| 66.67% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 1 | | adverbTags | | 0 | "he replied vaguely [vaguely]" |
| | dialogueSentences | 15 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.167 | | effectiveRatio | 0.133 | |
| 90.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1622 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "very" |
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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) | |
| 32.18% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1622 | | totalAiIsms | 22 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | word | "the last thing" | | count | 1 |
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| | highlights | | 0 | "flickered" | | 1 | "rhythmic" | | 2 | "pulse" | | 3 | "reminder" | | 4 | "intensity" | | 5 | "silence" | | 6 | "footsteps" | | 7 | "navigating" | | 8 | "chaotic" | | 9 | "synchronized" | | 10 | "calculated" | | 11 | "scanning" | | 12 | "pulsed" | | 13 | "cacophony" | | 14 | "velvet" | | 15 | "weight" | | 16 | "chill" | | 17 | "glint" | | 18 | "the last thing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "the air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 106 | | matches | | |
| 35.04% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 7 | | narrationSentences | 106 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "started to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 115 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 10 | | totalWords | 1614 | | ratio | 0.006 | | matches | | 0 | "Request backup. Secure the perimeter. Do not enter unknown territory." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 1470 | | uniqueNames | 16 | | maxNameDensity | 0.82 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 12 | | Fifty | 1 | | London | 2 | | Morris | 3 | | Camden | 1 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Metropolitan | 1 | | Police | 1 | | Seville | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Police" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Tomás" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Market" | | 3 | "Seville" |
| | globalScore | 1 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 5 | | matches | | 0 | "staircases that seemed to lead nowhere" | | 1 | "shadows that seemed to move independently of their bodies" | | 2 | "parchment that seemed to writhe under the light of a tallow candle" | | 3 | "chanting that seemed to underpin the entire market" | | 4 | "sounded like bone hitting stone, and a low" | | 5 | "looked like they were built from salvaged" |
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| 76.08% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.239 | | wordCount | 1614 | | matches | | 0 | "not in a warehouse, but in a descending concrete stairwell" | | 1 | "not a weapon, but a key" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 115 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 39.37 | | std | 20.06 | | cv | 0.51 | | sampleLengths | | 0 | 70 | | 1 | 14 | | 2 | 52 | | 3 | 92 | | 4 | 3 | | 5 | 59 | | 6 | 49 | | 7 | 37 | | 8 | 44 | | 9 | 4 | | 10 | 40 | | 11 | 75 | | 12 | 52 | | 13 | 44 | | 14 | 76 | | 15 | 16 | | 16 | 68 | | 17 | 37 | | 18 | 36 | | 19 | 47 | | 20 | 35 | | 21 | 39 | | 22 | 55 | | 23 | 25 | | 24 | 11 | | 25 | 38 | | 26 | 8 | | 27 | 48 | | 28 | 11 | | 29 | 32 | | 30 | 30 | | 31 | 55 | | 32 | 45 | | 33 | 18 | | 34 | 30 | | 35 | 40 | | 36 | 48 | | 37 | 21 | | 38 | 27 | | 39 | 41 | | 40 | 42 |
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| 78.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 8 | | totalSentences | 106 | | matches | | 0 | "was replaced" | | 1 | "were scarred" | | 2 | "been hollowed" | | 3 | "was gone" | | 4 | "been reclaimed" | | 5 | "were draped" | | 6 | "were shrouded" | | 7 | "being watched" | | 8 | "were built" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 237 | | matches | | 0 | "was losing" | | 1 | "was navigating" | | 2 | "wasn't just running" | | 3 | "was standing" | | 4 | "were shaking" | | 5 | "was peddling" | | 6 | "were walking" | | 7 | "were dissolving" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 5 | | flaggedSentences | 12 | | totalSentences | 115 | | ratio | 0.104 | | matches | | 0 | "The rain in Soho didn't fall; it hammered." | | 1 | "She checked her watch—the worn leather strap felt heavy against her left wrist." | | 2 | "The walls here weren't brick; they were scarred, soot-stained concrete, weeping with condensation." | | 3 | "He wasn't just running; he was navigating." | | 4 | "She had heard the whispers in the precinct—rumors of an underground exchange that bypassed every law of man and physics." | | 5 | "Some were draped in heavy, tattered silks; others were shrouded in shadows that seemed to move independently of their bodies." | | 6 | "The sounds were a cacophony of languages—some melodic, some guttural, none quite human." | | 7 | "It was the same sensation she’d had the night Morris died—the feeling of being watched by something that didn't use eyes." | | 8 | "She rounded a corner of a spice stall—scents of cinnamon and something scorched—and nearly collided with a man standing in the shadow of a heavy velvet curtain." | | 9 | "The shadows here didn't behave; they stretched toward her, reaching out with long, spindly fingers." | | 10 | "He was something else entirely—something that belonged to the world Tomás had warned her about." | | 11 | "He stepped into the light, and for a split second, Quinn saw the glint of something metallic in his hand—not a weapon, but a key." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1484 | | adjectiveStacks | 1 | | stackExamples | | 0 | "short, curly dark hair." |
| | adverbCount | 29 | | adverbRatio | 0.01954177897574124 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.010107816711590296 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 115 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 115 | | mean | 14.03 | | std | 8.18 | | cv | 0.583 | | sampleLengths | | 0 | 8 | | 1 | 17 | | 2 | 22 | | 3 | 23 | | 4 | 14 | | 5 | 9 | | 6 | 13 | | 7 | 30 | | 8 | 13 | | 9 | 17 | | 10 | 11 | | 11 | 23 | | 12 | 28 | | 13 | 3 | | 14 | 5 | | 15 | 9 | | 16 | 17 | | 17 | 28 | | 18 | 15 | | 19 | 9 | | 20 | 25 | | 21 | 4 | | 22 | 20 | | 23 | 13 | | 24 | 3 | | 25 | 17 | | 26 | 7 | | 27 | 17 | | 28 | 4 | | 29 | 11 | | 30 | 10 | | 31 | 19 | | 32 | 19 | | 33 | 15 | | 34 | 17 | | 35 | 24 | | 36 | 5 | | 37 | 20 | | 38 | 27 | | 39 | 4 | | 40 | 20 | | 41 | 20 | | 42 | 7 | | 43 | 9 | | 44 | 2 | | 45 | 3 | | 46 | 17 | | 47 | 38 | | 48 | 6 | | 49 | 5 |
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| 34.78% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.3130434782608696 | | totalSentences | 115 | | uniqueOpeners | 36 | |
| 33.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 101 | | matches | | 0 | "Then, the tunnel opened." |
| | ratio | 0.01 | |
| 29.90% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 101 | | matches | | 0 | "It turned the neon glow" | | 1 | "She wiped a mixture of" | | 2 | "she hissed to herself, though" | | 3 | "She checked her watch—the worn" | | 4 | "Her boots slapped against the" | | 5 | "She ignored the protest of" | | 6 | "She tracked the flash of" | | 7 | "He turned left, diving toward" | | 8 | "She pushed through a heavy" | | 9 | "He wasn't just running; he" | | 10 | "He bypassed certain turns, opting" | | 11 | "She wasn't in a basement" | | 12 | "She was standing on a" | | 13 | "It was an abandoned Tube" | | 14 | "She had heard the whispers" | | 15 | "It was a place for" | | 16 | "He leaped over a low" | | 17 | "Her training screamed at her" | | 18 | "She looked down at her" | | 19 | "They were shaking, just slightly." |
| | ratio | 0.475 | |
| 34.26% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 86 | | totalSentences | 101 | | matches | | 0 | "The rain in Soho didn't" | | 1 | "It turned the neon glow" | | 2 | "Detective Harlow Quinn ducked under" | | 3 | "She wiped a mixture of" | | 4 | "she hissed to herself, though" | | 5 | "The suspect was fast, moving" | | 6 | "Every time Quinn thought she" | | 7 | "She checked her watch—the worn" | | 8 | "The ticking was a rhythmic" | | 9 | "The suspect bolted." | | 10 | "Quinn lunged into the pursuit." | | 11 | "Her boots slapped against the" | | 12 | "She ignored the protest of" | | 13 | "She tracked the flash of" | | 14 | "He turned left, diving toward" | | 15 | "Quinn followed, her hand instinctively" | | 16 | "She pushed through a heavy" | | 17 | "The air changed instantly." | | 18 | "The roar of the London" | | 19 | "The walls here weren't brick;" |
| | ratio | 0.851 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 101 | | matches | | 0 | "Now, she only had the" | | 1 | "If she called it in," | | 2 | "Before she could press him," |
| | ratio | 0.03 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 67 | | technicalSentenceCount | 14 | | matches | | 0 | "Every time Quinn thought she had a lock on the direction, the figure would bank a sharp corner, disappearing into the labyrinthine alleys that bled into the bel…" | | 1 | "She pushed through a heavy metal door, finding herself not in a warehouse, but in a descending concrete stairwell that spiraled deep into the earth." | | 2 | "The man was ahead of her, moving with a lightness that defied the steepness of the descent." | | 3 | "He bypassed certain turns, opting for narrow maintenance tunnels and jagged staircases that seemed to lead nowhere." | | 4 | "She was standing on a precipice overlooking a cavernous expanse that shouldn't have existed beneath the streets of Camden." | | 5 | "The architecture of the station had been reclaimed by things that didn't belong in a municipal blueprint." | | 6 | "He leaped over a low stone barrier, disappearing into a crowd of figures that moved with a strange, synchronized fluidity." | | 7 | "Next to it, a man with skin the color of bruised plums was peddling scraps of parchment that seemed to writhe under the light of a tallow candle." | | 8 | "There was the clink of coins that sounded like bone hitting stone, and a low, rhythmic chanting that seemed to underpin the entire market." | | 9 | "He wore a simple linen shirt, but his eyes, a warm brown, held a weary intelligence that felt far older than his twenty-nine years." | | 10 | "Before she could press him, the suspect surged past a nearby stall, ducking into a narrow alleyway between two structures that looked like they were built from …" | | 11 | "He simply stood there, silhouetted against the dim light of a hanging lantern, as if he had been waiting for her to arrive." | | 12 | "The man smiled, a slow, predatory expression that didn't reach his eyes." | | 13 | "The ground beneath her feet felt as though it were dissolving, and the last thing she saw before the darkness swallowed her was the green glow of a sign she cou…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "she started, but the words died in her throat" | | 1 | "she snapped, her jaw tightening" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 4 | | fancyTags | | 0 | "she hissed (hiss)" | | 1 | "she started (start)" | | 2 | "she snapped (snap)" | | 3 | "he corrected (correct)" |
| | dialogueSentences | 15 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.667 | | effectiveRatio | 0.533 | |