| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said finally [finally]" |
| | dialogueSentences | 51 | | tagDensity | 0.314 | | leniency | 0.627 | | rawRatio | 0.063 | | effectiveRatio | 0.039 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1457 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 72.55% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1457 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "could feel" | | 1 | "velvet" | | 2 | "processed" | | 3 | "mechanical" | | 4 | "flickered" | | 5 | "echoed" | | 6 | "pulse" |
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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 | 113 | | matches | (empty) | |
| 79.65% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 4 | | narrationSentences | 113 | | filterMatches | | | hedgeMatches | | 0 | "appeared to" | | 1 | "seemed to" | | 2 | "started to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 148 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1452 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 1097 | | uniqueNames | 12 | | maxNameDensity | 1.19 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Greek | 1 | | Street | 1 | | Quinn | 13 | | November | 1 | | Morris | 5 | | Shaftesbury | 1 | | Avenue | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 4 | | Sympathy | 1 | | Pressed | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Tomás" |
| | places | | 0 | "Greek" | | 1 | "Street" | | 2 | "November" | | 3 | "Shaftesbury" | | 4 | "Avenue" |
| | globalScore | 0.907 | | windowScore | 0.833 | |
| 48.65% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | glossingSentenceCount | 3 | | matches | | 0 | "smelled like the Morris case, though she'd" | | 1 | "looked like an abandoned tube entrance" | | 2 | "looked like gas lamps but burned an unset" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.689 | | wordCount | 1452 | | matches | | 0 | "Not threatening, but deliberate" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 148 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 78 | | mean | 18.62 | | std | 15.43 | | cv | 0.829 | | sampleLengths | | 0 | 36 | | 1 | 3 | | 2 | 47 | | 3 | 45 | | 4 | 41 | | 5 | 30 | | 6 | 6 | | 7 | 1 | | 8 | 26 | | 9 | 36 | | 10 | 39 | | 11 | 12 | | 12 | 2 | | 13 | 54 | | 14 | 35 | | 15 | 5 | | 16 | 51 | | 17 | 15 | | 18 | 50 | | 19 | 6 | | 20 | 2 | | 21 | 47 | | 22 | 9 | | 23 | 6 | | 24 | 22 | | 25 | 1 | | 26 | 5 | | 27 | 22 | | 28 | 3 | | 29 | 14 | | 30 | 2 | | 31 | 15 | | 32 | 8 | | 33 | 31 | | 34 | 4 | | 35 | 36 | | 36 | 22 | | 37 | 8 | | 38 | 5 | | 39 | 1 | | 40 | 28 | | 41 | 15 | | 42 | 16 | | 43 | 5 | | 44 | 16 | | 45 | 16 | | 46 | 2 | | 47 | 6 | | 48 | 4 | | 49 | 19 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 113 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 186 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 148 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1101 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.025431425976385105 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005449591280653951 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 148 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 148 | | mean | 9.81 | | std | 7.01 | | cv | 0.714 | | sampleLengths | | 0 | 16 | | 1 | 20 | | 2 | 3 | | 3 | 27 | | 4 | 20 | | 5 | 7 | | 6 | 22 | | 7 | 14 | | 8 | 2 | | 9 | 8 | | 10 | 15 | | 11 | 12 | | 12 | 6 | | 13 | 21 | | 14 | 9 | | 15 | 2 | | 16 | 4 | | 17 | 1 | | 18 | 3 | | 19 | 23 | | 20 | 10 | | 21 | 10 | | 22 | 16 | | 23 | 9 | | 24 | 4 | | 25 | 26 | | 26 | 5 | | 27 | 7 | | 28 | 2 | | 29 | 11 | | 30 | 17 | | 31 | 26 | | 32 | 19 | | 33 | 16 | | 34 | 5 | | 35 | 18 | | 36 | 10 | | 37 | 23 | | 38 | 2 | | 39 | 1 | | 40 | 12 | | 41 | 11 | | 42 | 19 | | 43 | 20 | | 44 | 6 | | 45 | 2 | | 46 | 2 | | 47 | 25 | | 48 | 12 | | 49 | 8 |
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| 72.07% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.47297297297297297 | | totalSentences | 148 | | uniqueOpeners | 70 | |
| 69.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 96 | | matches | | 0 | "Definitely bone, though she didn't" | | 1 | "Then she pocketed the bone" |
| | ratio | 0.021 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 96 | | matches | | 0 | "She pushed harder, boots slapping" | | 1 | "Her worn leather watch caught" | | 2 | "She yanked it free without" | | 3 | "She emerged onto the main" | | 4 | "She tried again." | | 5 | "She stared at the dark" | | 6 | "She could feel it in" | | 7 | "She kept one hand on" | | 8 | "She didn't frame it as" | | 9 | "His eyebrows rose." | | 10 | "He tilted his head, studying" | | 11 | "He pushed off from the" | | 12 | "She'd heard worse." | | 13 | "She met his gaze, held" | | 14 | "he said finally" | | 15 | "His jaw tightened" | | 16 | "He reached into his pocket," | | 17 | "He couldn't know about Morris." | | 18 | "He started to turn away," | | 19 | "He vanished into the crowd" |
| | ratio | 0.26 | |
| 64.17% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 96 | | matches | | 0 | "The suspect's coat whipped around" | | 1 | "She pushed harder, boots slapping" | | 2 | "The words disappeared into the" | | 3 | "The suspect, a wiry man" | | 4 | "Something that smelled like the" | | 5 | "The suspect ducked left, heading" | | 6 | "Quinn adjusted her trajectory, cutting" | | 7 | "Her worn leather watch caught" | | 8 | "She yanked it free without" | | 9 | "She emerged onto the main" | | 10 | "The metal gate hung open," | | 11 | "She tried again." | | 12 | "Nothing but that electrical hiss" | | 13 | "The rain intensified, plastering her" | | 14 | "Water ran down her sharp" | | 15 | "She stared at the dark" | | 16 | "Every instinct screamed wrong." | | 17 | "The kind of wrong that" | | 18 | "She could feel it in" | | 19 | "The stairs went deeper than" |
| | ratio | 0.792 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 45.45% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 6 | | matches | | 0 | "She pushed harder, boots slapping against wet cobblestones, her breath coming in sharp bursts that misted in the November air." | | 1 | "Three weeks of dead ends, false leads, and that gnawing feeling in her gut that said this case connected to something bigger." | | 2 | "The air grew thick, carrying scents that didn't belong together: incense and rotting meat, old books and fresh blood, something chemical and sharp underneath it…" | | 3 | "A young man leaned against a pillar nearby, arms crossed, watching her with warm brown eyes that held more knowledge than his apparent age suggested." | | 4 | "A vendor two stalls down began wrapping something that moved inside its paper packaging." | | 5 | "It led her to a tent at the back of the chamber, black fabric that absorbed the green light instead of reflecting it." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn repeated (repeat)" | | 1 | "A vendor muttering (mutter)" |
| | dialogueSentences | 51 | | tagDensity | 0.098 | | leniency | 0.196 | | rawRatio | 0.4 | | effectiveRatio | 0.078 | |