| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said softly [softly]" |
| | dialogueSentences | 10 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.2 | | effectiveRatio | 0.2 | |
| 87.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1224 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "softly" |
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| 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) | |
| 67.32% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1224 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "streaming" | | 1 | "pumping" | | 2 | "measured" | | 3 | "footsteps" | | 4 | "throbbed" | | 5 | "pulse" | | 6 | "scanning" |
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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 | 71 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 71 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 76 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 8 | | totalWords | 1235 | | ratio | 0.006 | | matches | | 0 | "missing, presumed deceased." | | 1 | "poor Quinn, still chasing ghosts." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 1172 | | uniqueNames | 9 | | maxNameDensity | 0.77 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | Harlow | 2 | | Quinn | 9 | | Herrera | 6 | | Saint | 1 | | Christopher | 1 | | Tube | 1 | | Morris | 2 | | London | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Morris" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 55.66% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like it should hurt" | | 1 | "not quite fear, something closer to warning" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.81 | | wordCount | 1235 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 76 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 44.11 | | std | 33.04 | | cv | 0.749 | | sampleLengths | | 0 | 49 | | 1 | 75 | | 2 | 17 | | 3 | 7 | | 4 | 113 | | 5 | 19 | | 6 | 9 | | 7 | 71 | | 8 | 31 | | 9 | 114 | | 10 | 20 | | 11 | 56 | | 12 | 103 | | 13 | 32 | | 14 | 13 | | 15 | 85 | | 16 | 6 | | 17 | 106 | | 18 | 29 | | 19 | 11 | | 20 | 35 | | 21 | 33 | | 22 | 49 | | 23 | 35 | | 24 | 42 | | 25 | 19 | | 26 | 32 | | 27 | 24 |
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| 90.44% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 71 | | matches | | 0 | "been trained" | | 1 | "were tiled" | | 2 | "was gone" |
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| 97.44% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 195 | | matches | | 0 | "were already fading" | | 1 | "was still moving" | | 2 | "was pulling" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 76 | | ratio | 0.118 | | matches | | 0 | "She knew the name now, knew the face — olive skin, dark curls flattened by the downpour, a Saint Christopher medallion that caught the streetlight when he glanced back over his shoulder." | | 1 | "Everyone in Camden walked past them a hundred times without seeing them — the boarded entrance to a Tube station that had closed before either of them was born, the grille rusted, the sign long since scraped clean." | | 2 | "Below her, the stairwell descended into a throat of pure black, and out of it came a smell she couldn't place — wet stone, yes, but underneath it something sweeter and stranger, like incense burning over hot copper." | | 3 | "Three years since DS Morris had walked into a place like this — a doorway that shouldn't open, a stairwell that went down further than the blueprints allowed — and had never walked back out." | | 4 | "She hadn't told anyone where she was tonight, because the people she'd have to tell would look at her the way they'd looked at her after Morris — with that careful, patient pity, *poor Quinn, still chasing ghosts.* If she radioed this in, they'd find an empty stairwell and a boarded door, because that was what these places did." | | 5 | "If she lost him now, she lost everything — and she had spent three years refusing to lose anything else to the dark." | | 6 | "Stalls crowded the old platform beneath strings of lantern-light that burned in colors she had no name for — a green that throbbed like a pulse, a blue so cold it looked like it should hurt." | | 7 | "There — moving fast along the far wall, glancing back, the medallion swinging." | | 8 | "Across the platform, Herrera reached a doorway hung with a curtain of green light and turned, and for one suspended instant their eyes met across the impossible room — his wide with something that was not quite fear, something closer to warning." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1166 | | adjectiveStacks | 1 | | stackExamples | | 0 | "careful settled behind them." |
| | adverbCount | 35 | | adverbRatio | 0.030017152658662092 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005145797598627788 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 76 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 76 | | mean | 16.25 | | std | 13.82 | | cv | 0.85 | | sampleLengths | | 0 | 20 | | 1 | 29 | | 2 | 26 | | 3 | 2 | | 4 | 32 | | 5 | 15 | | 6 | 3 | | 7 | 9 | | 8 | 5 | | 9 | 4 | | 10 | 3 | | 11 | 52 | | 12 | 19 | | 13 | 4 | | 14 | 38 | | 15 | 7 | | 16 | 12 | | 17 | 9 | | 18 | 38 | | 19 | 26 | | 20 | 7 | | 21 | 31 | | 22 | 2 | | 23 | 35 | | 24 | 4 | | 25 | 21 | | 26 | 5 | | 27 | 47 | | 28 | 13 | | 29 | 6 | | 30 | 1 | | 31 | 15 | | 32 | 3 | | 33 | 3 | | 34 | 23 | | 35 | 4 | | 36 | 8 | | 37 | 6 | | 38 | 59 | | 39 | 2 | | 40 | 2 | | 41 | 34 | | 42 | 5 | | 43 | 4 | | 44 | 23 | | 45 | 13 | | 46 | 6 | | 47 | 37 | | 48 | 30 | | 49 | 12 |
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| 74.12% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.5 | | totalSentences | 76 | | uniqueOpeners | 38 | |
| 52.08% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 64 | | matches | | 0 | "Then he was gone through" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 64 | | matches | | 0 | "She knew the name now," | | 1 | "He was fast, but she" | | 2 | "Her voice cracked against the" | | 3 | "He did not stop." | | 4 | "They never did." | | 5 | "Her boots slammed through a" | | 6 | "She knew those steps." | | 7 | "It hung open on a" | | 8 | "She stood at the edge" | | 9 | "They'd found his car." | | 10 | "They'd found his radio, his" | | 11 | "They had never found him." | | 12 | "She glanced down at the" | | 13 | "She hadn't told anyone where" | | 14 | "She kept her voice level," | | 15 | "His grip tightened, and his" | | 16 | "She reached into her coat," | | 17 | "His cat-bright eyes lifted to" | | 18 | "he said softly, releasing her" |
| | ratio | 0.297 | |
| 69.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 64 | | matches | | 0 | "The rain came sideways, hammering" | | 1 | "Detective Harlow Quinn ran through" | | 2 | "She knew the name now," | | 3 | "He was fast, but she" | | 4 | "Her voice cracked against the" | | 5 | "He did not stop." | | 6 | "They never did." | | 7 | "Her boots slammed through a" | | 8 | "Herrera vaulted a low railing" | | 9 | "She knew those steps." | | 10 | "Everyone in Camden walked past" | | 11 | "It hung open on a" | | 12 | "Quinn reached the top of" | | 13 | "Herrera's footsteps were already fading" | | 14 | "She stood at the edge" | | 15 | "They'd found his car." | | 16 | "They'd found his radio, his" | | 17 | "They had never found him." | | 18 | "The official report said *missing," | | 19 | "She glanced down at the" |
| | ratio | 0.781 | |
| 78.13% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 64 | | matches | | | ratio | 0.016 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 9 | | matches | | 0 | "She knew the name now, knew the face — olive skin, dark curls flattened by the downpour, a Saint Christopher medallion that caught the streetlight when he glanc…" | | 1 | "Her boots slammed through a puddle deep enough to swallow her ankle, and she felt the cold bite straight up her shin, but she kept her arms pumping, kept her br…" | | 2 | "Faint music drifted up, threaded with voices, the murmur of a crowd that should not have existed in an abandoned station beneath a dead city street." | | 3 | "She stood at the edge with the rain drumming on her skull and her hand resting on the railing, and for the first time in a long while, Harlow Quinn hesitated." | | 4 | "They'd found his radio, his notebook, his wedding ring placed neatly on the dashboard as if he'd taken it off himself." | | 5 | "Stalls crowded the old platform beneath strings of lantern-light that burned in colors she had no name for — a green that throbbed like a pulse, a blue so cold …" | | 6 | "Figures moved among the stalls in cloaks and fine coats and a few in nothing she could parse as clothing at all, haggling over jars of luminous liquid, over fol…" | | 7 | "A boy, no older than twelve, with eyes that reflected the lantern-light like a cat's." | | 8 | "Across the platform, Herrera reached a doorway hung with a curtain of green light and turned, and for one suspended instant their eyes met across the impossible…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 50.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 10 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0.333 | | effectiveRatio | 0.2 | |