| 42.11% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 3 | | adverbTags | | 0 | "Harlow said softly [softly]" | | 1 | "the taller woman warned softly [softly]" | | 2 | "Harlow repeated flatly [flatly]" |
| | dialogueSentences | 38 | | tagDensity | 0.421 | | leniency | 0.842 | | rawRatio | 0.188 | | effectiveRatio | 0.158 | |
| 81.13% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1325 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "completely" | | 1 | "softly" | | 2 | "nervously" |
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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) | |
| 58.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1325 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "shattered" | | 1 | "traced" | | 2 | "gloom" | | 3 | "weight" | | 4 | "throb" | | 5 | "magnetic" | | 6 | "chill" | | 7 | "scanned" | | 8 | "pristine" | | 9 | "calculating" |
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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 | 1 | | narrationSentences | 77 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 77 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 99 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1319 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 61.24% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1014 | | uniqueNames | 13 | | maxNameDensity | 1.78 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 18 | | Quinn | 1 | | Morris | 3 | | Miller | 8 | | Camden | 1 | | Vance | 2 | | Victorian | 1 | | Thames | 1 | | Metropolitan | 1 | | Police | 1 | | Two | 1 | | Oxford-style | 1 | | Eva | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Miller" | | 4 | "Vance" | | 5 | "Police" | | 6 | "Two" | | 7 | "Eva" |
| | places | | | globalScore | 0.612 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.758 | | wordCount | 1319 | | matches | | 0 | "not cardinal directions, but interlocking, sharp geometric sigils" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 99 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 28.67 | | std | 18 | | cv | 0.628 | | sampleLengths | | 0 | 31 | | 1 | 46 | | 2 | 9 | | 3 | 3 | | 4 | 36 | | 5 | 17 | | 6 | 35 | | 7 | 49 | | 8 | 41 | | 9 | 13 | | 10 | 32 | | 11 | 5 | | 12 | 8 | | 13 | 40 | | 14 | 51 | | 15 | 12 | | 16 | 69 | | 17 | 14 | | 18 | 29 | | 19 | 13 | | 20 | 29 | | 21 | 41 | | 22 | 6 | | 23 | 44 | | 24 | 24 | | 25 | 16 | | 26 | 7 | | 27 | 63 | | 28 | 9 | | 29 | 12 | | 30 | 37 | | 31 | 15 | | 32 | 77 | | 33 | 12 | | 34 | 8 | | 35 | 60 | | 36 | 26 | | 37 | 37 | | 38 | 20 | | 39 | 16 | | 40 | 38 | | 41 | 30 | | 42 | 32 | | 43 | 49 | | 44 | 26 | | 45 | 32 |
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| 87.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 77 | | matches | | 0 | "was frozen" | | 1 | "were carved" | | 2 | "being towed" | | 3 | "was signed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 174 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 99 | | ratio | 0.061 | | matches | | 0 | "He wore a tailored charcoal overcoat—cashmere, high-end, completely out of place against the sewage-stained walls of an abandoned subterranean passage." | | 1 | "Strange, razor-thin lines were carved into the glass face—not cardinal directions, but interlocking, sharp geometric sigils that made her temples throb if she stared too long." | | 2 | "One set belonged to Vance—broad, leather-soled shoes, scuffed, panicking, skidding toward the exit." | | 3 | "A faint, acrid smell hovered in the air—like sulfur, dried lavender, and burnt hair." | | 4 | "It bore an engraving—a stylized eye half-blinded by three vertical slashes." | | 5 | "She recognized the academic type—the satchel, the Oxford-style leather shoes caked in subterranean dirt, the smell of old paper and ink that clung to them despite the damp air of the tunnel." |
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| 82.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1032 | | adjectiveStacks | 3 | | stackExamples | | 0 | "Strange, razor-thin lines" | | 1 | "broad, leather-soled shoes," | | 2 | "thick, leather-bound books" |
| | adverbCount | 24 | | adverbRatio | 0.023255813953488372 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.013565891472868217 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 99 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 99 | | mean | 13.32 | | std | 7.52 | | cv | 0.565 | | sampleLengths | | 0 | 16 | | 1 | 15 | | 2 | 13 | | 3 | 11 | | 4 | 22 | | 5 | 9 | | 6 | 3 | | 7 | 17 | | 8 | 19 | | 9 | 6 | | 10 | 11 | | 11 | 13 | | 12 | 22 | | 13 | 5 | | 14 | 24 | | 15 | 20 | | 16 | 10 | | 17 | 31 | | 18 | 9 | | 19 | 4 | | 20 | 5 | | 21 | 27 | | 22 | 5 | | 23 | 4 | | 24 | 4 | | 25 | 10 | | 26 | 30 | | 27 | 6 | | 28 | 20 | | 29 | 25 | | 30 | 12 | | 31 | 18 | | 32 | 26 | | 33 | 5 | | 34 | 20 | | 35 | 7 | | 36 | 7 | | 37 | 6 | | 38 | 10 | | 39 | 9 | | 40 | 4 | | 41 | 13 | | 42 | 25 | | 43 | 4 | | 44 | 16 | | 45 | 12 | | 46 | 13 | | 47 | 6 | | 48 | 17 | | 49 | 8 |
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| 80.47% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.494949494949495 | | totalSentences | 99 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 76 | | matches | | 0 | "Her left thumb traced the" | | 1 | "She shone her torch down" | | 2 | "He wore a tailored charcoal" | | 3 | "She tilted the beam down." | | 4 | "She flipped the dead man's" | | 5 | "It was a small brass" | | 6 | "It twitched erratically, snapping hard" | | 7 | "She stood up, her joints" | | 8 | "Her sharp jaw tightened as" | | 9 | "She raised the beam." | | 10 | "It wasn't spray paint." | | 11 | "She crouched near a puddle" | | 12 | "It bore an engraving—a stylized" | | 13 | "She had seen bone like" | | 14 | "She pulled her satchel close," | | 15 | "Her boots clicked heavily on" | | 16 | "She recognized the academic type—the" | | 17 | "She pulled the brass compass" | | 18 | "Her green eyes darted from" |
| | ratio | 0.25 | |
| 65.26% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 76 | | matches | | 0 | "The cold air in the" | | 1 | "Detective Harlow Quinn stepped over" | | 2 | "Her left thumb traced the" | | 3 | "She shone her torch down" | | 4 | "Constable Miller stood near the" | | 5 | "A yellow tape line spanned" | | 6 | "Harlow ducked under the plastic" | | 7 | "Miller gestured toward a mound" | | 8 | "Harlow knelt beside the body." | | 9 | "The man lay curled on" | | 10 | "He wore a tailored charcoal" | | 11 | "Miller said, tapping his notepad" | | 12 | "Harlow snapped on a fresh" | | 13 | "She tilted the beam down." | | 14 | "Vance’s face was frozen in" | | 15 | "Miller bent closer, squinting." | | 16 | "Harlow pointed her torch at" | | 17 | "She flipped the dead man's" | | 18 | "The inner pocket gaped open," | | 19 | "Harlow reached into the dead" |
| | ratio | 0.789 | |
| 65.79% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 76 | | matches | | 0 | "Yet, directly beneath the tear," |
| | ratio | 0.013 | |
| 74.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 4 | | matches | | 0 | "Vance’s face was frozen in a mask of sheer, unadulterated terror, his mouth stretched wide, eyes glassy, pupils dilated into massive black abysses that caught n…" | | 1 | "Strange, razor-thin lines were carved into the glass face—not cardinal directions, but interlocking, sharp geometric sigils that made her temples throb if she s…" | | 2 | "Red hair curled wildly around her face, framing round glasses that reflected the harsh flashlights." | | 3 | "Beside her walked a taller woman with a sharp, calculating air, her gaze sweeping the vaulted ceiling before ever dropping to the body on the ground." |
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| 93.75% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 1 | | matches | | 0 | "Miller offered, though his voice lacked conviction" |
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| 18.42% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 5 | | fancyTags | | 0 | "Miller guessed (guess)" | | 1 | "Harlow called out (call out)" | | 2 | "the taller woman warned softly (warn)" | | 3 | "Harlow repeated flatly (repeat)" | | 4 | "Harlow stated (state)" |
| | dialogueSentences | 38 | | tagDensity | 0.289 | | leniency | 0.579 | | rawRatio | 0.455 | | effectiveRatio | 0.263 | |