| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said instead [instead]" |
| | dialogueSentences | 34 | | tagDensity | 0.324 | | leniency | 0.647 | | rawRatio | 0.091 | | effectiveRatio | 0.059 | |
| 82.80% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1163 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "suddenly" | | 1 | "truly" | | 2 | "quickly" | | 3 | "very" |
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| 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) | |
| 87.10% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1163 | | totalAiIsms | 3 | | found | | | highlights | | |
| 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 | 84 | | matches | (empty) | |
| 91.84% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 84 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1163 | | 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 | 19 | | wordCount | 935 | | uniqueNames | 12 | | maxNameDensity | 0.75 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Dean | 1 | | Street | 1 | | Harlow | 1 | | Quinn | 7 | | Silence | 1 | | Soho | 1 | | Tube | 1 | | Morris | 1 | | Camden | 2 | | Laughter | 1 | | Three | 1 | | Tuesday | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | | 0 | "Dean" | | 1 | "Street" | | 2 | "Soho" | | 3 | "Three" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 51 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.86 | | wordCount | 1163 | | matches | | 0 | "not left or right but straight through a rusted door set into the alley wall" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 107 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 23.73 | | std | 19.97 | | cv | 0.841 | | sampleLengths | | 0 | 39 | | 1 | 31 | | 2 | 12 | | 3 | 74 | | 4 | 53 | | 5 | 35 | | 6 | 23 | | 7 | 25 | | 8 | 8 | | 9 | 11 | | 10 | 4 | | 11 | 83 | | 12 | 14 | | 13 | 3 | | 14 | 58 | | 15 | 73 | | 16 | 16 | | 17 | 37 | | 18 | 1 | | 19 | 18 | | 20 | 32 | | 21 | 16 | | 22 | 3 | | 23 | 3 | | 24 | 16 | | 25 | 20 | | 26 | 14 | | 27 | 52 | | 28 | 27 | | 29 | 19 | | 30 | 18 | | 31 | 43 | | 32 | 10 | | 33 | 17 | | 34 | 24 | | 35 | 6 | | 36 | 3 | | 37 | 16 | | 38 | 4 | | 39 | 20 | | 40 | 40 | | 41 | 6 | | 42 | 23 | | 43 | 2 | | 44 | 7 | | 45 | 53 | | 46 | 5 | | 47 | 22 | | 48 | 24 |
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| 96.91% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 84 | | matches | | 0 | "been pulled" | | 1 | "being passed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 161 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 107 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 943 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.026511134676564158 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0042417815482502655 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 10.87 | | std | 8.64 | | cv | 0.795 | | sampleLengths | | 0 | 39 | | 1 | 2 | | 2 | 19 | | 3 | 6 | | 4 | 4 | | 5 | 7 | | 6 | 5 | | 7 | 21 | | 8 | 26 | | 9 | 22 | | 10 | 1 | | 11 | 1 | | 12 | 3 | | 13 | 7 | | 14 | 20 | | 15 | 14 | | 16 | 12 | | 17 | 9 | | 18 | 20 | | 19 | 2 | | 20 | 4 | | 21 | 4 | | 22 | 19 | | 23 | 25 | | 24 | 8 | | 25 | 2 | | 26 | 9 | | 27 | 4 | | 28 | 15 | | 29 | 18 | | 30 | 28 | | 31 | 3 | | 32 | 19 | | 33 | 14 | | 34 | 3 | | 35 | 18 | | 36 | 12 | | 37 | 3 | | 38 | 25 | | 39 | 4 | | 40 | 21 | | 41 | 21 | | 42 | 11 | | 43 | 16 | | 44 | 2 | | 45 | 14 | | 46 | 10 | | 47 | 19 | | 48 | 7 | | 49 | 1 |
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| 85.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5420560747663551 | | totalSentences | 107 | | uniqueOpeners | 58 | |
| 44.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 75 | | matches | | 0 | "Then, just as suddenly, silence." |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 75 | | matches | | 0 | "She'd put two rounds into" | | 1 | "Her shout bounced off wet" | | 2 | "She slowed at the alley" | | 3 | "She called it in." | | 4 | "She went in anyway." | | 5 | "Her torch beam swept tile" | | 6 | "Her radio crackled, then dissolved" | | 7 | "She kept walking." | | 8 | "She'd have known." | | 9 | "She knew everything about this" | | 10 | "They'd been pulled up, and" | | 11 | "She could smell it from" | | 12 | "She didn't look up from" | | 13 | "She looked away before she" | | 14 | "she said instead" | | 15 | "Her eyes were the pale" | | 16 | "She held up her warrant" | | 17 | "It rippled down the stall" | | 18 | "He looked her over the" | | 19 | "She felt the cold point" |
| | ratio | 0.267 | |
| 53.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 75 | | matches | | 0 | "The suspect vaulted a recycling" | | 1 | "She'd put two rounds into" | | 2 | "Amateurs surrendered after the first" | | 3 | "This man had sprinted." | | 4 | "Her shout bounced off wet" | | 5 | "She slowed at the alley" | | 6 | "A Tube maintenance access, painted" | | 7 | "The handle gleamed where his" | | 8 | "Quinn pressed her left wrist" | | 9 | "The worn leather watch strap," | | 10 | "Pain was a compass." | | 11 | "She called it in." | | 12 | "Dispatch answered with static and" | | 13 | "Herrera would bleed into the" | | 14 | "She went in anyway." | | 15 | "The stairs were narrow and" | | 16 | "Her torch beam swept tile" | | 17 | "A word repeated down the" | | 18 | "Her radio crackled, then dissolved" | | 19 | "She kept walking." |
| | ratio | 0.813 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 75 | | matches | (empty) | | ratio | 0 | |
| 65.64% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 4 | | matches | | 0 | "The stairs were narrow and slick, lit by caged bulbs that buzzed like trapped wasps." | | 1 | "Painted over with signage from decades past, yes, but beneath the paint, drawn in something that had dried a rust-red she didn't want to name, there were symbol…" | | 2 | "Dozens of torches, hundreds, strung along a corridor of stalls that stretched further than the tunnel had any right to go." | | 3 | "Far down the corridor of stalls, past the flickering torches and the silhouettes of things that were shopping as calmly as housewives on a Tuesday, something sc…" |
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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 | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 34 | | tagDensity | 0.147 | | leniency | 0.294 | | rawRatio | 0.2 | | effectiveRatio | 0.059 | |