| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1360 | | 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) | |
| 52.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1360 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "shattered" | | 1 | "rhythmic" | | 2 | "familiar" | | 3 | "footsteps" | | 4 | "gloom" | | 5 | "scanning" | | 6 | "silk" | | 7 | "stomach" | | 8 | "velvet" | | 9 | "calculated" | | 10 | "echo" | | 11 | "flicked" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 2 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 94 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 94 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 4 | | totalWords | 1355 | | ratio | 0.003 | | matches | | 0 | "unexplained blunt force trauma" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 96.28% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1303 | | uniqueNames | 15 | | maxNameDensity | 1.07 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | London | 2 | | Camden | 2 | | High | 1 | | Street | 1 | | Harlow | 14 | | Quinn | 1 | | Herrera | 7 | | Soho | 1 | | Morris | 3 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Morris" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Tomás" |
| | places | | 0 | "London" | | 1 | "Camden" | | 2 | "High" | | 3 | "Street" | | 4 | "Soho" |
| | globalScore | 0.963 | | windowScore | 1 | |
| 53.85% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 3 | | matches | | 0 | "sounded like bees in a wall" | | 1 | "looked like a woman who belonged" | | 2 | "ring that seemed to echo too loudly in the vaulted ceiling" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.738 | | wordCount | 1355 | | matches | | 0 | "not the usual damp subterranean rot of the London underground, but something sharper" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 38.71 | | std | 21.72 | | cv | 0.561 | | sampleLengths | | 0 | 52 | | 1 | 47 | | 2 | 106 | | 3 | 19 | | 4 | 58 | | 5 | 39 | | 6 | 10 | | 7 | 53 | | 8 | 54 | | 9 | 47 | | 10 | 59 | | 11 | 16 | | 12 | 53 | | 13 | 51 | | 14 | 13 | | 15 | 47 | | 16 | 3 | | 17 | 32 | | 18 | 54 | | 19 | 8 | | 20 | 59 | | 21 | 80 | | 22 | 15 | | 23 | 28 | | 24 | 44 | | 25 | 38 | | 26 | 24 | | 27 | 36 | | 28 | 43 | | 29 | 12 | | 30 | 33 | | 31 | 40 | | 32 | 25 | | 33 | 7 | | 34 | 50 |
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| 86.60% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 94 | | matches | | 0 | "been shuttered" | | 1 | "was snapped" | | 2 | "was gone" | | 3 | "been stripped" | | 4 | "was choked" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 209 | | matches | | 0 | "wasn't running" | | 1 | "was drawing" | | 2 | "was still settling" | | 3 | "was watching" | | 4 | "wasn't looking" | | 5 | "was, breathing" | | 6 | "was speaking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 4 | | flaggedSentences | 8 | | totalSentences | 95 | | ratio | 0.084 | | matches | | 0 | "She knew the way he carried himself—the slight, protective hitch on his left side, a subconscious shield for the patched-up scar on his forearm." | | 1 | "Ruptured organs stitched back together with threads that dissolved into ash; shattered bones that fused in hours instead of months." | | 2 | "Harlow remembered the council notices from months ago; the station had been shuttered since the sixties, a hollow artery beneath the city." | | 3 | "The scent was strange—not the usual damp subterranean rot of the London underground, but something sharper." | | 4 | "He wasn't looking for police; he was watching the few patrons who drifted down from a secondary entrance." | | 5 | "Inside was a sterling silver lighter—a retirement gift to Morris from his father, which she’d recovered from his desk." | | 6 | "She did not look like a woman lost; she looked like a woman who belonged." | | 7 | "A small, blue flame flared, illuminating his face—his skin was gray, dry as parchment, with deep, unnatural creases around his jaw." |
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| 82.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 804 | | adjectiveStacks | 3 | | stackExamples | | 0 | "heavy, grease-slicked mist" | | 1 | "under *unexplained blunt force" | | 2 | "polished, finger-sized knucklebone" |
| | adverbCount | 15 | | adverbRatio | 0.018656716417910446 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007462686567164179 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 14.26 | | std | 8.13 | | cv | 0.57 | | sampleLengths | | 0 | 32 | | 1 | 20 | | 2 | 4 | | 3 | 24 | | 4 | 19 | | 5 | 5 | | 6 | 15 | | 7 | 27 | | 8 | 20 | | 9 | 39 | | 10 | 19 | | 11 | 7 | | 12 | 19 | | 13 | 32 | | 14 | 6 | | 15 | 22 | | 16 | 11 | | 17 | 10 | | 18 | 18 | | 19 | 10 | | 20 | 12 | | 21 | 13 | | 22 | 17 | | 23 | 22 | | 24 | 15 | | 25 | 26 | | 26 | 16 | | 27 | 1 | | 28 | 2 | | 29 | 2 | | 30 | 12 | | 31 | 22 | | 32 | 6 | | 33 | 19 | | 34 | 5 | | 35 | 11 | | 36 | 18 | | 37 | 10 | | 38 | 7 | | 39 | 18 | | 40 | 14 | | 41 | 16 | | 42 | 21 | | 43 | 13 | | 44 | 18 | | 45 | 18 | | 46 | 11 | | 47 | 3 | | 48 | 19 | | 49 | 13 |
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| 46.32% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3157894736842105 | | totalSentences | 95 | | uniqueOpeners | 30 | |
| 74.07% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 90 | | matches | | 0 | "Instead, the space was choked" | | 1 | "Then, the guard let out" |
| | ratio | 0.022 | |
| 42.22% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 90 | | matches | | 0 | "She knew those shoulders." | | 1 | "She knew the way he" | | 2 | "She had been tracking Herrera" | | 3 | "It smelled of the same" | | 4 | "Her boots clicked against the" | | 5 | "She reached the mouth of" | | 6 | "She paused, her sharp jaw" | | 7 | "Her hand drifted naturally to" | | 8 | "she whispered, her voice a" | | 9 | "She pushed through the gap" | | 10 | "She tracked him by the" | | 11 | "He wasn't running yet, which" | | 12 | "Her military training screamed at" | | 13 | "She pushed the door open." | | 14 | "It swung inward on greased" | | 15 | "She kept one hand on" | | 16 | "He wasn't looking for police;" | | 17 | "Her stomach tightened." | | 18 | "She had heard whispers of" | | 19 | "It was a myth, she’d" |
| | ratio | 0.444 | |
| 48.89% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 90 | | matches | | 0 | "The rain in London did" | | 1 | "Detective Harlow Quinn adjusted the" | | 2 | "She knew those shoulders." | | 3 | "She knew the way he" | | 4 | "Tomás Herrera was moving fast," | | 5 | "Harlow checked her left wrist." | | 6 | "The worn leather strap of" | | 7 | "She had been tracking Herrera" | | 8 | "It smelled of the same" | | 9 | "Herrera turned abruptly, ducking down" | | 10 | "Harlow broke into a silent," | | 11 | "Her boots clicked against the" | | 12 | "She reached the mouth of" | | 13 | "She paused, her sharp jaw" | | 14 | "Her hand drifted naturally to" | | 15 | "The alley was dark, smelling" | | 16 | "she whispered, her voice a" | | 17 | "She pushed through the gap" | | 18 | "She tracked him by the" | | 19 | "He wasn't running yet, which" |
| | ratio | 0.822 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 90 | | matches | | 0 | "Or, worse, he knew exactly" | | 1 | "To pass him, each traveler" | | 2 | "If she let him go" |
| | ratio | 0.033 | |
| 49.18% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 8 | | matches | | 0 | "The rain in London did not fall so much as it drifted, a heavy, grease-slicked mist that turned the neon glare of Camden High Street into a smear of green and a…" | | 1 | "She had been tracking Herrera for three weeks, ever since a tipster in Soho linked him to a series of back-alley medical procedures that defied basic biology." | | 2 | "It smelled of the same impossible, sickening wrongness that had hung in the air three years ago, the night DS Morris died in a warehouse by the docks, his chest…" | | 3 | "She reached the mouth of the alley just in time to see the tail of Herrera’s jacket vanish around a corner, slipping past a chain-link fence that hung open like…" | | 4 | "The alley dead-ended at a set of metal double doors that belonged to an abandoned Tube station." | | 5 | "He wasn't looking for police; he was watching the few patrons who drifted down from a secondary entrance." | | 6 | "He was a big man, broad-necked, with eyes that caught the orange lantern light in a way that didn't seem entirely human." | | 7 | "The guard stared at her, his dark eyes searching her sharp features, his gaze lingering on the quiet authority in her posture." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 1 | | matches | | 0 | "she whispered, her voice a low rasp" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "he whispered (whisper)" |
| | dialogueSentences | 5 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0.667 | | effectiveRatio | 0.667 | |