| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.409 | | leniency | 0.818 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.52% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1055 | | totalAiIsmAdverbs | 2 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
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| | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 81.04% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1055 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "pristine" | | 1 | "weight" | | 2 | "scanning" | | 3 | "etched" |
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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 | 83 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 83 | | filterMatches | | | hedgeMatches | (empty) | |
| 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 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1063 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 871 | | uniqueNames | 5 | | maxNameDensity | 0.69 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 6 | | Patel | 4 | | One | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Patel" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 62.28% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 2 | | matches | | 0 | "quite reach, she found what she was looking for" | | 1 | "rside bolt was visibly corroded into its h" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.941 | | wordCount | 1063 | | matches | | 0 | "not the dead, stale breath of a sealed cavity, but a slow" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 96 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 31.26 | | std | 24.38 | | cv | 0.78 | | sampleLengths | | 0 | 64 | | 1 | 26 | | 2 | 66 | | 3 | 40 | | 4 | 12 | | 5 | 3 | | 6 | 1 | | 7 | 18 | | 8 | 45 | | 9 | 38 | | 10 | 37 | | 11 | 9 | | 12 | 70 | | 13 | 37 | | 14 | 9 | | 15 | 32 | | 16 | 86 | | 17 | 18 | | 18 | 6 | | 19 | 75 | | 20 | 15 | | 21 | 9 | | 22 | 8 | | 23 | 16 | | 24 | 12 | | 25 | 75 | | 26 | 52 | | 27 | 7 | | 28 | 34 | | 29 | 47 | | 30 | 5 | | 31 | 57 | | 32 | 27 | | 33 | 7 |
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| 75.67% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 83 | | matches | | 0 | "been bricked" | | 1 | "been brushed" | | 2 | "been drawn" | | 3 | "was rusted" | | 4 | "been turned" | | 5 | "were bricked" | | 6 | "been repointed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 132 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 96 | | ratio | 0.073 | | matches | | 0 | "The Tube station smelled of old iron and something else — something that didn't belong to any maintenance crew or urban fox." | | 1 | "The tiles were original — cream with a green border, cracked in places, the ghost of a station name still legible under decades of grime." | | 2 | "The detritus of sixty years — the bird nests and damp cardboard and the particular archaeology of urban abandonment — had been brushed to the edges." | | 3 | "When the beam swept the floor, they both saw it — a faint circular pattern in the dust, roughly two metres in diameter." | | 4 | "The surrounding frame showed tool marks from the outside, fresh scratches in the rust patina — someone forcing it open — but the underside bolt was visibly corroded into its housing." | | 5 | "Behind the brick, air circulated — not the dead, stale breath of a sealed cavity, but a slow and deliberate current, as though something on the far side exhaled." | | 6 | "Her torch caught something on the ground at the base of the arch — so small she'd nearly stepped over it twice." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 866 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.03348729792147806 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.015011547344110854 | |
| 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 | 11.07 | | std | 8.03 | | cv | 0.725 | | sampleLengths | | 0 | 22 | | 1 | 28 | | 2 | 14 | | 3 | 9 | | 4 | 13 | | 5 | 4 | | 6 | 21 | | 7 | 15 | | 8 | 30 | | 9 | 8 | | 10 | 25 | | 11 | 2 | | 12 | 5 | | 13 | 12 | | 14 | 3 | | 15 | 1 | | 16 | 15 | | 17 | 3 | | 18 | 10 | | 19 | 20 | | 20 | 11 | | 21 | 4 | | 22 | 9 | | 23 | 29 | | 24 | 5 | | 25 | 20 | | 26 | 6 | | 27 | 6 | | 28 | 6 | | 29 | 3 | | 30 | 13 | | 31 | 1 | | 32 | 21 | | 33 | 4 | | 34 | 12 | | 35 | 2 | | 36 | 17 | | 37 | 18 | | 38 | 11 | | 39 | 8 | | 40 | 9 | | 41 | 6 | | 42 | 26 | | 43 | 2 | | 44 | 9 | | 45 | 17 | | 46 | 5 | | 47 | 26 | | 48 | 7 | | 49 | 2 |
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| 81.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.53125 | | totalSentences | 96 | | uniqueOpeners | 51 | |
| 49.02% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 68 | | matches | | 0 | "Ceremonially, something in the back" |
| | ratio | 0.015 | |
| 78.82% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 68 | | matches | | 0 | "He was young, thorough, and" | | 1 | "She'd never heard of it." | | 2 | "She turned to look at" | | 3 | "He glanced at his tablet," | | 4 | "It was dusty, yes, but" | | 5 | "She pulled on a fresh" | | 6 | "His expression was neutral." | | 7 | "She'd seen that once before," | | 8 | "She tilted his chin gently" | | 9 | "she called toward the far" | | 10 | "She turned a slow circle," | | 11 | "She kept her voice even" | | 12 | "He pulled up the photograph" | | 13 | "It hadn't been turned in" | | 14 | "She walked to the nearest" | | 15 | "She moved to the second" | | 16 | "She pressed her palm flat." | | 17 | "She stepped back and studied" | | 18 | "They were consistent with the" | | 19 | "She photographed it without comment." |
| | ratio | 0.353 | |
| 70.29% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 53 | | totalSentences | 68 | | matches | | 0 | "The Tube station smelled of" | | 1 | "Detective Harlow Quinn crouched at" | | 2 | "The light was harsh and" | | 3 | "Camden wasn't supposed to have" | | 4 | "The maps said this stretch" | | 5 | "Someone had clearly disagreed." | | 6 | "DS Patel appeared at her" | | 7 | "He was young, thorough, and" | | 8 | "Quinn moved along the platform" | | 9 | "The tiles were original —" | | 10 | "She'd never heard of it." | | 11 | "She turned to look at" | | 12 | "He glanced at his tablet," | | 13 | "The victim lay on his" | | 14 | "A man in a quality" | | 15 | "Patel looked at the floor." | | 16 | "It was dusty, yes, but" | | 17 | "The victim's resting place was" | | 18 | "She pulled on a fresh" | | 19 | "Tolliver was a broad man," |
| | ratio | 0.779 | |
| 73.53% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 68 | | matches | | 0 | "Whoever had opened that hatch" |
| | ratio | 0.015 | |
| 61.22% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 4 | | matches | | 0 | "The Tube station smelled of old iron and something else — something that didn't belong to any maintenance crew or urban fox." | | 1 | "Tolliver was a broad man, thick through the chest, the kind of weight that made placement a two-person job at minimum." | | 2 | "Behind the brick, air circulated — not the dead, stale breath of a sealed cavity, but a slow and deliberate current, as though something on the far side exhaled…" | | 3 | "She could make out markings on its surface, fine-etched lines that weren't decorative in any way she recognised." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | 0 | "Patel continued (continue)" |
| | dialogueSentences | 22 | | tagDensity | 0.227 | | leniency | 0.455 | | rawRatio | 0.2 | | effectiveRatio | 0.091 | |