| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1398 | | 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) | |
| 17.74% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1398 | | totalAiIsms | 23 | | found | | | highlights | | 0 | "flickered" | | 1 | "footsteps" | | 2 | "echoed" | | 3 | "gloom" | | 4 | "wavered" | | 5 | "pulse" | | 6 | "glinting" | | 7 | "flicked" | | 8 | "mosaic" | | 9 | "charged" | | 10 | "shattered" | | 11 | "fluttered" | | 12 | "quickened" | | 13 | "chill" | | 14 | "reverberated" | | 15 | "thundered" |
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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 | 182 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 182 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 203 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1387 | | ratio | 0 | | matches | (empty) | |
| 89.29% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 1 | | matches | | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 16 | | wordCount | 1280 | | uniqueNames | 7 | | maxNameDensity | 0.47 | | worstName | "Quinn" | | maxWindowNameDensity | 1 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 6 | | Raven | 1 | | Nest | 1 | | Units | 1 | | Tube | 2 | | Morris | 1 | | Rainwater | 4 |
| | persons | | 0 | "Quinn" | | 1 | "Nest" | | 2 | "Morris" | | 3 | "Rainwater" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 108 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a living thing, calling her d" | | 1 | "seemed warmed by her touch, eyes hollow but leering" |
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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 | 1387 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 203 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 60 | | mean | 23.12 | | std | 14.68 | | cv | 0.635 | | sampleLengths | | 0 | 20 | | 1 | 53 | | 2 | 7 | | 3 | 18 | | 4 | 5 | | 5 | 28 | | 6 | 34 | | 7 | 32 | | 8 | 48 | | 9 | 39 | | 10 | 55 | | 11 | 33 | | 12 | 43 | | 13 | 15 | | 14 | 1 | | 15 | 25 | | 16 | 17 | | 17 | 21 | | 18 | 4 | | 19 | 19 | | 20 | 1 | | 21 | 41 | | 22 | 30 | | 23 | 5 | | 24 | 27 | | 25 | 48 | | 26 | 37 | | 27 | 28 | | 28 | 6 | | 29 | 30 | | 30 | 38 | | 31 | 28 | | 32 | 15 | | 33 | 21 | | 34 | 12 | | 35 | 11 | | 36 | 40 | | 37 | 35 | | 38 | 44 | | 39 | 33 | | 40 | 8 | | 41 | 13 | | 42 | 2 | | 43 | 10 | | 44 | 17 | | 45 | 13 | | 46 | 35 | | 47 | 12 | | 48 | 8 | | 49 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 182 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 266 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 203 | | ratio | 0.015 | | matches | | 0 | "His head snapped back; he hit the ground with a dull thud." | | 1 | "The floor sprawled with mosaic tiles—some intact, most cracked." | | 2 | "She pictured DS Morris—her partner—lost three years ago to something not human." |
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| 99.04% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 73 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 3 | | adverbRatio | 0.0410958904109589 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0136986301369863 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 203 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 203 | | mean | 6.83 | | std | 3.86 | | cv | 0.565 | | sampleLengths | | 0 | 10 | | 1 | 10 | | 2 | 10 | | 3 | 12 | | 4 | 6 | | 5 | 6 | | 6 | 7 | | 7 | 2 | | 8 | 2 | | 9 | 8 | | 10 | 7 | | 11 | 7 | | 12 | 5 | | 13 | 6 | | 14 | 1 | | 15 | 4 | | 16 | 4 | | 17 | 8 | | 18 | 12 | | 19 | 4 | | 20 | 9 | | 21 | 7 | | 22 | 4 | | 23 | 7 | | 24 | 7 | | 25 | 4 | | 26 | 5 | | 27 | 12 | | 28 | 3 | | 29 | 8 | | 30 | 17 | | 31 | 15 | | 32 | 3 | | 33 | 3 | | 34 | 3 | | 35 | 3 | | 36 | 4 | | 37 | 2 | | 38 | 8 | | 39 | 8 | | 40 | 5 | | 41 | 6 | | 42 | 10 | | 43 | 7 | | 44 | 5 | | 45 | 12 | | 46 | 8 | | 47 | 7 | | 48 | 16 | | 49 | 7 |
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| 55.99% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.3448275862068966 | | totalSentences | 203 | | uniqueOpeners | 70 | |
| 59.17% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 169 | | matches | | 0 | "Only a crackling radio pinned" | | 1 | "Then hurtled after him." | | 2 | "Then the next." |
| | ratio | 0.018 | |
| 25.92% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 82 | | totalSentences | 169 | | matches | | 0 | "She’d tailed him from the" | | 1 | "Her boots slapped the wet" | | 2 | "His footsteps echoed twice, then" | | 3 | "She risked a glance over" | | 4 | "She ended the transmission." | | 5 | "Her leather watch tapped against" | | 6 | "She kicked it open." | | 7 | "She drew her torch." | | 8 | "Her boots echoed." | | 9 | "He jabbed twice." | | 10 | "He punched the hatch aside" | | 11 | "She hit the metal plate" | | 12 | "She ignored it and tumbled" | | 13 | "Her torch wavered, then steadied." | | 14 | "She stood on an abandoned" | | 15 | "Her pulse drummed in her" | | 16 | "Their robes were coal-black, fringe" | | 17 | "She raised her torch higher." | | 18 | "His hands were hidden in" | | 19 | "You didn’t need to see" |
| | ratio | 0.485 | |
| 28.05% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 146 | | totalSentences | 169 | | matches | | 0 | "The suspect’s shadow flickered ahead" | | 1 | "She’d tailed him from the" | | 2 | "Her boots slapped the wet" | | 3 | "His footsteps echoed twice, then" | | 4 | "She risked a glance over" | | 5 | "Units five minutes" | | 6 | "She ended the transmission." | | 7 | "A cold wind whipped at" | | 8 | "Her leather watch tapped against" | | 9 | "A slate-grey door stood half-ajar" | | 10 | "The suspect must have slipped" | | 11 | "She kicked it open." | | 12 | "Water dripped, drip-drop, onto the" | | 13 | "She drew her torch." | | 14 | "The beam sliced through gloom." | | 15 | "Each step she took sent" | | 16 | "Her boots echoed." | | 17 | "The air smelled of damp" | | 18 | "Halfway down, she saw him:" | | 19 | "A panicked gleam in his" |
| | ratio | 0.864 | |
| 29.59% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 169 | | matches | | 0 | "Now the alley yawned before" |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 2 | | matches | | 0 | "She sprinted through the archway, smashing past a second trader who hissed curses in half-Latin, half-Camden slang." | | 1 | "She gazed at the stairwell leading deeper into darkness, beyond any map, beneath an abandoned Tube station that wasn’t on any chart." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |