| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 1 | | adverbTags | | 0 | "hand gestured vaguely [vaguely]" |
| | dialogueSentences | 10 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0.5 | | effectiveRatio | 0.2 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 964 | | 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) | |
| 42.95% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 964 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "echoed" | | 1 | "echoing" | | 2 | "traced" | | 3 | "raced" | | 4 | "footsteps" | | 5 | "chaotic" | | 6 | "constructed" | | 7 | "pulsed" | | 8 | "weight" | | 9 | "standard" | | 10 | "profound" |
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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 | 104 | | matches | (empty) | |
| 87.91% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 104 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 21 | | totalWords | 962 | | ratio | 0.022 | | matches | | 0 | "backup, secure the perimeter" | | 1 | "go" | | 2 | "The Veil Market. Moves every full moon. Sells things that shouldn’t exist." | | 3 | "were they all people?" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 93.44% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 884 | | uniqueNames | 12 | | maxNameDensity | 1.13 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 10 | | Morris | 4 | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Camden | 1 | | Tube | 2 | | Edwardian | 1 | | Veil | 1 | | Market | 1 | | Thames | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Raven" |
| | places | | 0 | "Soho" | | 1 | "Market" | | 2 | "Thames" |
| | globalScore | 0.934 | | windowScore | 1 | |
| 45.83% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 3 | | matches | | 0 | "weapons that seemed to be made of shadow and bone" | | 1 | "watch that seemed to be made of a small, staring eye" | | 2 | "felt like a child’s toy" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 962 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 24.67 | | std | 18.26 | | cv | 0.74 | | sampleLengths | | 0 | 59 | | 1 | 36 | | 2 | 45 | | 3 | 3 | | 4 | 30 | | 5 | 38 | | 6 | 13 | | 7 | 35 | | 8 | 28 | | 9 | 13 | | 10 | 16 | | 11 | 42 | | 12 | 38 | | 13 | 37 | | 14 | 9 | | 15 | 23 | | 16 | 13 | | 17 | 46 | | 18 | 5 | | 19 | 2 | | 20 | 40 | | 21 | 6 | | 22 | 13 | | 23 | 10 | | 24 | 81 | | 25 | 19 | | 26 | 9 | | 27 | 11 | | 28 | 28 | | 29 | 17 | | 30 | 10 | | 31 | 12 | | 32 | 8 | | 33 | 69 | | 34 | 9 | | 35 | 34 | | 36 | 22 | | 37 | 21 | | 38 | 12 |
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| 91.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 104 | | matches | | 0 | "being clenched" | | 1 | "were ruined" | | 2 | "been transformed" | | 3 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 151 | | matches | | |
| 64.94% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 110 | | ratio | 0.027 | | matches | | 0 | "She kept her eyes on the fleeing figure—a dark coat, hood up, moving with a loping, unnatural grace." | | 1 | "It slid open with a hydraulic hiss, releasing a wave of sound and scent—murmuring voices, the clink of glass, strange, pungent spices, and that ozone smell, stronger now." | | 2 | "The people—*were they all people?*—moved with odd gaits." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 889 | | adjectiveStacks | 1 | | stackExamples | | 0 | "heavy, moth-eaten coat." |
| | adverbCount | 21 | | adverbRatio | 0.023622047244094488 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003374578177727784 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 8.75 | | std | 6.16 | | cv | 0.704 | | sampleLengths | | 0 | 13 | | 1 | 11 | | 2 | 6 | | 3 | 15 | | 4 | 8 | | 5 | 6 | | 6 | 12 | | 7 | 18 | | 8 | 3 | | 9 | 3 | | 10 | 21 | | 11 | 7 | | 12 | 6 | | 13 | 1 | | 14 | 10 | | 15 | 3 | | 16 | 4 | | 17 | 3 | | 18 | 6 | | 19 | 2 | | 20 | 5 | | 21 | 10 | | 22 | 10 | | 23 | 17 | | 24 | 7 | | 25 | 4 | | 26 | 5 | | 27 | 7 | | 28 | 1 | | 29 | 16 | | 30 | 7 | | 31 | 12 | | 32 | 5 | | 33 | 12 | | 34 | 10 | | 35 | 1 | | 36 | 13 | | 37 | 7 | | 38 | 9 | | 39 | 13 | | 40 | 17 | | 41 | 12 | | 42 | 18 | | 43 | 7 | | 44 | 7 | | 45 | 6 | | 46 | 9 | | 47 | 28 | | 48 | 4 | | 49 | 5 |
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| 70.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.4636363636363636 | | totalSentences | 110 | | uniqueOpeners | 51 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 94 | | matches | | 0 | "Then he was moving again," | | 1 | "Somewhere in this labyrinth of" | | 2 | "Then she started down the" |
| | ratio | 0.032 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 94 | | matches | | 0 | "Her breath came in sharp," | | 1 | "She kept her eyes on" | | 2 | "He burst onto a brighter" | | 3 | "He didn’t even flinch." | | 4 | "He moved like he knew" | | 5 | "Her shoes were ruined." | | 6 | "He vanished around a corner." | | 7 | "She heard a scrape of" | | 8 | "Her training screamed *backup, secure" | | 9 | "She took the steps, each" | | 10 | "He held up a small," | | 11 | "He pressed it against the" | | 12 | "It slid open with a" | | 13 | "He’d called her, his voice" | | 14 | "They found his body in" | | 15 | "She sprinted across the ticket" | | 16 | "She threw her arm out," | | 17 | "She shoved, muscles straining against" | | 18 | "It gave an inch." | | 19 | "She stood on a metal" |
| | ratio | 0.277 | |
| 66.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 94 | | matches | | 0 | "The suspect’s shoulder clipped a" | | 1 | "The sound echoed off the" | | 2 | "Detective Harlow Quinn didn’t break" | | 3 | "Her breath came in sharp," | | 4 | "The one who knew about" | | 5 | "Rain lashed down, turning the" | | 6 | "She kept her eyes on" | | 7 | "He burst onto a brighter" | | 8 | "Quinn saw a pale, sharp" | | 9 | "He didn’t even flinch." | | 10 | "Amateur or professional?" | | 11 | "Professionals usually complied, knew the" | | 12 | "This one was something else." | | 13 | "He moved like he knew" | | 14 | "The chase dipped into a" | | 15 | "The rain eased to a" | | 16 | "Quinn’s sharp jaw ached from" | | 17 | "Her shoes were ruined." | | 18 | "He vanished around a corner." | | 19 | "Quinn rounded it, hand on" |
| | ratio | 0.787 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 94 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 1 | | matches | | 0 | "She stood on a metal gantry overlooking a scene that made her brain stutter." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |