| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.43% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1045 | | 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) | |
| 80.86% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1045 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "fractured" | | 1 | "silence" | | 2 | "pulsed" | | 3 | "footsteps" |
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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 | 55 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 55 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 62 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1039 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 81.58% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 950 | | uniqueNames | 11 | | maxNameDensity | 1.37 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Harlow | 1 | | Quinn | 13 | | Berwick | 1 | | Street | 1 | | Morris | 4 | | Tube | 1 | | Camden | 2 | | Heads | 1 |
| | persons | | 0 | "Nest" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Morris" | | 4 | "Heads" |
| | places | | 0 | "Raven" | | 1 | "Soho" | | 2 | "Berwick" | | 3 | "Street" |
| | globalScore | 0.816 | | windowScore | 0.833 | |
| 28.05% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | glossingSentenceCount | 2 | | matches | | 0 | "smelled like this—copper and ozone and som" | | 1 | "something like old copper coins" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1039 | | matches | (empty) | |
| 59.14% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 62 | | matches | | 0 | "screamed that a" | | 1 | "unsolved that she" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 33.52 | | std | 20.53 | | cv | 0.613 | | sampleLengths | | 0 | 53 | | 1 | 47 | | 2 | 2 | | 3 | 62 | | 4 | 46 | | 5 | 37 | | 6 | 2 | | 7 | 38 | | 8 | 14 | | 9 | 45 | | 10 | 29 | | 11 | 40 | | 12 | 79 | | 13 | 3 | | 14 | 52 | | 15 | 52 | | 16 | 43 | | 17 | 9 | | 18 | 63 | | 19 | 32 | | 20 | 48 | | 21 | 21 | | 22 | 53 | | 23 | 22 | | 24 | 3 | | 25 | 42 | | 26 | 4 | | 27 | 38 | | 28 | 35 | | 29 | 17 | | 30 | 8 |
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| 98.88% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 55 | | matches | | |
| 43.14% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 170 | | matches | | 0 | "was already disappearing" | | 1 | "wasn't coming" | | 2 | "was running" | | 3 | "were deciding" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 62 | | ratio | 0.097 | | matches | | 0 | "Quinn recognized him from the CCTV stills—tall, thin, moving with the jerky economy of someone who'd learned to walk without drawing attention." | | 1 | "Eighteen years on the force had taught her the rhythm of a tail—close enough to react, far enough to vanish into a doorway if he turned." | | 2 | "The manual had never covered the reports she'd buried in her own desk drawer—witnesses babbling about market stalls that sold moonlight, about coins made of bone, about doors that only opened once a month." | | 3 | "Voices reached her before the light did—murmured haggling, a laugh too sharp to be human, the clink of coin on stone." | | 4 | "Not human heads, not all of them—she caught the flash of something with too many eyes near a stall selling jars of shifting smoke, caught the low growl from a shape wrapped head to foot in oilskin." | | 5 | "Whatever had taken him had smelled like this—copper and ozone and something sweetly rotten underneath." |
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| 96.68% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 959 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 42 | | adverbRatio | 0.043795620437956206 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0072992700729927005 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 62 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 62 | | mean | 16.76 | | std | 11.41 | | cv | 0.681 | | sampleLengths | | 0 | 27 | | 1 | 26 | | 2 | 8 | | 3 | 22 | | 4 | 17 | | 5 | 2 | | 6 | 22 | | 7 | 26 | | 8 | 3 | | 9 | 11 | | 10 | 19 | | 11 | 5 | | 12 | 22 | | 13 | 12 | | 14 | 25 | | 15 | 2 | | 16 | 8 | | 17 | 30 | | 18 | 9 | | 19 | 5 | | 20 | 13 | | 21 | 18 | | 22 | 14 | | 23 | 29 | | 24 | 12 | | 25 | 28 | | 26 | 35 | | 27 | 10 | | 28 | 34 | | 29 | 3 | | 30 | 42 | | 31 | 1 | | 32 | 9 | | 33 | 21 | | 34 | 31 | | 35 | 43 | | 36 | 6 | | 37 | 3 | | 38 | 2 | | 39 | 37 | | 40 | 24 | | 41 | 32 | | 42 | 4 | | 43 | 29 | | 44 | 15 | | 45 | 9 | | 46 | 5 | | 47 | 1 | | 48 | 6 | | 49 | 20 |
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| 85.48% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.532258064516129 | | totalSentences | 62 | | uniqueOpeners | 33 | |
| 65.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 51 | | matches | | 0 | "Somewhere beyond the dimming arch," |
| | ratio | 0.02 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 51 | | matches | | 0 | "He glanced left, then right," | | 1 | "She kept to the far" | | 2 | "He didn't turn." | | 3 | "He moved like a man" | | 4 | "He cut down Berwick Street," | | 5 | "She smiled, closing the gap." | | 6 | "Her voice bounced off wet" | | 7 | "She reached the grate and" | | 8 | "She thumbed the button anyway." | | 9 | "She looked up" | | 10 | "She holstered the radio and" | | 11 | "She went down." | | 12 | "She thought of Morris." | | 13 | "She stepped forward." | | 14 | "She stepped past the woman" |
| | ratio | 0.294 | |
| 97.25% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 37 | | totalSentences | 51 | | matches | | 0 | "Detective Harlow Quinn stood in" | | 1 | "The man came out at" | | 2 | "Quinn recognized him from the" | | 3 | "He glanced left, then right," | | 4 | "She kept to the far" | | 5 | "He didn't turn." | | 6 | "He moved like a man" | | 7 | "He cut down Berwick Street," | | 8 | "She smiled, closing the gap." | | 9 | "A grate sat propped open" | | 10 | "Her voice bounced off wet" | | 11 | "She reached the grate and" | | 12 | "Quinn's radio hissed static when" | | 13 | "She thumbed the button anyway." | | 14 | "She looked up" | | 15 | "The radio gave her nothing" | | 16 | "She holstered the radio and" | | 17 | "The beam caught brick, catching" | | 18 | "Every instinct from eighteen years" | | 19 | "The manual had never covered" |
| | ratio | 0.725 | |
| 98.04% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 51 | | matches | | | ratio | 0.02 | |
| 20.41% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 6 | | matches | | 0 | "Rain hammered the pavement outside the Raven's Nest, turning Soho's cobblestones into a black mirror that fractured the neon sign's green glow into a hundred cr…" | | 1 | "Quinn recognized him from the CCTV stills—tall, thin, moving with the jerky economy of someone who'd learned to walk without drawing attention." | | 2 | "She kept to the far side of the street, boots splashing through gutters swollen with runoff, her breath fogging in the cold." | | 3 | "Quinn's hand found her sidearm, thumb resting light against the safety, though every rational nerve in her screamed that a gun wouldn't matter here, not against…" | | 4 | "Thought of his flat, untouched for three years, thought of the case file marked unsolved that she still kept in her bottom drawer like a wound that wouldn't clo…" | | 5 | "Behind her, the stairwell up to the ordinary world sat open and waiting, an easy retreat into streets that made sense, into a precinct that would tell her she'd…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |