| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 66 | | tagDensity | 0.106 | | leniency | 0.212 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.46% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2205 | | 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) | |
| 90.93% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2205 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "weight" | | 1 | "etched" | | 2 | "flicked" | | 3 | "footsteps" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
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| | highlights | | 0 | "eyes widened" | | 1 | "eyes narrowed" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 172 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 172 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 230 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2207 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 79 | | wordCount | 1626 | | uniqueNames | 8 | | maxNameDensity | 2.09 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Bell" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 34 | | Camden | 1 | | Underground | 1 | | Metropolitan | 1 | | Bell | 24 | | Eva | 16 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Bell" | | 3 | "Eva" |
| | places | (empty) | | globalScore | 0.454 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 104 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.453 | | wordCount | 2207 | | matches | | 0 | "not toward the tunnel mouth or the stairs, but toward the far end of the platform" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 230 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 97 | | mean | 22.75 | | std | 20.99 | | cv | 0.923 | | sampleLengths | | 0 | 131 | | 1 | 31 | | 2 | 102 | | 3 | 59 | | 4 | 31 | | 5 | 15 | | 6 | 32 | | 7 | 31 | | 8 | 33 | | 9 | 14 | | 10 | 1 | | 11 | 2 | | 12 | 63 | | 13 | 9 | | 14 | 2 | | 15 | 62 | | 16 | 12 | | 17 | 13 | | 18 | 15 | | 19 | 23 | | 20 | 4 | | 21 | 28 | | 22 | 28 | | 23 | 19 | | 24 | 9 | | 25 | 38 | | 26 | 27 | | 27 | 64 | | 28 | 6 | | 29 | 45 | | 30 | 42 | | 31 | 6 | | 32 | 37 | | 33 | 8 | | 34 | 14 | | 35 | 6 | | 36 | 14 | | 37 | 4 | | 38 | 36 | | 39 | 14 | | 40 | 18 | | 41 | 49 | | 42 | 12 | | 43 | 10 | | 44 | 7 | | 45 | 6 | | 46 | 10 | | 47 | 15 | | 48 | 9 | | 49 | 27 |
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| 88.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 8 | | totalSentences | 172 | | matches | | 0 | "been told" | | 1 | "been sealed" | | 2 | "been inked" | | 3 | "been placed" | | 4 | "been forced" | | 5 | "been removed" | | 6 | "been carried" | | 7 | "been scattered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 257 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 230 | | ratio | 0.004 | | matches | | 0 | "The place still carried the bones of the Underground — soot in the grout, faded line maps behind cracked glass, a dead timetable board with half the letters missing — but the station had another skin beneath it now." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1627 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 45 | | adverbRatio | 0.027658266748617086 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0036877688998156115 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 230 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 230 | | mean | 9.6 | | std | 8.06 | | cv | 0.84 | | sampleLengths | | 0 | 20 | | 1 | 28 | | 2 | 39 | | 3 | 7 | | 4 | 11 | | 5 | 26 | | 6 | 22 | | 7 | 9 | | 8 | 25 | | 9 | 28 | | 10 | 5 | | 11 | 5 | | 12 | 9 | | 13 | 30 | | 14 | 17 | | 15 | 42 | | 16 | 10 | | 17 | 13 | | 18 | 8 | | 19 | 12 | | 20 | 3 | | 21 | 6 | | 22 | 8 | | 23 | 18 | | 24 | 11 | | 25 | 7 | | 26 | 10 | | 27 | 3 | | 28 | 4 | | 29 | 11 | | 30 | 18 | | 31 | 4 | | 32 | 10 | | 33 | 1 | | 34 | 2 | | 35 | 6 | | 36 | 4 | | 37 | 11 | | 38 | 33 | | 39 | 9 | | 40 | 9 | | 41 | 2 | | 42 | 3 | | 43 | 4 | | 44 | 10 | | 45 | 45 | | 46 | 8 | | 47 | 4 | | 48 | 8 | | 49 | 5 |
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| 44.64% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.30434782608695654 | | totalSentences | 230 | | uniqueOpeners | 70 | |
| 91.95% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 145 | | matches | | 0 | "Just the body, a ring" | | 1 | "Too neat for a forced" | | 2 | "Somewhere deeper in the station," | | 3 | "Just the low thrum of" |
| | ratio | 0.028 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 145 | | matches | | 0 | "She took in the scene" | | 1 | "She had tucked a strand" | | 2 | "He had the look of" | | 3 | "He hooked a thumb at" | | 4 | "His mouth hung open around" | | 5 | "She leaned closer." | | 6 | "It had a metallic sheen," | | 7 | "It clung in the crease" | | 8 | "His left palm held a" | | 9 | "His right hand clenched around" | | 10 | "She slipped on gloves and" | | 11 | "she asked Eva" | | 12 | "She followed it with her" | | 13 | "He nodded toward a square" | | 14 | "She crouched again." | | 15 | "Her eyes flicked to the" | | 16 | "She stopped over the feather," | | 17 | "She nodded once to herself." | | 18 | "She moved toward the maintenance" | | 19 | "She drew her torch and" |
| | ratio | 0.186 | |
| 39.31% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 122 | | totalSentences | 145 | | matches | | 0 | "The Tube stairs breathed cold" | | 1 | "The place still carried the" | | 2 | "Salt lines ran along the" | | 3 | "Someone had pinned a strip" | | 4 | "Quinn paused at the bottom" | | 5 | "She took in the scene" | | 6 | "A body lay near the" | | 7 | "The dead man wore a" | | 8 | "Eva stood near the far" | | 9 | "She had tucked a strand" | | 10 | "Inspector Bell, the scene lead," | | 11 | "He had the look of" | | 12 | "Quinn let her gaze slide" | | 13 | "He hooked a thumb at" | | 14 | "Quinn crouched beside the body," | | 15 | "The dead man’s pupils had" | | 16 | "His mouth hung open around" | | 17 | "She leaned closer." | | 18 | "It had a metallic sheen," | | 19 | "It clung in the crease" |
| | ratio | 0.841 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 145 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 64 | | technicalSentenceCount | 3 | | matches | | 0 | "Someone had pinned a strip of black cloth over a CCTV dome, as if fabric could blind a camera that had already been dead for years." | | 1 | "His left palm held a shallow burn in the shape of a circle, crisp-edged and pale at the centre, as if something hot had kissed the skin and left no scorch aroun…" | | 2 | "She held the lantern higher and caught a fresh detail on the wall beside the grate: a thumbprint in wet soot, smeared beside a sigil that had been half-wiped cl…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "Bell muttered (mutter)" | | 1 | "Quinn repeated (repeat)" |
| | dialogueSentences | 66 | | tagDensity | 0.091 | | leniency | 0.182 | | rawRatio | 0.333 | | effectiveRatio | 0.061 | |