| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.125 | | leniency | 0.25 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1279 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1279 | | totalAiIsms | 37 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | |
| | highlights | | 0 | "measured" | | 1 | "flickered" | | 2 | "pulse" | | 3 | "throbbed" | | 4 | "treacherous" | | 5 | "footsteps" | | 6 | "echoed" | | 7 | "gloom" | | 8 | "symphony" | | 9 | "echoes" | | 10 | "electric" | | 11 | "otherworldly" | | 12 | "etched" | | 13 | "silence" | | 14 | "scanned" | | 15 | "glinting" | | 16 | "thundered" | | 17 | "depths" | | 18 | "resolve" | | 19 | "silk" | | 20 | "charged" | | 21 | "shattered" | | 22 | "pulsed" |
| |
| 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 | 279 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 279 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 291 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 21 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1253 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 104 | | wordCount | 1188 | | uniqueNames | 35 | | maxNameDensity | 1.35 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Tomás" | | discoveredNames | | Soho | 2 | | Raven | 1 | | Nest | 2 | | Detective | 1 | | Harlow | 16 | | Quinn | 1 | | Tomás | 15 | | Herrera | 2 | | Saint | 1 | | Christopher | 1 | | Charing | 1 | | Cross | 1 | | Road | 2 | | Morris | 3 | | Tottenham | 1 | | Court | 1 | | Vice | 1 | | Market | 2 | | Tube | 1 | | Camden | 1 | | Chaos | 1 | | Backup | 3 | | Portal | 2 | | Word | 1 | | Rain | 6 | | Boots | 3 | | Footsteps | 3 | | Faint | 3 | | Torch | 6 | | Tunnel | 3 | | Grate | 3 | | Decision | 3 | | Crowd | 5 | | Fingers | 3 | | Scale-face | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" | | 7 | "Backup" | | 8 | "Portal" | | 9 | "Rain" | | 10 | "Boots" | | 11 | "Footsteps" | | 12 | "Torch" | | 13 | "Tunnel" | | 14 | "Grate" | | 15 | "Decision" | | 16 | "Crowd" | | 17 | "Fingers" | | 18 | "Scale-face" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Detective" | | 3 | "Charing" | | 4 | "Cross" | | 5 | "Road" | | 6 | "Tottenham" | | 7 | "Court" | | 8 | "Vice" |
| | globalScore | 0.827 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1253 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 291 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 116 | | mean | 10.8 | | std | 10.17 | | cv | 0.942 | | sampleLengths | | 0 | 61 | | 1 | 38 | | 2 | 8 | | 3 | 37 | | 4 | 34 | | 5 | 52 | | 6 | 34 | | 7 | 5 | | 8 | 30 | | 9 | 20 | | 10 | 32 | | 11 | 15 | | 12 | 16 | | 13 | 21 | | 14 | 32 | | 15 | 15 | | 16 | 6 | | 17 | 18 | | 18 | 3 | | 19 | 15 | | 20 | 21 | | 21 | 20 | | 22 | 13 | | 23 | 23 | | 24 | 11 | | 25 | 26 | | 26 | 8 | | 27 | 6 | | 28 | 24 | | 29 | 13 | | 30 | 8 | | 31 | 12 | | 32 | 7 | | 33 | 4 | | 34 | 5 | | 35 | 2 | | 36 | 8 | | 37 | 5 | | 38 | 3 | | 39 | 25 | | 40 | 18 | | 41 | 18 | | 42 | 4 | | 43 | 16 | | 44 | 9 | | 45 | 15 | | 46 | 6 | | 47 | 8 | | 48 | 10 | | 49 | 13 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 279 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 323 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 2 | | flaggedSentences | 16 | | totalSentences | 291 | | ratio | 0.055 | | matches | | 0 | "Military precision kicked in—feet precise, strides measured despite the wet stone threatening slip." | | 1 | "DS Morris's face flickered in her mind—gone three years, that warehouse case, whispers of things that didn't add up." | | 2 | "Underground entrance yawned nearby—closed for construction, barriers askew." | | 3 | "Phone torch pierced gloom—empty platform, graffiti claws on tiles." | | 4 | "She chose right—instinct from eighteen years chasing ghosts." | | 5 | "She'd heard rumors in Vice—black market keys carved from who-knew-what." | | 6 | "Torch swept the lock—rusted padlock, but runes etched deep, pulsing faint." | | 7 | "Footsteps approached from below—multiple." | | 8 | "Morris's end—warehouse shadows that moved wrong." | | 9 | "But Herrera—link to the clique, their off-books doc stitching supernaturals." | | 10 | "Crowd parted grudging—cop stink clung, even here." | | 11 | "No draw yet; rules blurred underground." | | 12 | "Rain forgotten; market pulse owned her veins." | | 13 | "Grabbed vial from stall—blue fizz." | | 14 | "Or—" | | 15 | "Then—" |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1215 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.013991769547325103 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0016460905349794238 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 291 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 291 | | mean | 4.31 | | std | 3.14 | | cv | 0.73 | | sampleLengths | | 0 | 5 | | 1 | 17 | | 2 | 13 | | 3 | 10 | | 4 | 16 | | 5 | 2 | | 6 | 6 | | 7 | 9 | | 8 | 21 | | 9 | 8 | | 10 | 4 | | 11 | 8 | | 12 | 5 | | 13 | 7 | | 14 | 13 | | 15 | 2 | | 16 | 9 | | 17 | 9 | | 18 | 2 | | 19 | 12 | | 20 | 8 | | 21 | 5 | | 22 | 15 | | 23 | 19 | | 24 | 5 | | 25 | 8 | | 26 | 3 | | 27 | 7 | | 28 | 4 | | 29 | 6 | | 30 | 6 | | 31 | 5 | | 32 | 4 | | 33 | 11 | | 34 | 7 | | 35 | 8 | | 36 | 4 | | 37 | 2 | | 38 | 4 | | 39 | 10 | | 40 | 10 | | 41 | 10 | | 42 | 3 | | 43 | 9 | | 44 | 2 | | 45 | 2 | | 46 | 11 | | 47 | 2 | | 48 | 3 | | 49 | 4 |
| |
| 99.08% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.5945017182130584 | | totalSentences | 291 | | uniqueOpeners | 173 | |
| 17.92% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 186 | | matches | | 0 | "Otherworldly murmur rose: voices layered," |
| | ratio | 0.005 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 186 | | matches | | 0 | "She gripped her coat collar" | | 1 | "His Saint Christopher medallion caught" | | 2 | "She glimpsed his olive skin," | | 3 | "Her shout drowned in the" | | 4 | "He didn't glance back." | | 5 | "He cut sharp right, into" | | 6 | "She'd watched him inside earlier," | | 7 | "He vaulted a low fence" | | 8 | "His silhouette twisted ahead, medallion" | | 9 | "He burst onto Tottenham Court" | | 10 | "Her lungs clawed air." | | 11 | "He vaulted the barrier, vanished" | | 12 | "She hit the metal hard," | | 13 | "She chose right—instinct from eighteen" | | 14 | "She stifled a curse." | | 15 | "She'd heard rumors in Vice—black" | | 16 | "He slipped through." | | 17 | "She gripped bars." | | 18 | "Her radio crackled static." | | 19 | "She pressed palm to watch," |
| | ratio | 0.22 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 130 | | totalSentences | 186 | | matches | | 0 | "Neon bled into gutters, green" | | 1 | "She gripped her coat collar" | | 2 | "His Saint Christopher medallion caught" | | 3 | "Boots slapped puddles, splashed her" | | 4 | "Salt-and-pepper hair plastered to her" | | 5 | "She glimpsed his olive skin," | | 6 | "Her shout drowned in the" | | 7 | "He didn't glance back." | | 8 | "Harlow followed, coat snagging wire." | | 9 | "Pain bit her palm where" | | 10 | "Military precision kicked in—feet precise," | | 11 | "Soho's pulse throbbed: laughter from" | | 12 | "Tomás emerged onto Charing Cross" | | 13 | "He cut sharp right, into" | | 14 | "Harlow's worn leather watch ticked" | | 15 | "She'd watched him inside earlier," | | 16 | "DS Morris's face flickered in" | | 17 | "He vaulted a low fence" | | 18 | "Harlow hurdled after, knees protesting" | | 19 | "Adrenaline burned it away." |
| | ratio | 0.699 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 186 | | matches | (empty) | | ratio | 0 | |
| 80.75% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 2 | | matches | | 0 | "DS Morris's face flickered in her mind—gone three years, that warehouse case, whispers of things that didn't add up." | | 1 | "Stalls flickered into view: vials glowing emerald, blades etched sigils, cages with eyes that blinked." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 87.50% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 16 | | tagDensity | 0.063 | | leniency | 0.125 | | rawRatio | 1 | | effectiveRatio | 0.125 | |