| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.435 | | leniency | 0.87 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.40% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1316 | | totalAiIsmAdverbs | 2 | | 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) | |
| 27.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1316 | | totalAiIsms | 19 | | found | | | highlights | | 0 | "flicked" | | 1 | "standard" | | 2 | "gloom" | | 3 | "echoes" | | 4 | "footsteps" | | 5 | "sentinel" | | 6 | "etched" | | 7 | "silk" | | 8 | "velvet" | | 9 | "gleaming" | | 10 | "glinting" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 87 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 87 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 100 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1316 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1201 | | uniqueNames | 15 | | maxNameDensity | 1.42 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Herrera | 10 | | Inverness | 1 | | Street | 1 | | Metropolitan | 1 | | Police | 1 | | Camden | 1 | | Victorian | 2 | | London | 2 | | Underground | 2 | | Morris | 2 | | Holborn | 1 | | Quinn | 17 | | Tomás | 4 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Herrera" | | 1 | "Police" | | 2 | "Morris" | | 3 | "Quinn" | | 4 | "Tomás" | | 5 | "Saint" | | 6 | "Christopher" |
| | places | | 0 | "Inverness" | | 1 | "Street" | | 2 | "Metropolitan" | | 3 | "London" | | 4 | "Holborn" |
| | globalScore | 0.792 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.76 | | wordCount | 1316 | | matches | | 0 | "not out of fear, but with slow, predatory curiosity" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 100 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 26.32 | | std | 17.76 | | cv | 0.675 | | sampleLengths | | 0 | 36 | | 1 | 48 | | 2 | 43 | | 3 | 3 | | 4 | 60 | | 5 | 33 | | 6 | 36 | | 7 | 28 | | 8 | 55 | | 9 | 30 | | 10 | 66 | | 11 | 19 | | 12 | 37 | | 13 | 22 | | 14 | 46 | | 15 | 24 | | 16 | 4 | | 17 | 40 | | 18 | 6 | | 19 | 15 | | 20 | 14 | | 21 | 15 | | 22 | 9 | | 23 | 26 | | 24 | 15 | | 25 | 37 | | 26 | 15 | | 27 | 32 | | 28 | 50 | | 29 | 51 | | 30 | 11 | | 31 | 10 | | 32 | 36 | | 33 | 12 | | 34 | 69 | | 35 | 9 | | 36 | 54 | | 37 | 28 | | 38 | 23 | | 39 | 9 | | 40 | 32 | | 41 | 3 | | 42 | 5 | | 43 | 6 | | 44 | 13 | | 45 | 27 | | 46 | 4 | | 47 | 2 | | 48 | 27 | | 49 | 21 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 87 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 185 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 100 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1209 | | adjectiveStacks | 1 | | stackExamples | | 0 | "revealing milky, pupilless eyes" |
| | adverbCount | 19 | | adverbRatio | 0.015715467328370553 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.007444168734491315 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 100 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 100 | | mean | 13.16 | | std | 7.03 | | cv | 0.534 | | sampleLengths | | 0 | 12 | | 1 | 24 | | 2 | 7 | | 3 | 23 | | 4 | 18 | | 5 | 11 | | 6 | 32 | | 7 | 3 | | 8 | 12 | | 9 | 6 | | 10 | 22 | | 11 | 10 | | 12 | 10 | | 13 | 25 | | 14 | 8 | | 15 | 13 | | 16 | 9 | | 17 | 14 | | 18 | 7 | | 19 | 21 | | 20 | 20 | | 21 | 15 | | 22 | 20 | | 23 | 18 | | 24 | 12 | | 25 | 22 | | 26 | 2 | | 27 | 5 | | 28 | 12 | | 29 | 25 | | 30 | 19 | | 31 | 28 | | 32 | 9 | | 33 | 6 | | 34 | 16 | | 35 | 15 | | 36 | 12 | | 37 | 19 | | 38 | 11 | | 39 | 13 | | 40 | 4 | | 41 | 13 | | 42 | 27 | | 43 | 4 | | 44 | 2 | | 45 | 15 | | 46 | 14 | | 47 | 15 | | 48 | 4 | | 49 | 5 |
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| 66.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.43 | | totalSentences | 100 | | uniqueOpeners | 43 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 82 | | matches | | 0 | "He carried a heavy leather" | | 1 | "He took the sharp corner" | | 2 | "Her voice cut through the" | | 3 | "His warm brown eyes widened," | | 4 | "He hurled an empty metal" | | 5 | "She drew her baton, flicked" | | 6 | "It smelled nothing like the" | | 7 | "She flicked her torch on," | | 8 | "Her boots found the centre" | | 9 | "His skin possessed an unnatural," | | 10 | "He hauled out a small," | | 11 | "He turned his heavy head" | | 12 | "She lunged forward, planted her" | | 13 | "She reached the threshold of" | | 14 | "He was handing a bundle" | | 15 | "She advanced through the crowd." | | 16 | "His fingers clenched around the" | | 17 | "He turned slowly, his olive" |
| | ratio | 0.22 | |
| 14.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 82 | | matches | | 0 | "Quinn vaulted the iron railing," | | 1 | "Water sprayed up from a" | | 2 | "Tomás Herrera ran like a" | | 3 | "He carried a heavy leather" | | 4 | "He took the sharp corner" | | 5 | "Quinn pushed through the burning" | | 6 | "Her voice cut through the" | | 7 | "Herrera glanced back over his" | | 8 | "The dim glow of a" | | 9 | "His warm brown eyes widened," | | 10 | "He hurled an empty metal" | | 11 | "Quinn sidestepped the tumbling aluminium" | | 12 | "The gap between them widened" | | 13 | "Herrera darted toward the mouth" | | 14 | "A faded municipal warning sign" | | 15 | "Herrera shoved the loose metal" | | 16 | "Quinn reached the gap three" | | 17 | "She drew her baton, flicked" | | 18 | "The alley ended at a" | | 19 | "The heavy padlock hung split" |
| | ratio | 0.89 | |
| 60.98% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 82 | | matches | | 0 | "Before he could recover, she" |
| | ratio | 0.012 | |
| 81.28% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 5 | | matches | | 0 | "Quinn vaulted the iron railing, her boots slamming hard onto wet asphalt." | | 1 | "He took the sharp corner into Inverness Street without breaking stride, his trainers squealing against the slick pavement." | | 2 | "Eighteen years in the Metropolitan Police taught an officer how to pace a pursuit, but Herrera possessed the desperate stamina of a man who knew precisely what …" | | 3 | "Herrera stood before the sentinel, chest heaving, his fingers digging into his collar." | | 4 | "He turned his heavy head toward her, revealing milky, pupilless eyes that reflected the torchlight like polished slate." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn called out, her voice hard as flint" | | 1 | "Tomás backed away, his eyes darting toward the shadowy fringes of the platform" |
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| 63.04% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "the sentinel roared (roar)" | | 1 | "Quinn called out (call out)" |
| | dialogueSentences | 23 | | tagDensity | 0.261 | | leniency | 0.522 | | rawRatio | 0.333 | | effectiveRatio | 0.174 | |