| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 40 | | tagDensity | 0.55 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.88% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1349 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "sharply" |
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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) | |
| 51.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1349 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "shattered" | | 1 | "rhythmic" | | 2 | "pristine" | | 3 | "gloom" | | 4 | "weight" | | 5 | "furrowing" | | 6 | "traced" | | 7 | "etched" | | 8 | "intricate" | | 9 | "scanned" | | 10 | "echoed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 72 | | matches | (empty) | |
| 83.33% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 72 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 84 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 68 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1344 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 55.28% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 1003 | | uniqueNames | 13 | | maxNameDensity | 1.89 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Camden | 1 | | Metropolitan | 1 | | Police | 1 | | Victorian | 1 | | Harlow | 19 | | Quinn | 1 | | Inspector | 1 | | Miller | 9 | | Heavy | 1 | | London | 1 | | Morris | 2 | | Whitechapel | 1 | | Smooth | 1 |
| | persons | | 0 | "Police" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Inspector" | | 4 | "Miller" | | 5 | "Morris" | | 6 | "Whitechapel" |
| | places | | | globalScore | 0.553 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 1 | | matches | | 0 | "sigils that seemed to shift slightly when her light grazed them" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.232 | | wordCount | 1344 | | matches | | 0 | "not numbers, not decorative flourishes, but precise, sharp sigils" | | 1 | "not decorative flourishes, but precise, sharp sigils" | | 2 | "not a robbery, but a payment" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 84 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 30.55 | | std | 17.62 | | cv | 0.577 | | sampleLengths | | 0 | 45 | | 1 | 33 | | 2 | 17 | | 3 | 52 | | 4 | 30 | | 5 | 33 | | 6 | 44 | | 7 | 27 | | 8 | 2 | | 9 | 7 | | 10 | 50 | | 11 | 43 | | 12 | 46 | | 13 | 37 | | 14 | 44 | | 15 | 9 | | 16 | 69 | | 17 | 46 | | 18 | 43 | | 19 | 34 | | 20 | 9 | | 21 | 32 | | 22 | 35 | | 23 | 29 | | 24 | 7 | | 25 | 39 | | 26 | 20 | | 27 | 4 | | 28 | 14 | | 29 | 67 | | 30 | 30 | | 31 | 16 | | 32 | 42 | | 33 | 2 | | 34 | 44 | | 35 | 15 | | 36 | 23 | | 37 | 68 | | 38 | 15 | | 39 | 43 | | 40 | 19 | | 41 | 37 | | 42 | 15 | | 43 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 72 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 170 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 84 | | ratio | 0.071 | | matches | | 0 | "The air down here smelled of wet soot, copper, and something sharp—like ozone before a lightning strike." | | 1 | "A thick drop rested here, another two feet away, then a long, smears-and-droplets streak leading straight toward the solid brick wall behind them—not toward the tracks where the body was recovered." | | 2 | "\"If he tripped, where's the void in the spatter?\" Harlow stood up, her 5'9\" frame casting a tall shadow against the tunnel wall. \"If a human body stood between the spurting artery and this brick, there'd be a shadow—a blank spot on the wall where his torso blocked the blood." | | 3 | "Harlow knelt, using the tip of a pen from her coat pocket to nudge the object into the light. It was a small brass casing, no larger than an old pocket watch, heavily tarnished with a thick patina of verdigris. Etched across its face were intricate, interlocking angular lines—not numbers, not decorative flourishes, but precise, sharp sigils that seemed to shift slightly when her light grazed them." | | 4 | "Harlow stood up slowly, her mind piecing together the broken geometry of the scene. The blood on the wall without a body. The impossible exit route. The triangular tracks. The uncirculated notes left on the chest—not a robbery, but a payment. An entrance fee." | | 5 | "\"They call it the Veil Market,\" she murmured, the name slipping out before she could stop it—a word whispered in confiscated informant tapes she'd listened to until her ears bled. \"It moves every full moon." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 601 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 9 | | adverbRatio | 0.014975041597337771 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0033277870216306157 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 84 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 84 | | mean | 16 | | std | 12.68 | | cv | 0.793 | | sampleLengths | | 0 | 22 | | 1 | 23 | | 2 | 12 | | 3 | 4 | | 4 | 17 | | 5 | 17 | | 6 | 27 | | 7 | 18 | | 8 | 7 | | 9 | 10 | | 10 | 5 | | 11 | 15 | | 12 | 19 | | 13 | 14 | | 14 | 12 | | 15 | 32 | | 16 | 8 | | 17 | 15 | | 18 | 4 | | 19 | 2 | | 20 | 7 | | 21 | 30 | | 22 | 14 | | 23 | 6 | | 24 | 17 | | 25 | 26 | | 26 | 9 | | 27 | 6 | | 28 | 31 | | 29 | 6 | | 30 | 9 | | 31 | 22 | | 32 | 16 | | 33 | 28 | | 34 | 9 | | 35 | 50 | | 36 | 5 | | 37 | 10 | | 38 | 4 | | 39 | 15 | | 40 | 1 | | 41 | 6 | | 42 | 6 | | 43 | 18 | | 44 | 43 | | 45 | 26 | | 46 | 3 | | 47 | 5 | | 48 | 9 | | 49 | 11 |
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| 84.52% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5357142857142857 | | totalSentences | 84 | | uniqueOpeners | 45 | |
| 98.04% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 68 | | matches | | 0 | "Maybe the local ghosts got" | | 1 | "Then, the faint, distinct sound" |
| | ratio | 0.029 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 68 | | matches | | 0 | "She stepped over a tangle" | | 1 | "He clutched a lukewarm paper" | | 2 | "She surveyed the cavernous station." | | 3 | "She stared down at the" | | 4 | "Her brown eyes narrowed." | | 5 | "Her eyes tracked the blood" | | 6 | "She leaned closer to the" | | 7 | "It was inside" | | 8 | "You've been jumpy ever since" | | 9 | "She swept her flashlight beam" | | 10 | "She focused the beam on" | | 11 | "She kicked aside a pile" | | 12 | "She turned her beam back" | | 13 | "she murmured, the name slipping" | | 14 | "I'm taking your" |
| | ratio | 0.221 | |
| 55.59% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 68 | | matches | | 0 | "Rain filtered through the shattered" | | 1 | "Detective Harlow Quinn adjusted the" | | 2 | "The air down here smelled" | | 3 | "She stepped over a tangle" | | 4 | "Detective Inspector Miller stood beside" | | 5 | "He clutched a lukewarm paper" | | 6 | "Harlow stopped at the perimeter" | | 7 | "She surveyed the cavernous station." | | 8 | "Harlow snapped on a pair" | | 9 | "Miller gestured with his cup" | | 10 | "Harlow crouched at the edge" | | 11 | "She stared down at the" | | 12 | "Her brown eyes narrowed." | | 13 | "Harlow pointed her tactical flashlight" | | 14 | "Miller shifted his weight, his" | | 15 | "Harlow dropped into a kneel" | | 16 | "Her eyes tracked the blood" | | 17 | "A thick drop rested here," | | 18 | "She leaned closer to the" | | 19 | "The soot on the London" |
| | ratio | 0.809 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 60.44% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 3 | | matches | | 0 | "Someone had wiped a broad swath clean, five feet off the ground, leaving faint, oily residue that glistened purple under her flashlight." | | 1 | "She focused the beam on a cluster of small, sharp indentations pressed into the damp dust. They were triangular, spaced evenly, as if a tripod made of iron need…" | | 2 | "Harlow knelt, using the tip of a pen from her coat pocket to nudge the object into the light. It was a small brass casing, no larger than an old pocket watch, h…" |
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| 50.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 3 | | matches | | 0 | "Harlow said, her voice dropping an octave" | | 1 | "Miller warned, his tone losing its easy confidence" | | 2 | "Harlow said, her voice deadly quiet" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 9 | | fancyTags | | 0 | "Miller chuckled (chuckle)" | | 1 | "she noted (note)" | | 2 | "Miller insisted (insist)" | | 3 | "Miller warned (warn)" | | 4 | "Harlow whispered (whisper)" | | 5 | "Harlow continued (continue)" | | 6 | "The rift snapped (snap)" | | 7 | "she murmured (murmur)" | | 8 | "Miller barked (bark)" |
| | dialogueSentences | 40 | | tagDensity | 0.325 | | leniency | 0.65 | | rawRatio | 0.692 | | effectiveRatio | 0.45 | |