| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 93.65% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1574 | | 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) | |
| 68.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1574 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "scanned" | | 1 | "measured" | | 2 | "pulse" | | 3 | "quickened" | | 4 | "electric" | | 5 | "standard" | | 6 | "mechanical" | | 7 | "stomach" | | 8 | "echoing" |
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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 | 149 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 149 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 149 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1599 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 1599 | | uniqueNames | 26 | | maxNameDensity | 0.69 | | worstName | "Harlow" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Pete" | | discoveredNames | | Quinn | 2 | | Greek | 2 | | Street | 3 | | Raven | 1 | | Nest | 2 | | Soho | 3 | | Pete | 5 | | Harlow | 11 | | Saint | 2 | | Christopher | 2 | | Square | 1 | | Covent | 1 | | Garden | 1 | | Dean | 1 | | Shaftesbury | 1 | | Avenue | 1 | | Herrera | 8 | | Morris | 4 | | Hackney | 1 | | Chalk | 1 | | Farm | 1 | | Road | 1 | | Camden | 4 | | Electric | 1 | | Ballroom | 1 | | Cockney | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Pete" | | 2 | "Harlow" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Herrera" | | 6 | "Morris" |
| | places | | 0 | "Greek" | | 1 | "Street" | | 2 | "Raven" | | 3 | "Soho" | | 4 | "Covent" | | 5 | "Garden" | | 6 | "Dean" | | 7 | "Shaftesbury" | | 8 | "Avenue" | | 9 | "Hackney" | | 10 | "Chalk" | | 11 | "Farm" | | 12 | "Road" | | 13 | "Camden" | | 14 | "Electric" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 96 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed almost deliberate" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 4 | | per1kWords | 2.502 | | wordCount | 1599 | | matches | | 0 | "not pain, but recognition" | | 1 | "No sound but" | | 2 | "not mechanical, not a lock releasing, but something else" | | 3 | "not a lock releasing, but something else" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 149 | | matches | (empty) | |
| 92.25% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 47.03 | | std | 22.24 | | cv | 0.473 | | sampleLengths | | 0 | 7 | | 1 | 84 | | 2 | 75 | | 3 | 57 | | 4 | 9 | | 5 | 67 | | 6 | 50 | | 7 | 73 | | 8 | 55 | | 9 | 76 | | 10 | 66 | | 11 | 21 | | 12 | 53 | | 13 | 77 | | 14 | 64 | | 15 | 51 | | 16 | 42 | | 17 | 67 | | 18 | 57 | | 19 | 65 | | 20 | 56 | | 21 | 11 | | 22 | 53 | | 23 | 36 | | 24 | 62 | | 25 | 37 | | 26 | 50 | | 27 | 49 | | 28 | 8 | | 29 | 34 | | 30 | 34 | | 31 | 16 | | 32 | 25 | | 33 | 12 |
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| 95.84% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 149 | | matches | | 0 | "been terrified" | | 1 | "was — reached" | | 2 | "was gone" | | 3 | "was insulated" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 281 | | matches | | 0 | "was going" | | 1 | "was heading" | | 2 | "were still spilling" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 25 | | semicolonCount | 0 | | flaggedSentences | 19 | | totalSentences | 149 | | ratio | 0.128 | | matches | | 0 | "He walked with purpose but not urgency — a man who knew where he was going and didn't expect to be followed." | | 1 | "Her informant — a junkie named Pete who owed her for looking the other way on a possession charge — had told her the bar was a meeting point for something bigger." | | 2 | "She recognized the posture — the way he scanned corners and checked sight lines without conscious thought." | | 3 | "Herrera — if that's who he was — reached the intersection of Greek Street and Soho Square and turned left." | | 4 | "The chase — if it could be called that — was a strange, measured thing." | | 5 | "She memorized the route out of habit — left on Dean Street, right on Shaftesbury Avenue, then a series of cuts through side streets she barely knew." | | 6 | "If he was part of something larger — a trafficking ring, a smuggling operation, whatever Pete had been too afraid to name — he might lead her to a meeting." | | 7 | "The expression frozen on his face — not pain, but recognition." | | 8 | "Herrera pushed through the crowd outside the Electric Ballroom without slowing down, and for a moment she lost him — just a flash of his dark jacket and curly hair swallowed by bodies and umbrellas." | | 9 | "She hadn't called it in because she had nothing to call in — just a hunch and a frightened informant's story about supernatural wounds and hidden rooms." | | 10 | "He glanced over his shoulder — a quick, practiced check — and she pressed herself into the shadow of a skip, holding her breath." | | 11 | "She ran her fingers along the edge and felt a shallow indentation — a slot, narrow and rectangular, about the length of her index finger." | | 12 | "She could wait — set up a surveillance point and watch for Herrera to emerge." | | 13 | "And she'd been here before — circling something just out of reach, watching it slip away while she followed proper procedure." | | 14 | "Saint Christopher — the patron saint of travelers." | | 15 | "And she thought about the file on her desk at the station — eighteen years of commendations and citations, a career built on following evidence, trusting the process, doing things by the book." | | 16 | "Whatever was behind it — evidence or danger or something she couldn't yet name — it was closer than she'd been in three years to understanding what had happened to her partner." | | 17 | "She pushed harder, leaning her shoulder into it, and felt the faintest give — not mechanical, not a lock releasing, but something else." | | 18 | "Warm air rushed out through the gap, carrying scents she couldn't name — smoke and copper and something sweet that turned her stomach." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1581 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 37 | | adverbRatio | 0.02340290955091714 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.006957621758380772 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 149 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 149 | | mean | 10.73 | | std | 8.71 | | cv | 0.812 | | sampleLengths | | 0 | 7 | | 1 | 26 | | 2 | 22 | | 3 | 36 | | 4 | 8 | | 5 | 2 | | 6 | 19 | | 7 | 32 | | 8 | 5 | | 9 | 5 | | 10 | 4 | | 11 | 4 | | 12 | 20 | | 13 | 5 | | 14 | 10 | | 15 | 18 | | 16 | 9 | | 17 | 5 | | 18 | 13 | | 19 | 21 | | 20 | 4 | | 21 | 3 | | 22 | 17 | | 23 | 4 | | 24 | 20 | | 25 | 17 | | 26 | 8 | | 27 | 5 | | 28 | 15 | | 29 | 9 | | 30 | 13 | | 31 | 8 | | 32 | 10 | | 33 | 8 | | 34 | 10 | | 35 | 17 | | 36 | 27 | | 37 | 4 | | 38 | 3 | | 39 | 4 | | 40 | 9 | | 41 | 11 | | 42 | 30 | | 43 | 3 | | 44 | 2 | | 45 | 21 | | 46 | 4 | | 47 | 16 | | 48 | 6 | | 49 | 2 |
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| 37.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 21 | | diversityRatio | 0.3087248322147651 | | totalSentences | 149 | | uniqueOpeners | 46 | |
| 76.92% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 130 | | matches | | 0 | "Genuinely, bone-deep terrified, and Harlow" | | 1 | "Then a minute." | | 2 | "Somewhere a siren wailed and" |
| | ratio | 0.023 | |
| 90.77% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 130 | | matches | | 0 | "He walked with purpose but" | | 1 | "She'd picked him up outside" | | 2 | "She'd been watching the Nest" | | 3 | "Her informant — a junkie" | | 4 | "He'd described faces, voices, a" | | 5 | "She'd filed it away and" | | 6 | "He wore a dark jacket," | | 7 | "She recognized the posture —" | | 8 | "Her leather watch grew slick" | | 9 | "She ignored it and followed." | | 10 | "He led her northwest, through" | | 11 | "She memorized the route out" | | 12 | "His stride never faltered." | | 13 | "He wasn't lost." | | 14 | "He had a destination." | | 15 | "She'd read the coroner's report" | | 16 | "She'd spent three years trying" | | 17 | "He was heading toward Camden." | | 18 | "She closed the distance to" | | 19 | "She quickened her pace, shouldering" |
| | ratio | 0.323 | |
| 67.69% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 102 | | totalSentences | 130 | | matches | | 0 | "The rain came down like" | | 1 | "Harlow Quinn stood beneath the" | | 2 | "He walked with purpose but" | | 3 | "She'd picked him up outside" | | 4 | "She'd been watching the Nest" | | 5 | "A dim hole-in-the-wall in Soho" | | 6 | "Her informant — a junkie" | | 7 | "A clique, he'd called them." | | 8 | "People who moved in shadows." | | 9 | "People who knew things." | | 10 | "Pete had been terrified." | | 11 | "Pete had the real thing." | | 12 | "He'd described faces, voices, a" | | 13 | "She'd filed it away and" | | 14 | "The medallion caught the streetlight" | | 15 | "He wore a dark jacket," | | 16 | "She recognized the posture —" | | 17 | "The way she did." | | 18 | "Herrera — if that's who" | | 19 | "Harlow stepped out from under" |
| | ratio | 0.785 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 130 | | matches | | 0 | "If Herrera was just a" | | 1 | "If he was part of" | | 2 | "Whoever used it, they used" |
| | ratio | 0.023 | |
| 62.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 62 | | technicalSentenceCount | 7 | | matches | | 0 | "A dim hole-in-the-wall in Soho that attracted the kind of clientele who paid in cash and didn't leave reviews." | | 1 | "Her informant — a junkie named Pete who owed her for looking the other way on a possession charge — had told her the bar was a meeting point for something bigge…" | | 2 | "And he'd described a man with a Saint Christopher medallion who treated wounds that shouldn't have been treatable." | | 3 | "She quickened her pace, shouldering past a group of girls who cursed at her in slurred Cockney, and caught sight of him again as he turned down a side street th…" | | 4 | "It was heavy, steel-reinforced, set into a frame that looked far newer than the surrounding brick." | | 5 | "A man who'd spent years treating wounds that shouldn't be treatable." | | 6 | "That career had left her standing in the rain at midnight, chasing ghosts through streets that led nowhere." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |