| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 55 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.97% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1242 | | totalAiIsmAdverbs | 1 | | 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) | |
| 87.92% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1242 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "wavered" | | 1 | "etched" | | 2 | "quivered" |
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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 | 148 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 148 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 190 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1242 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 935 | | uniqueNames | 9 | | maxNameDensity | 1.39 | | worstName | "Whitmore" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Whitmore" | | discoveredNames | | Whitmore | 13 | | Quinn | 13 | | Cool | 1 | | Greek | 2 | | Latin | 1 | | Morris | 1 | | London | 1 | | North-northwest | 3 | | South | 4 |
| | persons | | 0 | "Whitmore" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | | | globalScore | 0.805 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1242 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 190 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 81 | | mean | 15.33 | | std | 16.34 | | cv | 1.066 | | sampleLengths | | 0 | 51 | | 1 | 22 | | 2 | 1 | | 3 | 6 | | 4 | 4 | | 5 | 45 | | 6 | 4 | | 7 | 13 | | 8 | 28 | | 9 | 8 | | 10 | 18 | | 11 | 1 | | 12 | 16 | | 13 | 21 | | 14 | 26 | | 15 | 4 | | 16 | 2 | | 17 | 69 | | 18 | 1 | | 19 | 20 | | 20 | 2 | | 21 | 7 | | 22 | 13 | | 23 | 67 | | 24 | 7 | | 25 | 28 | | 26 | 3 | | 27 | 6 | | 28 | 1 | | 29 | 13 | | 30 | 23 | | 31 | 30 | | 32 | 5 | | 33 | 1 | | 34 | 4 | | 35 | 23 | | 36 | 33 | | 37 | 6 | | 38 | 1 | | 39 | 39 | | 40 | 18 | | 41 | 7 | | 42 | 4 | | 43 | 29 | | 44 | 6 | | 45 | 49 | | 46 | 5 | | 47 | 2 | | 48 | 20 | | 49 | 26 |
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| 88.67% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 148 | | matches | | 0 | "been stripped" | | 1 | "been drawn" | | 2 | "were polished" | | 3 | "been disturbed" | | 4 | "been dragged" | | 5 | "was buttoned" | | 6 | "been made" | | 7 | "been built" |
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| 71.79% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 156 | | matches | | 0 | "were doing" | | 1 | "was already walking" | | 2 | "was learning" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 190 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 946 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.024312896405919663 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003171247357293869 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 190 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 190 | | mean | 6.54 | | std | 6.31 | | cv | 0.966 | | sampleLengths | | 0 | 6 | | 1 | 21 | | 2 | 24 | | 3 | 14 | | 4 | 8 | | 5 | 1 | | 6 | 6 | | 7 | 4 | | 8 | 2 | | 9 | 19 | | 10 | 15 | | 11 | 9 | | 12 | 4 | | 13 | 13 | | 14 | 5 | | 15 | 23 | | 16 | 3 | | 17 | 5 | | 18 | 9 | | 19 | 3 | | 20 | 6 | | 21 | 1 | | 22 | 14 | | 23 | 2 | | 24 | 11 | | 25 | 5 | | 26 | 5 | | 27 | 4 | | 28 | 4 | | 29 | 7 | | 30 | 7 | | 31 | 4 | | 32 | 4 | | 33 | 2 | | 34 | 13 | | 35 | 13 | | 36 | 3 | | 37 | 2 | | 38 | 2 | | 39 | 5 | | 40 | 13 | | 41 | 18 | | 42 | 1 | | 43 | 20 | | 44 | 2 | | 45 | 7 | | 46 | 3 | | 47 | 10 | | 48 | 4 | | 49 | 3 |
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| 62.98% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.43157894736842106 | | totalSentences | 190 | | uniqueOpeners | 82 | |
| 93.46% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 107 | | matches | | 0 | "Too smooth, too dark, more" | | 1 | "More than calm." | | 2 | "Away from every route she" |
| | ratio | 0.028 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 107 | | matches | | 0 | "She walked the circle." | | 1 | "She rubbed a fleck on" | | 2 | "It came away silver." | | 3 | "She skirted the arc, one" | | 4 | "She ducked under the tape" | | 5 | "His face was calm." | | 6 | "His shoes were polished, the" | | 7 | "His coat was buttoned to" | | 8 | "She had felt it once" | | 9 | "She checked anyway." | | 10 | "Her fingers brushed the inside" | | 11 | "She fished it out." | | 12 | "She turned the compass in" | | 13 | "She turned it again." | | 14 | "She walked around the body." | | 15 | "She closed her fist around" | | 16 | "She liked him for that." | | 17 | "She crouched and set the" | | 18 | "She stepped between the compass" | | 19 | "She stepped back." |
| | ratio | 0.271 | |
| 90.84% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 79 | | totalSentences | 107 | | matches | | 0 | "The escalator groaned under her" | | 1 | "Quinn kept her torch low," | | 2 | "The platform below glowed under" | | 3 | "DC Whitmore stood at the" | | 4 | "Quinn never corrected him anymore" | | 5 | "The dead man lay between" | | 6 | "The tunnel had been stripped" | | 7 | "Someone had picked the lock" | | 8 | "Quinn crouched at the cordon." | | 9 | "Chalk on the platform floor" | | 10 | "The candles stood in a" | | 11 | "Whitmore clicked his pen" | | 12 | "Quinn touched the nearest with" | | 13 | "She walked the circle." | | 14 | "The chalk wasn’t chalk." | | 15 | "She rubbed a fleck on" | | 16 | "It came away silver." | | 17 | "Whitmore, behind her" | | 18 | "She skirted the arc, one" | | 19 | "The sigils weren’t Greek or" |
| | ratio | 0.738 | |
| 46.73% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 107 | | matches | | 0 | "If something was behind it," |
| | ratio | 0.009 | |
| 98.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 2 | | matches | | 0 | "The platform below glowed under three arc lights, rigged along the curving ceiling tiles, throwing long shadows that stayed put when the lamps swayed." | | 1 | "The lines wavered in the same places, a repetitive tremor, a person who kept looking over a shoulder." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 55 | | tagDensity | 0.164 | | leniency | 0.327 | | rawRatio | 0 | | effectiveRatio | 0 | |