| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 94.35% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 885 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 885 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | word | "down her spine" | | count | 1 |
| | 18 | |
| | highlights | | 0 | "chill" | | 1 | "rhythmic" | | 2 | "navigating" | | 3 | "glinting" | | 4 | "fleeting" | | 5 | "intricate" | | 6 | "flicker" | | 7 | "unreadable" | | 8 | "depths" | | 9 | "streaming" | | 10 | "scanning" | | 11 | "echoed" | | 12 | "cacophony" | | 13 | "resonated" | | 14 | "pulse" | | 15 | "warmth" | | 16 | "silence" | | 17 | "down her spine" | | 18 | "echoing" |
| |
| 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 | 71 | | matches | (empty) | |
| 82.49% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 71 | | filterMatches | | | hedgeMatches | | 0 | "appeared to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 71 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 884 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 884 | | uniqueNames | 11 | | maxNameDensity | 0.9 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 8 | | Herrera | 2 | | Saint | 1 | | Christopher | 1 | | Tomás | 7 | | Morris | 3 | | London | 1 | | Tube | 1 | | Camden | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Tomás" | | 6 | "Morris" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 884 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 71 | | matches | (empty) | |
| 51.86% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 9 | | mean | 98.22 | | std | 32.56 | | cv | 0.331 | | sampleLengths | | 0 | 135 | | 1 | 113 | | 2 | 71 | | 3 | 131 | | 4 | 80 | | 5 | 93 | | 6 | 99 | | 7 | 132 | | 8 | 30 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 71 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 143 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 71 | | ratio | 0.014 | | matches | | 0 | "The air here carried a different scent—something metallic, something earthy, overlaid with a faint sweetness, like dried herbs." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 892 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, bone-white object," |
| | adverbCount | 28 | | adverbRatio | 0.03139013452914798 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.01233183856502242 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 71 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 71 | | mean | 12.45 | | std | 7.35 | | cv | 0.59 | | sampleLengths | | 0 | 16 | | 1 | 16 | | 2 | 3 | | 3 | 27 | | 4 | 17 | | 5 | 22 | | 6 | 34 | | 7 | 25 | | 8 | 16 | | 9 | 9 | | 10 | 5 | | 11 | 14 | | 12 | 14 | | 13 | 10 | | 14 | 15 | | 15 | 2 | | 16 | 3 | | 17 | 16 | | 18 | 8 | | 19 | 3 | | 20 | 26 | | 21 | 18 | | 22 | 9 | | 23 | 14 | | 24 | 16 | | 25 | 10 | | 26 | 15 | | 27 | 24 | | 28 | 27 | | 29 | 16 | | 30 | 12 | | 31 | 14 | | 32 | 1 | | 33 | 1 | | 34 | 4 | | 35 | 14 | | 36 | 1 | | 37 | 5 | | 38 | 14 | | 39 | 14 | | 40 | 12 | | 41 | 21 | | 42 | 15 | | 43 | 12 | | 44 | 19 | | 45 | 14 | | 46 | 5 | | 47 | 4 | | 48 | 23 | | 49 | 3 |
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| 44.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.2676056338028169 | | totalSentences | 71 | | uniqueOpeners | 19 | |
| 49.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 67 | | matches | | 0 | "Just brick and boarded windows." |
| | ratio | 0.015 | |
| 76.72% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 67 | | matches | | 0 | "Her lungs burned." | | 1 | "She pumped her legs, the" | | 2 | "He moved with a dancer’s" | | 3 | "Her sharp jaw was set." | | 4 | "She spotted Tomás again, a" | | 5 | "He veered left, ducking down" | | 6 | "She pushed herself harder, the" | | 7 | "He headed straight for what" | | 8 | "He pulled out a small," | | 9 | "He pressed it against a" | | 10 | "He glanced back, his warm" | | 11 | "She slammed her palm against" | | 12 | "She circled the derelict shop," | | 13 | "She returned to the door," | | 14 | "She pulled out her tactical" | | 15 | "Her mind flashed back to" | | 16 | "She knew Tomás Herrera was" | | 17 | "He was part of the" | | 18 | "She pulled back from the" | | 19 | "She would find another way" |
| | ratio | 0.358 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 67 | | matches | | 0 | "Rain slicked the Soho street," | | 1 | "Detective Harlow Quinn’s breath hitched" | | 2 | "Her lungs burned." | | 3 | "She pumped her legs, the" | | 4 | "Tomás Herrera wove through the" | | 5 | "He moved with a dancer’s" | | 6 | "Each time Quinn closed the" | | 7 | "A sharp turn off the" | | 8 | "The alley walls rose high," | | 9 | "Quinn’s closely cropped salt-and-pepper hair" | | 10 | "Her sharp jaw was set." | | 11 | "She spotted Tomás again, a" | | 12 | "He veered left, ducking down" | | 13 | "Quinn’s military precision in her" | | 14 | "She pushed herself harder, the" | | 15 | "The passage opened into a" | | 16 | "A lone, flickering lamppost cast" | | 17 | "Tomás didn’t hesitate." | | 18 | "He headed straight for what" | | 19 | "The air here carried a" |
| | ratio | 0.955 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 67 | | matches | (empty) | | ratio | 0 | |
| 97.26% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 47 | | technicalSentenceCount | 3 | | matches | | 0 | "Quinn reached the door, her chest heaving, water streaming down her face." | | 1 | "The carving Tomás had touched stood out, intricate knotwork swirling into grotesque faces, their mouths gaping in silent screams." | | 2 | "But the memory of Morris, the gnawing suspicion that had haunted her for three years, whispered a different command." |
| |
| 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 | |