| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.11% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1259 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "suddenly" | | 1 | "slowly" | | 2 | "slightly" | | 3 | "really" |
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| 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) | |
| 28.51% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1259 | | totalAiIsms | 18 | | found | | 0 | | | 1 | | word | "practiced ease" | | count | 1 |
| | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | |
| | highlights | | 0 | "glint" | | 1 | "practiced ease" | | 2 | "echoing" | | 3 | "pounding" | | 4 | "standard" | | 5 | "rhythmic" | | 6 | "pulsed" | | 7 | "shimmered" | | 8 | "scanned" | | 9 | "flicker" | | 10 | "pulse" | | 11 | "flickered" | | 12 | "glinting" | | 13 | "jaw clenched" | | 14 | "vibrated" | | 15 | "silence" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "jaw clenched" | | 1 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 113 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 113 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 134 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 7 | | totalWords | 1240 | | ratio | 0.006 | | matches | | 0 | "Morris, D." | | 1 | "London" | | 2 | "under" | | 3 | "hunts" | | 4 | "taken" | | 5 | "own" |
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| 97.22% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 1 | | matches | | 0 | "Urban myth, they called it." |
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| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1004 | | uniqueNames | 10 | | maxNameDensity | 1.1 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Herrera" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 11 | | Morris | 3 | | Veil | 1 | | Market | 1 | | Bigfoot | 1 | | Herrera | 7 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" |
| | places | | | globalScore | 0.952 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | 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 | 1240 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 134 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 67 | | mean | 18.51 | | std | 16.95 | | cv | 0.916 | | sampleLengths | | 0 | 77 | | 1 | 38 | | 2 | 53 | | 3 | 48 | | 4 | 8 | | 5 | 36 | | 6 | 33 | | 7 | 13 | | 8 | 7 | | 9 | 51 | | 10 | 28 | | 11 | 8 | | 12 | 19 | | 13 | 3 | | 14 | 60 | | 15 | 3 | | 16 | 39 | | 17 | 12 | | 18 | 46 | | 19 | 1 | | 20 | 29 | | 21 | 15 | | 22 | 15 | | 23 | 49 | | 24 | 3 | | 25 | 2 | | 26 | 29 | | 27 | 20 | | 28 | 5 | | 29 | 29 | | 30 | 2 | | 31 | 6 | | 32 | 4 | | 33 | 21 | | 34 | 5 | | 35 | 37 | | 36 | 29 | | 37 | 16 | | 38 | 10 | | 39 | 15 | | 40 | 33 | | 41 | 8 | | 42 | 15 | | 43 | 7 | | 44 | 8 | | 45 | 24 | | 46 | 12 | | 47 | 10 | | 48 | 12 | | 49 | 1 |
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| 95.95% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 113 | | matches | | 0 | "being played" | | 1 | "were drawn" | | 2 | "been made" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 179 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 0 | | flaggedSentences | 14 | | totalSentences | 134 | | ratio | 0.104 | | matches | | 0 | "Ahead, a shadow darted between two narrow alleys—just a flash of dark fabric, a glint of damp hair." | | 1 | "The suspect—hood up, shoulders hunched—leapt over a fire escape’s lowered ladder and vanished into a gap between two buildings." | | 2 | "Faint, rhythmic music pulsed up from below—something with deep drums, no lyrics, no melody she could place." | | 3 | "The ladder ended in a tunnel—brick arched overhead, damp and crumbling in places, lit sporadically by gas sconces encased in iron cages." | | 4 | "The air was thick with the smell of incense and something sharper—ozone, maybe, or old blood." | | 5 | "The tunnel opened into a wide chamber, and suddenly—light." | | 6 | "But here it was—real, breathing, humming with a current that made the back of her neck prickle." | | 7 | "A stall to her right sold teeth—human, animal, others she couldn’t name—strung on twine and labeled in a script that shifted when she looked directly at it." | | 8 | "The vendor—an old woman wrapped in shawls of crow feathers—hissed, “Touch and pay.”" | | 9 | "Movement near the far end of the market—one stall draped in black cloth, no signage, just a single candle burning beneath a raven feather nailed to the wall." | | 10 | "Expunged file from NHS disciplinary board—unauthorized procedures, experimental treatments, patients discharged with healed wounds but blank memories." | | 11 | "Her watch flickered—hands jerking backward, then forward again." | | 12 | "He said something to the suspect—who bolted—and then turned, pushing through a curtain of beads into a back tunnel." | | 13 | "A scar ran the length of his left forearm—deep, jagged, like it had been made by something with teeth." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1025 | | adjectiveStacks | 1 | | stackExamples | | 0 | "ahead, moving fast, turning" |
| | adverbCount | 34 | | adverbRatio | 0.033170731707317075 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.010731707317073172 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 134 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 134 | | mean | 9.25 | | std | 6.72 | | cv | 0.726 | | sampleLengths | | 0 | 15 | | 1 | 17 | | 2 | 13 | | 3 | 18 | | 4 | 14 | | 5 | 5 | | 6 | 2 | | 7 | 31 | | 8 | 11 | | 9 | 19 | | 10 | 10 | | 11 | 2 | | 12 | 11 | | 13 | 14 | | 14 | 14 | | 15 | 20 | | 16 | 2 | | 17 | 6 | | 18 | 7 | | 19 | 6 | | 20 | 17 | | 21 | 2 | | 22 | 4 | | 23 | 12 | | 24 | 5 | | 25 | 8 | | 26 | 8 | | 27 | 7 | | 28 | 6 | | 29 | 7 | | 30 | 22 | | 31 | 16 | | 32 | 13 | | 33 | 10 | | 34 | 14 | | 35 | 4 | | 36 | 2 | | 37 | 6 | | 38 | 10 | | 39 | 9 | | 40 | 3 | | 41 | 4 | | 42 | 6 | | 43 | 14 | | 44 | 16 | | 45 | 20 | | 46 | 3 | | 47 | 4 | | 48 | 5 | | 49 | 13 |
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| 63.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.41044776119402987 | | totalSentences | 134 | | uniqueOpeners | 55 | |
| 34.01% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 98 | | matches | | 0 | "Instead, he reached into his" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 98 | | matches | | 0 | "Her trench coat clung to" | | 1 | "She rounded the corner, heart" | | 2 | "She skidded on wet stone," | | 3 | "She stepped forward, crouched, and" | | 4 | "Her left wrist itched beneath" | | 5 | "She took a breath and" | | 6 | "she called, voice echoing oddly" | | 7 | "She ran, boots splashing through" | | 8 | "She’d only heard whispers." | | 9 | "Her eyes scanned the crowd." | | 10 | "She saw one that read" | | 11 | "She reached for it." | | 12 | "Her pulse spiked." | | 13 | "She knew the name." | | 14 | "She moved forward, shoulder brushing" | | 15 | "Her watch flickered—hands jerking backward," | | 16 | "Their eyes met across the" | | 17 | "He didn’t look surprised." | | 18 | "He said something to the" | | 19 | "he said, voice calm" |
| | ratio | 0.255 | |
| 62.04% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 98 | | matches | | 0 | "Rain fell in diagonal sheets," | | 1 | "Detective Harlow Quinn vaulted over" | | 2 | "Her trench coat clung to" | | 3 | "The figure moved with practiced" | | 4 | "Quinn didn’t believe in coincidences." | | 5 | "She rounded the corner, heart" | | 6 | "The suspect—hood up, shoulders hunched—leapt" | | 7 | "Quinn followed, fingers brushing the" | | 8 | "The alley narrowed, walls slick" | | 9 | "She skidded on wet stone," | | 10 | "The opening gaped like a" | | 11 | "She stepped forward, crouched, and" | | 12 | "A narrow ladder disappeared into" | | 13 | "Her left wrist itched beneath" | | 14 | "This was one she wasn’t" | | 15 | "She took a breath and" | | 16 | "The ladder ended in a" | | 17 | "The air was thick with" | | 18 | "The suspect was already ahead," | | 19 | "Quinn kept her back to" |
| | ratio | 0.796 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 98 | | matches | (empty) | | ratio | 0 | |
| 93.02% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 3 | | matches | | 0 | "A man in a moth-eaten tailcoat weighed vials of liquid that shimmered like oil on water." | | 1 | "Cages hung from the ceiling, some empty, others holding small creatures that clicked their mandibles in rhythm with the drumbeat." | | 2 | "But here it was—real, breathing, humming with a current that made the back of her neck prickle." |
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| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | 0 | "an old woman wrapped (wrap)" |
| | dialogueSentences | 27 | | tagDensity | 0.185 | | leniency | 0.37 | | rawRatio | 0.2 | | effectiveRatio | 0.074 | |