| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 23 | | tagDensity | 0.304 | | leniency | 0.609 | | rawRatio | 0.143 | | effectiveRatio | 0.087 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1193 | | 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) | |
| 66.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1193 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "glint" | | 1 | "predictable" | | 2 | "echo" | | 3 | "footsteps" | | 4 | "flickered" | | 5 | "electric" | | 6 | "could feel" |
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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 | 102 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 102 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 118 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1183 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 67.18% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 966 | | uniqueNames | 21 | | maxNameDensity | 1.66 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 16 | | Tomás | 13 | | Herrera | 3 | | Charing | 1 | | Cross | 1 | | Road | 1 | | Tube | 1 | | Northern | 1 | | Line | 1 | | Saint | 1 | | Christopher | 1 | | Transport | 1 | | Police | 1 | | Underground | 1 | | Camden | 1 | | Maglite | 1 | | Three | 1 | | Morris | 2 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Line" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Morris" |
| | places | | 0 | "Charing" | | 1 | "Cross" | | 2 | "Road" | | 3 | "Camden" | | 4 | "Three" |
| | globalScore | 0.672 | | windowScore | 0.833 | |
| 36.36% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like scales" | | 1 | "sounded like dice" | | 2 | "symbols that seemed to shift under her thumb" |
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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 | 1183 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 118 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 26.29 | | std | 18.62 | | cv | 0.708 | | sampleLengths | | 0 | 55 | | 1 | 11 | | 2 | 14 | | 3 | 53 | | 4 | 42 | | 5 | 26 | | 6 | 50 | | 7 | 4 | | 8 | 56 | | 9 | 4 | | 10 | 33 | | 11 | 6 | | 12 | 23 | | 13 | 7 | | 14 | 2 | | 15 | 6 | | 16 | 52 | | 17 | 47 | | 18 | 7 | | 19 | 50 | | 20 | 12 | | 21 | 1 | | 22 | 46 | | 23 | 6 | | 24 | 14 | | 25 | 7 | | 26 | 60 | | 27 | 18 | | 28 | 15 | | 29 | 12 | | 30 | 17 | | 31 | 18 | | 32 | 51 | | 33 | 34 | | 34 | 41 | | 35 | 4 | | 36 | 19 | | 37 | 25 | | 38 | 46 | | 39 | 41 | | 40 | 48 | | 41 | 45 | | 42 | 18 | | 43 | 29 | | 44 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 102 | | matches | | |
| 70.97% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 155 | | matches | | 0 | "was chasing" | | 1 | "was heading" | | 2 | "was already swinging" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 118 | | ratio | 0.059 | | matches | | 0 | "The man she was chasing—Tomás Herrera, former paramedic, current person of interest in three separate supernatural-related incidents—glanced over his shoulder and put on a burst of speed." | | 1 | "And there—Tomás Herrera, moving fast along the yellow line, heading for the tunnel mouth where the darkness swallowed the tracks." | | 2 | "Quinn’s training screamed at her—wait for backup, secure the scene, do not pursue into an active rail tunnel." | | 3 | "The air grew colder, thick with the mineral smell of old stone and something else—something sharp and herbal, like burnt sage." | | 4 | "Something flickered behind his eyes—recognition, maybe even sympathy." | | 5 | "Beyond it, Quinn saw stairs—old ironwork spiraling down into a warm, amber glow." | | 6 | "Quinn caught it reflexively—a bone token, carved with symbols that seemed to shift under her thumb." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 978 | | adjectiveStacks | 2 | | stackExamples | | 0 | "former paramedic, current person" | | 1 | "separate supernatural-related incidents—" |
| | adverbCount | 22 | | adverbRatio | 0.022494887525562373 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.00408997955010225 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 118 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 118 | | mean | 10.03 | | std | 7.33 | | cv | 0.731 | | sampleLengths | | 0 | 12 | | 1 | 16 | | 2 | 27 | | 3 | 11 | | 4 | 11 | | 5 | 3 | | 6 | 12 | | 7 | 16 | | 8 | 10 | | 9 | 15 | | 10 | 9 | | 11 | 5 | | 12 | 13 | | 13 | 15 | | 14 | 3 | | 15 | 4 | | 16 | 1 | | 17 | 2 | | 18 | 13 | | 19 | 3 | | 20 | 8 | | 21 | 20 | | 22 | 15 | | 23 | 7 | | 24 | 4 | | 25 | 12 | | 26 | 8 | | 27 | 10 | | 28 | 6 | | 29 | 20 | | 30 | 4 | | 31 | 5 | | 32 | 12 | | 33 | 3 | | 34 | 13 | | 35 | 6 | | 36 | 3 | | 37 | 17 | | 38 | 2 | | 39 | 1 | | 40 | 7 | | 41 | 2 | | 42 | 6 | | 43 | 18 | | 44 | 15 | | 45 | 13 | | 46 | 2 | | 47 | 4 | | 48 | 11 | | 49 | 8 |
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| 68.64% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4322033898305085 | | totalSentences | 118 | | uniqueOpeners | 51 | |
| 73.26% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 91 | | matches | | 0 | "Nowhere to run." | | 1 | "Maybe two minutes out." |
| | ratio | 0.022 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 91 | | matches | | 0 | "He moved well for someone" | | 1 | "They never stopped." | | 2 | "She hurdled the debris, her" | | 3 | "He was heading underground." | | 4 | "Her eyes swept the platform" | | 5 | "She hit the platform running." | | 6 | "His olive skin looked sallow" | | 7 | "He jumped down onto the" | | 8 | "She was already swinging herself" | | 9 | "She followed the sound of" | | 10 | "He touched the medallion at" | | 11 | "he said quietly" | | 12 | "She’d heard whispers." | | 13 | "Her superiors laughed it off." | | 14 | "She had seconds to decide." | | 15 | "He reached into his pocket" | | 16 | "She didn’t know which one" | | 17 | "She stepped through the door" |
| | ratio | 0.198 | |
| 47.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 91 | | matches | | 0 | "Detective Harlow Quinn’s lungs burned" | | 1 | "Rain lashed her face in" | | 2 | "The man she was chasing—Tomás" | | 3 | "He moved well for someone" | | 4 | "The words tore from her" | | 5 | "They never stopped." | | 6 | "Tomás ducked left into an" | | 7 | "Quinn followed without breaking stride," | | 8 | "A stack of pallets clattered" | | 9 | "She hurdled the debris, her" | | 10 | "The alley spat them out" | | 11 | "Traffic hissed through standing water." | | 12 | "A double-decker bus groaned past," | | 13 | "Tomás dodged between two cabs" | | 14 | "Quinn’s jaw tightened." | | 15 | "He was heading underground." | | 16 | "The Northern Line at this" | | 17 | "Tomás vaulted the gate with" | | 18 | "The Transport Police officer on" | | 19 | "Quinn flashed her warrant card" |
| | ratio | 0.824 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 74.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 4 | | matches | | 0 | "The Transport Police officer on duty shouted something that got lost in the station’s echo." | | 1 | "She was already swinging herself down after him, her shoes crunching on the gravel bed." | | 2 | "The beam cut a narrow path through the dark, illuminating rusted maintenance ladders, old posters plastered to the curved walls, a rat that skittered away from …" | | 3 | "A supernatural black market that moved locations every full moon, accessible only with the right token." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Quinn muttered (mutter)" |
| | dialogueSentences | 23 | | tagDensity | 0.13 | | leniency | 0.261 | | rawRatio | 0.333 | | effectiveRatio | 0.087 | |