| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 3 | | adverbTags | | 0 | "she acknowledged grudgingly [grudgingly]" | | 1 | "Herrera grinned wryly [wryly]" | | 2 | "she replied softly [softly]" |
| | dialogueSentences | 12 | | tagDensity | 0.833 | | leniency | 1 | | rawRatio | 0.3 | | effectiveRatio | 0.3 | |
| 70.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1013 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "sharply" | | 1 | "coyly" | | 2 | "softly" | | 3 | "inexorably" |
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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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1013 | | totalAiIsms | 26 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | |
| | highlights | | 0 | "cacophony" | | 1 | "fleeting" | | 2 | "electric" | | 3 | "navigated" | | 4 | "dance" | | 5 | "resolve" | | 6 | "determined" | | 7 | "familiar" | | 8 | "intrigue" | | 9 | "pulse" | | 10 | "anticipation" | | 11 | "quickened" | | 12 | "weight" | | 13 | "silence" | | 14 | "depths" | | 15 | "warmth" | | 16 | "chill" | | 17 | "potential" | | 18 | "quivered" | | 19 | "trepidation" | | 20 | "echoing" | | 21 | "footsteps" | | 22 | "wavered" |
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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 | 64 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 64 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 67 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 989 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 942 | | uniqueNames | 16 | | maxNameDensity | 0.74 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Harlow | 7 | | Quinn | 4 | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Veil | 2 | | Market | 2 | | Camden | 1 | | Tube | 1 | | Morris | 1 | | Tomás | 1 | | Herrera | 5 | | Trust | 1 | | Saint | 1 | | Christopher | 1 | | Choice | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Market" | | 4 | "Morris" | | 5 | "Tomás" | | 6 | "Herrera" | | 7 | "Saint" | | 8 | "Christopher" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 989 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 70.90% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 39.56 | | std | 15.75 | | cv | 0.398 | | sampleLengths | | 0 | 59 | | 1 | 60 | | 2 | 39 | | 3 | 47 | | 4 | 43 | | 5 | 48 | | 6 | 54 | | 7 | 51 | | 8 | 56 | | 9 | 73 | | 10 | 45 | | 11 | 52 | | 12 | 21 | | 13 | 35 | | 14 | 23 | | 15 | 26 | | 16 | 11 | | 17 | 18 | | 18 | 40 | | 19 | 17 | | 20 | 32 | | 21 | 35 | | 22 | 47 | | 23 | 42 | | 24 | 15 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 64 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 160 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 1 | | flaggedSentences | 18 | | totalSentences | 67 | | ratio | 0.269 | | matches | | 0 | "Brown eyes tracked the fleeting silhouette—that unwelcome glimpse of a man slipping through pedestrian chaos like a shadow against the neon congealing into pools of electric light." | | 1 | "Ahead, the suspect turned sharply, ducking into an alley—a vestibule of shadows where street lamps feared to tread." | | 2 | "Her quarry, a lean man clad in a nondescript hoodie, dared a glance back, eyes meeting hers briefly—a challenge, perhaps even desperation." | | 3 | "The alley tapered, steel grates beneath her boots announcing her arrival with a clang—and then the shadows broke, spilling her into a junction in front of The Raven's Nest." | | 4 | "She shook the drops from her hair, focusing on the figure ahead—a momentary hesitation, caught between familiar territory and a sudden pursuit underground." | | 5 | "Her suspect dashed across the road, fleeing down a set of basement steps, towards the veil of myth and intrigue: The Veil Market—the underground labyrinth of Camden, beneath the abandoned Tube station." | | 6 | "A pulse of anticipation quickened her heartbeat; the chase took her beyond these haunted streets: into realms where reality and supernatural danced coyly, menacingly." | | 7 | "She knew well enough—one bone token marked entry here." | | 8 | "Instinct dictated pursuit, drove her into darkness too familiar from the loss that still haunted her—the unexplained disappearance of DS Morris three years past." | | 9 | "She paused at a shape shifting in the depths—a figure bowed over a heavy metal door." | | 10 | "\"Quinn!\" a voice—Tomás Herrera's—came unbidden with an edge of incredulity, met her in the obscurity." | | 11 | "Her question cut sharply through atmosphere, tangling with their shared past—their shared tragedies and intermittent truths." | | 12 | "She pushed forward, bravado hiding fear—as authority of uniform often does." | | 13 | "Her hesitation there—significant moment threading stories dark, decisions each treadmill in pursuit often creates." | | 14 | "Harlow's step took her past Herrera, despite warnings crimson with consequence—despite internal struggles soft with whispered breath of hollow victories, hesitant defeats." | | 15 | "The homeless, the lost—each secret carried beneath echoing arches illuminated uniquely, fearing known." | | 16 | "Into the realm of black market secrets and forbidden exchanges, footsteps fell like scattered whispers—a place bearing geography tied inexorably to parts of her unknown." | | 17 | "The tunnel transformed in its approach—a black canvas of tarpaulins, marketplace narratives written against bricks as copper stung nostrils." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 374 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 9 | | adverbRatio | 0.02406417112299465 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.013368983957219251 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 67 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 67 | | mean | 14.76 | | std | 7.08 | | cv | 0.48 | | sampleLengths | | 0 | 21 | | 1 | 11 | | 2 | 27 | | 3 | 6 | | 4 | 27 | | 5 | 27 | | 6 | 18 | | 7 | 21 | | 8 | 18 | | 9 | 29 | | 10 | 12 | | 11 | 13 | | 12 | 13 | | 13 | 5 | | 14 | 22 | | 15 | 3 | | 16 | 5 | | 17 | 7 | | 18 | 11 | | 19 | 29 | | 20 | 12 | | 21 | 13 | | 22 | 19 | | 23 | 9 | | 24 | 23 | | 25 | 32 | | 26 | 24 | | 27 | 12 | | 28 | 9 | | 29 | 9 | | 30 | 4 | | 31 | 24 | | 32 | 15 | | 33 | 16 | | 34 | 13 | | 35 | 16 | | 36 | 15 | | 37 | 20 | | 38 | 17 | | 39 | 9 | | 40 | 9 | | 41 | 3 | | 42 | 16 | | 43 | 16 | | 44 | 3 | | 45 | 12 | | 46 | 11 | | 47 | 14 | | 48 | 12 | | 49 | 11 |
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| 97.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.582089552238806 | | totalSentences | 67 | | uniqueOpeners | 39 | |
| 52.91% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 63 | | matches | | 0 | "Too many criminals had her" |
| | ratio | 0.016 | |
| 93.02% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 63 | | matches | | 0 | "Her breath misted, mingling with" | | 1 | "She navigated puddles with precision," | | 2 | "Her quarry was fast, but" | | 3 | "Her quarry, a lean man" | | 4 | "It was enough." | | 5 | "She risked her career on" | | 6 | "She happened upon the distinct" | | 7 | "She shook the drops from" | | 8 | "Her suspect dashed across the" | | 9 | "She reached the steps, each" | | 10 | "She knew well enough—one bone" | | 11 | "She paused at a shape" | | 12 | "she acknowledged grudgingly, protections rising" | | 13 | "Her question cut sharply through" | | 14 | "She pushed forward, bravado hiding" | | 15 | "He motioned towards the steps" | | 16 | "she replied softly, anger tempered" | | 17 | "It lingered inevitable within her:" | | 18 | "Her hesitation there—significant moment threading" | | 19 | "Her descent into The Veil" |
| | ratio | 0.317 | |
| 55.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 51 | | totalSentences | 63 | | matches | | 0 | "Detective Harlow Quinn's voice cut" | | 1 | "Her breath misted, mingling with" | | 2 | "Brown eyes tracked the fleeting" | | 3 | "Pavements were slick beneath her" | | 4 | "She navigated puddles with precision," | | 5 | "Her quarry was fast, but" | | 6 | "Quinn only grimaced, the reflection" | | 7 | "Harlow adjusted her path, not" | | 8 | "The alley funnelled her towards" | | 9 | "Every fibre in her body" | | 10 | "Her quarry, a lean man" | | 11 | "It was enough." | | 12 | "The connection fed Harlow's fire." | | 13 | "She risked her career on" | | 14 | "The alley tapered, steel grates" | | 15 | "Vehicles grumbled by, oblivious to" | | 16 | "She happened upon the distinct" | | 17 | "Quinn paused, swept the street" | | 18 | "The city, rain-streaked and volatile," | | 19 | "She shook the drops from" |
| | ratio | 0.81 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 2 | | matches | | 0 | "She navigated puddles with precision, military-honed legs propelling her forward, dodging umbrellas in a dance as complicated as any covert operation she'd run …" | | 1 | "The alley tapered, steel grates beneath her boots announcing her arrival with a clang—and then the shadows broke, spilling her into a junction in front of The R…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 3 | | matches | | 0 | "called a voice from a passing taxi, tyres spraying her ankles with muddy water" | | 1 | "she acknowledged grudgingly, protections rising like tidal defences" | | 2 | "Herrera grinned wryly, hands shifting over the Saint Christopher medallion" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "soaked air her shout (air shout)" | | 1 | "she acknowledged grudgingly (acknowledge)" |
| | dialogueSentences | 12 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.5 | | effectiveRatio | 0.333 | |