| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 969 | | 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) | |
| 43.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 969 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echo" | | 2 | "vibrated" | | 3 | "depths" | | 4 | "spectral" | | 5 | "scanning" | | 6 | "chilling" |
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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 | 1 | | narrationSentences | 77 | | matches | | |
| 68.65% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 77 | | filterMatches | | | hedgeMatches | | 0 | "seem to" | | 1 | "appeared to" | | 2 | "began to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 967 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 28.32% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 904 | | uniqueNames | 11 | | maxNameDensity | 2.43 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Quinn | 22 | | Herrera | 1 | | Tomás | 7 | | Confidential | 1 | | Human | 1 | | Source | 1 | | Victor | 3 | | Footsteps | 1 | | Underground | 1 | | Ahead | 1 |
| | persons | | 0 | "Detective" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Tomás" | | 4 | "Victor" | | 5 | "Footsteps" |
| | places | | | globalScore | 0.283 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | 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 | 967 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 81 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 27.63 | | std | 15.85 | | cv | 0.574 | | sampleLengths | | 0 | 39 | | 1 | 42 | | 2 | 24 | | 3 | 36 | | 4 | 38 | | 5 | 12 | | 6 | 9 | | 7 | 3 | | 8 | 33 | | 9 | 34 | | 10 | 27 | | 11 | 42 | | 12 | 48 | | 13 | 19 | | 14 | 9 | | 15 | 41 | | 16 | 29 | | 17 | 15 | | 18 | 38 | | 19 | 25 | | 20 | 31 | | 21 | 61 | | 22 | 21 | | 23 | 23 | | 24 | 16 | | 25 | 69 | | 26 | 28 | | 27 | 11 | | 28 | 30 | | 29 | 2 | | 30 | 54 | | 31 | 7 | | 32 | 18 | | 33 | 11 | | 34 | 22 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 77 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 157 | | matches | | 0 | "were emitting" | | 1 | "was approaching" |
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| 1.76% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 2 | | flaggedSentences | 4 | | totalSentences | 81 | | ratio | 0.049 | | matches | | 0 | "Quinn recognised the watchful demeanor of her Confidential Human Source, Victor; he raised a hand to his temple in a gesture indicating Quinn's target was nearby." | | 1 | "Suddenly, a new sound – a low hum that vibrated the floor under Quinn's boots." | | 2 | "On her left, a candlelit stall offered bottled remedies—potions, labelled in a language Quinn didn't recognise." | | 3 | "Anyone down here in this rabbit warren of a market was probably flying to a trance or worse; substances she'd encountered way too often." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 753 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.014608233731739707 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005312084993359893 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 81 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 81 | | mean | 11.94 | | std | 6.09 | | cv | 0.51 | | sampleLengths | | 0 | 15 | | 1 | 24 | | 2 | 10 | | 3 | 11 | | 4 | 2 | | 5 | 5 | | 6 | 9 | | 7 | 5 | | 8 | 14 | | 9 | 10 | | 10 | 13 | | 11 | 7 | | 12 | 16 | | 13 | 12 | | 14 | 26 | | 15 | 5 | | 16 | 7 | | 17 | 9 | | 18 | 3 | | 19 | 8 | | 20 | 8 | | 21 | 10 | | 22 | 7 | | 23 | 11 | | 24 | 8 | | 25 | 9 | | 26 | 6 | | 27 | 15 | | 28 | 2 | | 29 | 10 | | 30 | 27 | | 31 | 15 | | 32 | 9 | | 33 | 7 | | 34 | 10 | | 35 | 7 | | 36 | 15 | | 37 | 4 | | 38 | 13 | | 39 | 2 | | 40 | 9 | | 41 | 7 | | 42 | 24 | | 43 | 10 | | 44 | 11 | | 45 | 18 | | 46 | 15 | | 47 | 15 | | 48 | 23 | | 49 | 16 |
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| 66.26% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.41975308641975306 | | totalSentences | 81 | | uniqueOpeners | 34 | |
| 91.32% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 73 | | matches | | 0 | "Suddenly, a new sound –" | | 1 | "Further on, an elderly man" |
| | ratio | 0.027 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 73 | | matches | | 0 | "She'd been tailing the hooded" | | 1 | "Her breath formed puffs of" | | 2 | "It had to be him." | | 3 | "He'd used a similar hoodie" | | 4 | "His gravelly voice filled the" | | 5 | "she panted, slowing to a" | | 6 | "She peeked around the corner," | | 7 | "She stepped onto the groaning" | | 8 | "she called out" | | 9 | "Her voice boomed off the" | | 10 | "They were decorated with faded" | | 11 | "She moved past a table" | | 12 | "He studied Quinn with yellow" | | 13 | "She shuddered, looking away." | | 14 | "She took a sharp breath" | | 15 | "They faced one another, their" | | 16 | "Her watch's luminous dial indicated" | | 17 | "She checked behind the DJ" | | 18 | "she said, her eyes still" | | 19 | "She kept to the outer" |
| | ratio | 0.288 | |
| 28.49% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 73 | | matches | | 0 | "The rain battered Detective Quinn's" | | 1 | "She'd been tailing the hooded" | | 2 | "Her breath formed puffs of" | | 3 | "The figure's hood blew back," | | 4 | "It had to be him." | | 5 | "He'd used a similar hoodie" | | 6 | "Quinn picked up her pace." | | 7 | "Quinn closed the gap, confident" | | 8 | "Tomás weaved between parked cars" | | 9 | "Quinn followed, her boots splashing" | | 10 | "The alley was a tight" | | 11 | "A figure emerged from the" | | 12 | "Quinn recognised the watchful demeanor" | | 13 | "Victor rushed to meet her." | | 14 | "His gravelly voice filled the" | | 15 | "she panted, slowing to a" | | 16 | "Footsteps splashed from somewhere behind" | | 17 | "Quinn darted past Victor, towards" | | 18 | "She peeked around the corner," | | 19 | "An opening, an entrance to" |
| | ratio | 0.863 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 96.27% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 3 | | matches | | 0 | "The illumination source was spectral, as if the walls themselves were emitting a faint glow." | | 1 | "They faced one another, their wings folded, their eyes closed as if in prayer or meditation." | | 2 | "Quinn ignored the seller behind the stall, her eyes scanning the tunnels, willing them to reveal her prey." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn muttered, more to herself than anyone else" | | 1 | "she said, her eyes still scanning the crowd" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "she panted (pant)" | | 1 | "Quinn muttered (mutter)" |
| | dialogueSentences | 10 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0.667 | | effectiveRatio | 0.4 | |