| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.385 | | leniency | 0.769 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.35% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1369 | | 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) | |
| 41.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1369 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "unravel" | | 1 | "tapestry" | | 2 | "familiar" | | 3 | "flickered" | | 4 | "pulsed" | | 5 | "depths" | | 6 | "gloom" | | 7 | "tension" | | 8 | "scanned" | | 9 | "footsteps" | | 10 | "scanning" | | 11 | "could feel" | | 12 | "weight" | | 13 | "pounding" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 89 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 89 | | filterMatches | (empty) | | hedgeMatches | | |
| 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 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1372 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1250 | | uniqueNames | 8 | | maxNameDensity | 1.68 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 21 | | Raven | 1 | | Nest | 1 | | London | 2 | | Veil | 1 | | Market | 1 |
| | persons | | | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "London" | | 3 | "Market" |
| | globalScore | 0.66 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 1 | | matches | | 0 | "script that seemed to shift when she looked at them directly" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.729 | | wordCount | 1372 | | matches | | 0 | "not a weapon but a small, pale object" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 36.11 | | std | 19.34 | | cv | 0.536 | | sampleLengths | | 0 | 61 | | 1 | 51 | | 2 | 53 | | 3 | 56 | | 4 | 8 | | 5 | 58 | | 6 | 40 | | 7 | 45 | | 8 | 52 | | 9 | 3 | | 10 | 65 | | 11 | 2 | | 12 | 73 | | 13 | 55 | | 14 | 4 | | 15 | 60 | | 16 | 35 | | 17 | 56 | | 18 | 36 | | 19 | 47 | | 20 | 16 | | 21 | 17 | | 22 | 30 | | 23 | 19 | | 24 | 34 | | 25 | 40 | | 26 | 38 | | 27 | 25 | | 28 | 42 | | 29 | 10 | | 30 | 55 | | 31 | 42 | | 32 | 34 | | 33 | 14 | | 34 | 42 | | 35 | 21 | | 36 | 5 | | 37 | 28 |
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| 97.38% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 89 | | matches | | 0 | "was plastered" | | 1 | "was stopped" |
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| 73.02% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 210 | | matches | | 0 | "was running" | | 1 | "wasn't falling" | | 2 | "was shaking" | | 3 | "was already turning" |
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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 | 1252 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.015175718849840255 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.004792332268370607 | |
| 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 | 14.29 | | std | 7.24 | | cv | 0.506 | | sampleLengths | | 0 | 18 | | 1 | 23 | | 2 | 20 | | 3 | 14 | | 4 | 22 | | 5 | 15 | | 6 | 9 | | 7 | 20 | | 8 | 24 | | 9 | 11 | | 10 | 14 | | 11 | 10 | | 12 | 21 | | 13 | 4 | | 14 | 4 | | 15 | 11 | | 16 | 24 | | 17 | 23 | | 18 | 15 | | 19 | 14 | | 20 | 11 | | 21 | 5 | | 22 | 19 | | 23 | 21 | | 24 | 9 | | 25 | 15 | | 26 | 3 | | 27 | 3 | | 28 | 22 | | 29 | 3 | | 30 | 12 | | 31 | 16 | | 32 | 11 | | 33 | 26 | | 34 | 2 | | 35 | 12 | | 36 | 25 | | 37 | 19 | | 38 | 17 | | 39 | 8 | | 40 | 12 | | 41 | 17 | | 42 | 18 | | 43 | 4 | | 44 | 10 | | 45 | 18 | | 46 | 14 | | 47 | 18 | | 48 | 16 | | 49 | 19 |
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| 34.38% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.28125 | | totalSentences | 96 | | uniqueOpeners | 27 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 85 | | matches | | 0 | "Her target was twenty yards" | | 1 | "She'd been watching the bar" | | 2 | "Her salt-and-pepper hair was plastered" | | 3 | "He cut left down an" | | 4 | "He pulled something from his" | | 5 | "He pressed it against a" | | 6 | "She stopped at the threshold." | | 7 | "She could call for backup," | | 8 | "She stepped through." | | 9 | "She'd always dismissed it as" | | 10 | "She scanned the crowd for" | | 11 | "She slipped between two tents" | | 12 | "He was stopped at a" | | 13 | "he said, his voice cracked" | | 14 | "She kept her hand on" | | 15 | "She could feel the weight" | | 16 | "he said, and then he" | | 17 | "She burst into a larger" | | 18 | "She looked back at the" | | 19 | "She had a choice." |
| | ratio | 0.235 | |
| 24.71% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 85 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn kept her" | | 2 | "Her target was twenty yards" | | 3 | "The suspect had bolted when" | | 4 | "She'd been watching the bar" | | 5 | "The man in the dark" | | 6 | "Quinn's lungs burned with the" | | 7 | "Her salt-and-pepper hair was plastered" | | 8 | "The man glanced back, his" | | 9 | "He cut left down an" | | 10 | "The alley was narrow, choked" | | 11 | "The man's foot slipped on" | | 12 | "Quinn closed the distance." | | 13 | "He pulled something from his" | | 14 | "He pressed it against a" | | 15 | "A section of the wall" | | 16 | "The man disappeared into the" | | 17 | "She stopped at the threshold." | | 18 | "The air coming from the" | | 19 | "The stone steps were worn" |
| | ratio | 0.871 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 43.96% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 65 | | technicalSentenceCount | 9 | | matches | | 0 | "She'd been watching the bar for two weeks, logging faces and patterns, waiting for the thread that would unravel the whole tapestry." | | 1 | "He pulled something from his pocket, not a weapon but a small, pale object that caught the faint light from the street behind them." | | 2 | "The beam cut through the gloom, revealing walls covered in symbols she didn't recognize-coils of script that seemed to shift when she looked at them directly." | | 3 | "The ceiling arched high overhead, lost in shadows, while stalls and makeshift shops lined a central thoroughfare that stretched as far as she could see." | | 4 | "An underground bazaar that moved with the moon, selling things that couldn't be bought with regular money." | | 5 | "She'd always dismissed it as folklore, the kind of story that drunks told to make themselves sound important." | | 6 | "She burst into a larger chamber, where the market's central thoroughfare opened up around a fountain that flowed with something dark and viscous." | | 7 | "She looked back at the market, at the faces that had tracked her since she'd arrived, at the flickering blue-green flames and the impossible transactions taking…" | | 8 | "The man was already turning, his silhouette dissolving into the dark." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, his voice cracked" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0 | | effectiveRatio | 0 | |