| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.31% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1355 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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 | 1355 | | totalAiIsms | 29 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | | | 23 | | | 24 | | | 25 | | | 26 | |
| | highlights | | 0 | "glistening" | | 1 | "fleeting" | | 2 | "rhythmic" | | 3 | "clandestine" | | 4 | "facade" | | 5 | "flickered" | | 6 | "reminder" | | 7 | "cascading" | | 8 | "chilled" | | 9 | "otherworldly" | | 10 | "navigated" | | 11 | "structure" | | 12 | "pulse" | | 13 | "quickened" | | 14 | "etched" | | 15 | "gloom" | | 16 | "calculating" | | 17 | "glint" | | 18 | "looming" | | 19 | "pulsed" | | 20 | "unravel" | | 21 | "weight" | | 22 | "tangible" | | 23 | "measured" | | 24 | "resolve" | | 25 | "familiar" | | 26 | "depths" |
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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 | 0 | | narrationSentences | 52 | | matches | (empty) | |
| 32.97% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 52 | | filterMatches | | | hedgeMatches | | 0 | "appeared to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 52 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1350 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 1347 | | uniqueNames | 14 | | maxNameDensity | 0.52 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Herrera" | | discoveredNames | | London | 1 | | Harlow | 1 | | Quinn | 7 | | Raven | 1 | | Nest | 2 | | Soho | 2 | | Morris | 2 | | Camden | 1 | | Tube | 1 | | Tomás | 1 | | Herrera | 4 | | Spanish-born | 1 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Tomás" | | 4 | "Herrera" | | 5 | "Saint" | | 6 | "Christopher" |
| | places | | 0 | "London" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Soho" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 1 | | matches | | 0 | "as though sensing an intrusion looming above, though he made no immediate move to retreat or confront" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1350 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 52 | | matches | | |
| 6.68% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 11 | | mean | 122.73 | | std | 21.28 | | cv | 0.173 | | sampleLengths | | 0 | 131 | | 1 | 129 | | 2 | 124 | | 3 | 120 | | 4 | 114 | | 5 | 91 | | 6 | 115 | | 7 | 164 | | 8 | 106 | | 9 | 157 | | 10 | 99 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 52 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 215 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 52 | | ratio | 0.096 | | matches | | 0 | "No rational explanation had ever emerged, only forensic anomalies that pointed to involvement beyond human understanding—witnesses who swore they saw impossible shadows or heard cries that twisted the air itself." | | 1 | "Quinn's pulse quickened as she realized the trajectory—no random flight, but a deliberate path toward the underground realm she had only glimpsed in rumors." | | 2 | "Recognition struck immediately from her accumulated dossiers—this was Tomás Herrera, the Spanish-born medic who had forfeited his practice after unauthorized interventions on behalf of the clique." | | 3 | "The market teemed with patrons in the background—suppliers of banned alchemical substances in slender vials that pulsed with inner light, dealers in whispered information that could unravel lives, and figures whose forms seemed to shift at the edges of perception." | | 4 | "Withdrawal at this stage preserved safety, allowed her to summon support and map the entrance properly before any pursuit, but it squandered the opportunity to seize tangible connections to the clique's activities—the meetings at the Nest, the treatments handled by men like Herrera, the leads that might explain why bodies continued to surface with inexplicable marks." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1357 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.023581429624170966 | | lyAdverbCount | 21 | | lyAdverbRatio | 0.015475313190862197 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 52 | | echoCount | 0 | | echoWords | (empty) | |
| 64.62% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 52 | | mean | 25.96 | | std | 8.09 | | cv | 0.312 | | sampleLengths | | 0 | 23 | | 1 | 25 | | 2 | 22 | | 3 | 33 | | 4 | 28 | | 5 | 18 | | 6 | 26 | | 7 | 15 | | 8 | 34 | | 9 | 36 | | 10 | 27 | | 11 | 30 | | 12 | 22 | | 13 | 21 | | 14 | 24 | | 15 | 15 | | 16 | 17 | | 17 | 19 | | 18 | 23 | | 19 | 22 | | 20 | 24 | | 21 | 39 | | 22 | 24 | | 23 | 27 | | 24 | 24 | | 25 | 16 | | 26 | 37 | | 27 | 18 | | 28 | 20 | | 29 | 16 | | 30 | 26 | | 31 | 26 | | 32 | 23 | | 33 | 24 | | 34 | 24 | | 35 | 22 | | 36 | 26 | | 37 | 23 | | 38 | 35 | | 39 | 34 | | 40 | 30 | | 41 | 40 | | 42 | 36 | | 43 | 18 | | 44 | 30 | | 45 | 56 | | 46 | 24 | | 47 | 29 | | 48 | 7 | | 49 | 22 |
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| 86.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.5192307692307693 | | totalSentences | 52 | | uniqueOpeners | 27 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 8 | | totalSentences | 52 | | matches | | 0 | "She had initiated the pursuit" | | 1 | "she commanded, projecting her voice" | | 2 | "Her muscles protested the sustained" | | 3 | "She passed shuttered markets and" | | 4 | "Her boots rang softly on" | | 5 | "Her finger brushed the grip" | | 6 | "She eased further down the" | | 7 | "She moved with measured steps" |
| | ratio | 0.154 | |
| 75.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 40 | | totalSentences | 52 | | matches | | 0 | "The rain fell in relentless" | | 1 | "Detective Harlow Quinn advanced through" | | 2 | "She had initiated the pursuit" | | 3 | "The green neon sign above" | | 4 | "she commanded, projecting her voice" | | 5 | "The suspect faltered briefly but" | | 6 | "Quinn responded by increasing her" | | 7 | "The worn leather watch secured" | | 8 | "This chase represented her latest" | | 9 | "The group appeared to orchestrate" | | 10 | "Determination surged through her veins," | | 11 | "The urban landscape shifted seamlessly" | | 12 | "Quinn navigated around clusters of" | | 13 | "The suspect's figure grew marginally" | | 14 | "Her muscles protested the sustained" | | 15 | "Rain blurred the edges of" | | 16 | "She passed shuttered markets and" | | 17 | "Details of the environment flooded" | | 18 | "These elements receded as the" | | 19 | "The structure rose from the" |
| | ratio | 0.769 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 13 | | matches | | 0 | "The suspect faltered briefly but regained speed, slipping between two idling vehicles and vanishing into a tight alley flanked by shuttered storefronts, their a…" | | 1 | "Quinn responded by increasing her pace, her form cutting through the elements with practiced efficiency." | | 2 | "No rational explanation had ever emerged, only forensic anomalies that pointed to involvement beyond human understanding—witnesses who swore they saw impossible…" | | 3 | "Determination surged through her veins, propelling her forward even as fatigue threatened to encroach, her military bearing keeping her posture rigid against th…" | | 4 | "With hurried motions, he withdrew a small bone token from an inner pocket and applied it to a designated spot on the wall, the object pale and etched with faint…" | | 5 | "The force of the entry jarred her frame, sending a sharp twinge through her shoulder, but she persisted, stepping across the threshold onto the initial landing." | | 6 | "Progressing downward, Quinn surveyed the scene with caution, her eyes adjusting to the dim, uneven lighting from lanterns strung along the old platform walls." | | 7 | "Recognition struck immediately from her accumulated dossiers—this was Tomás Herrera, the Spanish-born medic who had forfeited his practice after unauthorized in…" | | 8 | "Short curls of dark brown framed a face with olive skin toned by life's rigors, including the notable scar traversing his left forearm where the sleeve of his j…" | | 9 | "Herrera murmured something inaudible to the suspect, his gaze sweeping the stairwell briefly as though sensing an intrusion looming above, though he made no imm…" | | 10 | "The market teemed with patrons in the background—suppliers of banned alchemical substances in slender vials that pulsed with inner light, dealers in whispered i…" | | 11 | "Withdrawal at this stage preserved safety, allowed her to summon support and map the entrance properly before any pursuit, but it squandered the opportunity to …" | | 12 | "She moved with measured steps toward the platform, the sound of her approach masked by the ongoing bartering below, her mind fixed on the man ahead and the trut…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |