| 33.33% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 1 | | adverbTags | | 0 | "He stepped back [back]" |
| | dialogueSentences | 12 | | tagDensity | 0.083 | | leniency | 0.167 | | rawRatio | 1 | | effectiveRatio | 0.167 | |
| 95.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1050 | | 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) | |
| 76.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1050 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "glint" | | 1 | "flickered" | | 2 | "framework" | | 3 | "shimmered" |
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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 | 53 | | matches | (empty) | |
| 88.95% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 53 | | filterMatches | (empty) | | hedgeMatches | | 0 | "managed to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 63 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1050 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 97.09% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 945 | | uniqueNames | 15 | | maxNameDensity | 1.06 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 10 | | Hanway | 1 | | Street | 3 | | Raven | 1 | | Nest | 1 | | Herrera | 4 | | Oxford | 1 | | Tottenham | 1 | | Court | 1 | | Road | 1 | | Camden | 1 | | High | 1 | | Morris | 2 | | Deptford | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Morris" |
| | places | | 0 | "Hanway" | | 1 | "Street" | | 2 | "Raven" | | 3 | "Oxford" | | 4 | "Tottenham" | | 5 | "Court" | | 6 | "Road" | | 7 | "Camden" | | 8 | "High" | | 9 | "Deptford" |
| | globalScore | 0.971 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1050 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 63 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 31.82 | | std | 25.53 | | cv | 0.802 | | sampleLengths | | 0 | 16 | | 1 | 5 | | 2 | 51 | | 3 | 99 | | 4 | 1 | | 5 | 49 | | 6 | 59 | | 7 | 20 | | 8 | 14 | | 9 | 63 | | 10 | 8 | | 11 | 48 | | 12 | 4 | | 13 | 82 | | 14 | 18 | | 15 | 24 | | 16 | 70 | | 17 | 57 | | 18 | 30 | | 19 | 37 | | 20 | 4 | | 21 | 12 | | 22 | 16 | | 23 | 24 | | 24 | 22 | | 25 | 11 | | 26 | 2 | | 27 | 46 | | 28 | 30 | | 29 | 73 | | 30 | 15 | | 31 | 34 | | 32 | 6 |
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| 98.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 53 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 158 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 63 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 949 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.03582718651211802 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.008429926238145416 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 63 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 63 | | mean | 16.67 | | std | 10.46 | | cv | 0.628 | | sampleLengths | | 0 | 16 | | 1 | 5 | | 2 | 9 | | 3 | 21 | | 4 | 21 | | 5 | 19 | | 6 | 36 | | 7 | 2 | | 8 | 24 | | 9 | 5 | | 10 | 13 | | 11 | 1 | | 12 | 16 | | 13 | 3 | | 14 | 5 | | 15 | 25 | | 16 | 17 | | 17 | 32 | | 18 | 10 | | 19 | 20 | | 20 | 7 | | 21 | 7 | | 22 | 24 | | 23 | 39 | | 24 | 8 | | 25 | 13 | | 26 | 15 | | 27 | 20 | | 28 | 4 | | 29 | 32 | | 30 | 3 | | 31 | 2 | | 32 | 27 | | 33 | 18 | | 34 | 4 | | 35 | 14 | | 36 | 24 | | 37 | 19 | | 38 | 14 | | 39 | 37 | | 40 | 1 | | 41 | 20 | | 42 | 36 | | 43 | 30 | | 44 | 19 | | 45 | 18 | | 46 | 4 | | 47 | 12 | | 48 | 6 | | 49 | 10 |
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| 88.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5396825396825397 | | totalSentences | 63 | | uniqueOpeners | 34 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 50 | | matches | | 0 | "Of course he didn't stop." | | 1 | "Just a puddle of something" |
| | ratio | 0.04 | |
| 92.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 50 | | matches | | 0 | "He cut left down Hanway" | | 1 | "She'd clocked him outside the" | | 2 | "She'd pulled his file after" | | 3 | "He'd been a ghost since." | | 4 | "Her voice cracked against brick" | | 5 | "He didn't stop." | | 6 | "He hit Oxford Street and" | | 7 | "She followed, breath ragged, radio" | | 8 | "She didn't wait for it" | | 9 | "She thought of Morris." | | 10 | "She'd stopped asking her superiors" | | 11 | "She drew her torch instead" | | 12 | "He turned, finally, and there" | | 13 | "He stepped back through the" | | 14 | "He turned and walked deeper" | | 15 | "She thought about Morris's badge," |
| | ratio | 0.32 | |
| 70.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 39 | | totalSentences | 50 | | matches | | 0 | "The figure ahead didn't so" | | 1 | "He cut left down Hanway" | | 2 | "She'd clocked him outside the" | | 3 | "The green neon sign had" | | 4 | "She'd pulled his file after" | | 5 | "He'd been a ghost since." | | 6 | "Her voice cracked against brick" | | 7 | "He didn't stop." | | 8 | "Nobody stopped when they had" | | 9 | "He hit Oxford Street and" | | 10 | "Quinn shouldered through a group" | | 11 | "She followed, breath ragged, radio" | | 12 | "The response fizzled into nothing" | | 13 | "She didn't wait for it" | | 14 | "Herrera cut through a service" | | 15 | "Quinn skidded to a stop" | | 16 | "The stairwell smelled of damp" | | 17 | "A single strip light flickered" | | 18 | "She thought of Morris." | | 19 | "She'd stopped asking her superiors" |
| | ratio | 0.78 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 50 | | matches | | 0 | "Now he was ninety feet" | | 1 | "By the time she reached" |
| | ratio | 0.04 | |
| 46.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 5 | | matches | | 0 | "She'd pulled his file after the NHS flagged him three years back, something about unauthorised treatments, patients who didn't exist on any hospital's books." | | 1 | "The stairs bottomed out at a rusted turnstile, half-collapsed, and beyond it a platform that shouldn't have existed anymore." | | 2 | "Voices murmured in overlapping tongues, undercut by something that made the hair along Quinn's arms rise, a low hum, almost musical, threading beneath the ordin…" | | 3 | "He turned and walked deeper into the market, unhurried now, as though he knew she wouldn't follow, as though the threshold behind him did the work of a locked d…" | | 4 | "Quinn stood at the turnstile with rain still running off her collar, torch beam trembling slightly in a hand that hadn't shaken like this in years." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |