 | 8 | | 17 | 20 | | 18 | 2 | | 19 | 32 | | 20 | 32 | | 21 | 8 | | 22 | 44 | | 23 | 2 | | 24 | 49 | | 25 | 34 | | 26 | 20 | | 27 | 6 | | 28 | 1 | | 29 | 36 | | 30 | 17 | | 31 | 3 | | 32 | 12 | | 33 | 2 | | 34 | 25 | | 35 | 6 | | 36 | 30 | | 37 | 56 | | 38 | 15 | | 39 | 2 | | 40 | 43 | | 41 | 36 | | 42 | 20 | | 43 | 3 | | 44 | 2 | | 45 | 52 | | 46 | 24 | | 47 | 8 | | 48 | 32 | | 49 | 11 |
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| 98.88% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 55 | | matches | | |
| 61.11% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 144 | | matches | | 0 | "was trying" | | 1 | "was trying" | | 2 | "was already moving" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 93 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 801 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.03870162297128589 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.01373283395755306 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 93 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 93 | | mean | 13.22 | | std | 10.02 | | cv | 0.758 | | sampleLengths | | 0 | 12 | | 1 | 2 | | 2 | 22 | | 3 | 17 | | 4 | 1 | | 5 | 23 | | 6 | 3 | | 7 | 20 | | 8 | 15 | | 9 | 6 | | 10 | 16 | | 11 | 7 | | 12 | 3 | | 13 | 15 | | 14 | 29 | | 15 | 6 | | 16 | 4 | | 17 | 11 | | 18 | 3 | | 19 | 6 | | 20 | 31 | | 21 | 33 | | 22 | 12 | | 23 | 19 | | 24 | 13 | | 25 | 3 | | 26 | 8 | | 27 | 15 | | 28 | 5 | | 29 | 2 | | 30 | 12 | | 31 | 20 | | 32 | 18 | | 33 | 2 | | 34 | 2 | | 35 | 10 | | 36 | 8 | | 37 | 14 | | 38 | 30 | | 39 | 2 | | 40 | 29 | | 41 | 20 | | 42 | 18 | | 43 | 16 | | 44 | 4 | | 45 | 16 | | 46 | 6 | | 47 | 1 | | 48 | 18 | | 49 | 18 |
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| 93.55% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5806451612903226 | | totalSentences | 93 | | uniqueOpeners | 54 | |
| 68.03% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 49 | | matches | | 0 | "Maybe somebody saying it out" |
| | ratio | 0.02 | |
| 15.92% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 49 | | matches | | 0 | "He looked up from the" | | 1 | "She set the tray down" | | 2 | "He laughed, short and awkward," | | 3 | "She meant it two ways," | | 4 | "He said it like he" | | 5 | "She crossed her arms, studying" | | 6 | "He lifted his glass, some" | | 7 | "He turned the glass, watching" | | 8 | "It used to be the" | | 9 | "He said it flat, no" | | 10 | "She shook her head, barely," | | 11 | "She kept her voice level," | | 12 | "He studied her properly then," | | 13 | "He turned the glass again," | | 14 | "he made a small, useless" | | 15 | "She shrugged, and it wasn't" | | 16 | "He looked at her like" | | 17 | "he said, before he could" | | 18 | "he gestured vaguely" | | 19 | "She reached for her glass" |
| | ratio | 0.51 | |
| 21.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 43 | | totalSentences | 49 | | matches | | 0 | "Rory nearly dropped the tray" | | 1 | "He looked up from the" | | 2 | "Nobody called her that anymore," | | 3 | "She set the tray down" | | 4 | "He laughed, short and awkward," | | 5 | "She meant it two ways," | | 6 | "The Dylan she remembered had" | | 7 | "This Dylan filled his shirt" | | 8 | "A crease between his brows" | | 9 | "He said it like he" | | 10 | "She crossed her arms, studying" | | 11 | "He lifted his glass, some" | | 12 | "The pause told her everything" | | 13 | "He turned the glass, watching" | | 14 | "A short, hollow sound, not" | | 15 | "Rory pulled out the chair" | | 16 | "It used to be the" | | 17 | "He said it flat, no" | | 18 | "Something shifted in his face" | | 19 | "The word came out like" |
| | ratio | 0.878 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 49 | | matches | | 0 | "Because maybe it would have" |
| | ratio | 0.02 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 5 | | matches | | 0 | "The Dylan she remembered had been all elbows and ambition, six foot of nervous energy who quoted case law in the union bar to impress girls who weren't impresse…" | | 1 | "The bar noise filled the gap, someone's laughter three tables over, the low scrape of a chair, Silas cracking ice behind the counter with the rhythm of a man wh…" | | 2 | "He looked at her like he was trying to reconcile two people who couldn't possibly be the same one, the girl who'd argued moot court cases with the precision of …" | | 3 | "That got a real laugh out of him this time, short but genuine, the first thing all evening that sounded like the boy she remembered instead of the man who'd rep…" | | 4 | "His eyes found hers across the room, steady, unreadable, the kind of look that had nothing to do with whisky or old university friends." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 2 | | fancyTags | | 0 | "He laughed (laugh)" | | 1 | "Something shifted (shift)" |
| | dialogueSentences | 60 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0.2 | | effectiveRatio | 0.067 | |