| 33.33% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 1 | | adverbTags | | 0 | "She glanced around [around]" |
| | dialogueSentences | 12 | | tagDensity | 0.417 | | leniency | 0.833 | | rawRatio | 0.2 | | effectiveRatio | 0.167 | |
| 91.27% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1146 | | totalAiIsmAdverbs | 2 | | 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) | |
| 60.73% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1146 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "chill" | | 1 | "pounding" | | 2 | "navigated" | | 3 | "warmth" | | 4 | "scanned" | | 5 | "glinting" | | 6 | "raced" | | 7 | "glint" | | 8 | "echoing" |
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| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "heart pounded in chest" | | count | 1 |
| | 1 | | label | "eyes widened/narrowed" | | count | 1 |
| | 2 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "heart raced in her chest" | | 1 | "eyes widened" | | 2 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 88 | | matches | | |
| 61.69% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 4 | | narrationSentences | 88 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "started to" | | 2 | "tried to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1146 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 77.95% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 1041 | | uniqueNames | 6 | | maxNameDensity | 1.44 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 15 | | Morris | 2 | | Tube | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | (empty) | | globalScore | 0.78 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | 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 | 1146 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 96 | | matches | | |
| 61.01% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 39.52 | | std | 14.37 | | cv | 0.364 | | sampleLengths | | 0 | 64 | | 1 | 65 | | 2 | 53 | | 3 | 32 | | 4 | 80 | | 5 | 51 | | 6 | 20 | | 7 | 15 | | 8 | 27 | | 9 | 42 | | 10 | 37 | | 11 | 38 | | 12 | 45 | | 13 | 35 | | 14 | 39 | | 15 | 40 | | 16 | 50 | | 17 | 31 | | 18 | 30 | | 19 | 25 | | 20 | 25 | | 21 | 31 | | 22 | 31 | | 23 | 46 | | 24 | 50 | | 25 | 51 | | 26 | 40 | | 27 | 32 | | 28 | 21 |
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| 85.33% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 88 | | matches | | 0 | "were covered" | | 1 | "were sold" | | 2 | "being said" | | 3 | "was torn" | | 4 | "was lined" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 174 | | matches | | 0 | "was getting" | | 1 | "was going" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 96 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 311 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 9 | | adverbRatio | 0.028938906752411574 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.01607717041800643 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 11.94 | | std | 4.99 | | cv | 0.418 | | sampleLengths | | 0 | 16 | | 1 | 23 | | 2 | 25 | | 3 | 21 | | 4 | 20 | | 5 | 7 | | 6 | 17 | | 7 | 24 | | 8 | 15 | | 9 | 7 | | 10 | 7 | | 11 | 13 | | 12 | 19 | | 13 | 22 | | 14 | 17 | | 15 | 7 | | 16 | 16 | | 17 | 7 | | 18 | 11 | | 19 | 14 | | 20 | 22 | | 21 | 9 | | 22 | 6 | | 23 | 10 | | 24 | 10 | | 25 | 12 | | 26 | 3 | | 27 | 9 | | 28 | 12 | | 29 | 6 | | 30 | 15 | | 31 | 11 | | 32 | 16 | | 33 | 15 | | 34 | 12 | | 35 | 10 | | 36 | 13 | | 37 | 17 | | 38 | 8 | | 39 | 17 | | 40 | 14 | | 41 | 14 | | 42 | 20 | | 43 | 15 | | 44 | 10 | | 45 | 10 | | 46 | 3 | | 47 | 9 | | 48 | 7 | | 49 | 12 |
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| 36.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.28125 | | totalSentences | 96 | | uniqueOpeners | 27 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 87 | | matches | (empty) | | ratio | 0 | |
| 22.30% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 43 | | totalSentences | 87 | | matches | | 0 | "She was getting too old" | | 1 | "She'd lost her partner, her" | | 2 | "She followed the suspect down" | | 3 | "He seemed to know exactly" | | 4 | "They came to a stop" | | 5 | "She could call for backup," | | 6 | "She had to know what" | | 7 | "She pushed through the door," | | 8 | "She scanned the room quickly," | | 9 | "He was nowhere to be" | | 10 | "She glanced around, looking for" | | 11 | "Her gaze landed on a" | | 12 | "She strode over to it," | | 13 | "Her fingers found a switch" | | 14 | "She had a feeling she" | | 15 | "She followed the tracks, the" | | 16 | "He spoke to a few" | | 17 | "She had to get closer," | | 18 | "She pulled her jacket tighter" | | 19 | "She stepped into the light," |
| | ratio | 0.494 | |
| 17.47% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 87 | | matches | | 0 | "The rain pounded against the" | | 1 | "Detective Harlow Quinn blinked the" | | 2 | "The suspect, a young man" | | 3 | "Quinn's sensible flats splashed through" | | 4 | "She was getting too old" | | 5 | "The file on the late" | | 6 | "She'd lost her partner, her" | | 7 | "Something with claws dipped in" | | 8 | "She followed the suspect down" | | 9 | "He seemed to know exactly" | | 10 | "They came to a stop" | | 11 | "The suspect glanced back at" | | 12 | "Quinn gritted her teeth, weighing" | | 13 | "She could call for backup," | | 14 | "She had to know what" | | 15 | "She pushed through the door," | | 16 | "The walls were covered in" | | 17 | "She scanned the room quickly," | | 18 | "He was nowhere to be" | | 19 | "Quinn approached the bar, keeping" |
| | ratio | 0.885 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 87 | | matches | | 0 | "Where secrets were sold like" | | 1 | "Before he was torn apart" |
| | ratio | 0.023 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 2 | | matches | | 0 | "She was getting too old for this, she thought bitterly, the sharp pains in her joints agreeing with the sentiment." | | 1 | "Quinn kept to the shadows, watching as the suspect moved through the crowd, his medallion glinting in the dull light." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 2 | | matches | | 0 | "he said, his voice barely audible over the murmurs of the crowd" | | 1 | "he said, his voice thick with exhaustion" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |