| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 67 | | tagDensity | 0.119 | | leniency | 0.239 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1782 | | 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) | |
| 77.55% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1782 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "measured" | | 1 | "trembled" | | 2 | "scanned" | | 3 | "radiant" | | 4 | "silence" | | 5 | "pulse" | | 6 | "traced" | | 7 | "eyebrow" |
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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 | 173 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 173 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 231 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1781 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 40.78% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 1465 | | uniqueNames | 8 | | maxNameDensity | 2.18 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 32 | | Soho | 2 | | Raven | 1 | | Nest | 1 | | Tube | 1 | | Radiant | 1 | | Cream | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" |
| | places | | | globalScore | 0.408 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 117 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed narrower than before" |
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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 | 1781 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 231 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 125 | | mean | 14.25 | | std | 14.31 | | cv | 1.004 | | sampleLengths | | 0 | 38 | | 1 | 11 | | 2 | 2 | | 3 | 35 | | 4 | 24 | | 5 | 27 | | 6 | 18 | | 7 | 44 | | 8 | 8 | | 9 | 9 | | 10 | 5 | | 11 | 27 | | 12 | 8 | | 13 | 29 | | 14 | 6 | | 15 | 4 | | 16 | 7 | | 17 | 2 | | 18 | 4 | | 19 | 35 | | 20 | 6 | | 21 | 16 | | 22 | 9 | | 23 | 9 | | 24 | 37 | | 25 | 4 | | 26 | 2 | | 27 | 56 | | 28 | 10 | | 29 | 24 | | 30 | 10 | | 31 | 79 | | 32 | 3 | | 33 | 14 | | 34 | 21 | | 35 | 1 | | 36 | 19 | | 37 | 13 | | 38 | 6 | | 39 | 26 | | 40 | 4 | | 41 | 3 | | 42 | 6 | | 43 | 36 | | 44 | 29 | | 45 | 6 | | 46 | 60 | | 47 | 10 | | 48 | 31 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 173 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 250 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 231 | | ratio | 0.009 | | matches | | 0 | "One showed a smiling woman holding a jar of something called Radiant Cream; the slogan had faded to a grey smear." | | 1 | "Behind her, the gate swung on its hinges, leaving the passage open to the street above—and the red glow on the tracks brightened against the rain-dark city below." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1470 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.017687074829931974 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 231 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 231 | | mean | 7.71 | | std | 4.95 | | cv | 0.642 | | sampleLengths | | 0 | 9 | | 1 | 29 | | 2 | 11 | | 3 | 2 | | 4 | 3 | | 5 | 15 | | 6 | 17 | | 7 | 16 | | 8 | 5 | | 9 | 3 | | 10 | 17 | | 11 | 3 | | 12 | 7 | | 13 | 10 | | 14 | 8 | | 15 | 11 | | 16 | 11 | | 17 | 22 | | 18 | 8 | | 19 | 3 | | 20 | 6 | | 21 | 5 | | 22 | 4 | | 23 | 8 | | 24 | 8 | | 25 | 7 | | 26 | 8 | | 27 | 7 | | 28 | 11 | | 29 | 11 | | 30 | 6 | | 31 | 4 | | 32 | 3 | | 33 | 4 | | 34 | 2 | | 35 | 4 | | 36 | 6 | | 37 | 15 | | 38 | 7 | | 39 | 7 | | 40 | 6 | | 41 | 16 | | 42 | 2 | | 43 | 3 | | 44 | 4 | | 45 | 9 | | 46 | 10 | | 47 | 5 | | 48 | 19 | | 49 | 3 |
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| 43.51% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.2857142857142857 | | totalSentences | 231 | | uniqueOpeners | 66 | |
| 42.46% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 157 | | matches | | 0 | "Then he shoved through a" | | 1 | "Somewhere beyond them, a train" |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 157 | | matches | | 0 | "He looked back." | | 1 | "His hood slipped, showing a" | | 2 | "She didn’t slow." | | 3 | "He grabbed the door and" | | 4 | "She crossed the room and" | | 5 | "It gave under her hand," | | 6 | "She entered the passage." | | 7 | "She tried again." | | 8 | "She kept the radio in" | | 9 | "She wedged her fingers between" | | 10 | "She raised her torch." | | 11 | "She looked for the suspect." | | 12 | "He had a bone token" | | 13 | "Its owner shouted after him," | | 14 | "He knocked over a rack" | | 15 | "They struck the platform and" | | 16 | "She keyed her radio again." | | 17 | "She could retreat, bring a" | | 18 | "Its face showed 11:43." | | 19 | "She had time to choose." |
| | ratio | 0.21 | |
| 20.51% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 138 | | totalSentences | 157 | | matches | | 0 | "Rain silvered the pavement and" | | 1 | "Detective Harlow Quinn ran with" | | 2 | "He looked back." | | 3 | "His hood slipped, showing a" | | 4 | "Quinn hit the kerb as" | | 5 | "A cyclist swore at her." | | 6 | "She didn’t slow." | | 7 | "The suspect reappeared beneath the" | | 8 | "The Raven’s Nest." | | 9 | "He grabbed the door and" | | 10 | "Quinn drew her warrant card" | | 11 | "The green light trembled over" | | 12 | "Maps covered the walls, their" | | 13 | "A man at the counter" | | 14 | "Quinn scanned the room." | | 15 | "A chair scraped near the" | | 16 | "The bartender’s eyes shifted towards" | | 17 | "Quinn moved before he could" | | 18 | "She crossed the room and" | | 19 | "It gave under her hand," |
| | ratio | 0.879 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 157 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 2 | | matches | | 0 | "Detective Harlow Quinn ran with one hand on her coat, the other free, her boots striking the street in a measured rhythm that had nothing to do with calm." | | 1 | "Black-and-white photographs hung between them: faces from another century, all staring past the room as if they knew what stood behind it." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 2 | | fancyTags | | 0 | "the bartender warned (warn)" | | 1 | "Quinn shouted (shout)" |
| | dialogueSentences | 67 | | tagDensity | 0.119 | | leniency | 0.239 | | rawRatio | 0.25 | | effectiveRatio | 0.06 | |