| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.75 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.67% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 790 | | 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) | |
| 36.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 790 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "glinting" | | 1 | "determined" | | 2 | "loomed" | | 3 | "scanned" | | 4 | "otherworldly" | | 5 | "pounding" | | 6 | "etched" | | 7 | "flickered" | | 8 | "stomach" |
| |
| 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 |
|
| | highlights | | 0 | "The air was thick with" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 47 | | matches | | |
| 82.07% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 47 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 48 | | 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 | 795 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 776 | | uniqueNames | 15 | | maxNameDensity | 1.29 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 10 | | Quinn | 2 | | Soho | 1 | | Dean | 1 | | Street | 1 | | Raven | 2 | | Nest | 2 | | Silas | 2 | | Tomás | 5 | | Veil | 1 | | Market | 1 | | Tube | 1 | | Camden | 1 | | Morris | 1 | | Herrera | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Silas" | | 4 | "Tomás" | | 5 | "Market" | | 6 | "Camden" | | 7 | "Morris" | | 8 | "Herrera" |
| | places | | 0 | "Soho" | | 1 | "Dean" | | 2 | "Street" | | 3 | "Nest" |
| | globalScore | 0.856 | | windowScore | 0.833 | |
| 38.89% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like hours, and she was determined" | | 1 | "market that seemed to be a hub for the very people and things she was trying to investigate" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 795 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 48 | | matches | (empty) | |
| 37.25% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 15 | | mean | 53 | | std | 14.86 | | cv | 0.28 | | sampleLengths | | 0 | 63 | | 1 | 64 | | 2 | 56 | | 3 | 59 | | 4 | 14 | | 5 | 55 | | 6 | 33 | | 7 | 71 | | 8 | 47 | | 9 | 48 | | 10 | 44 | | 11 | 42 | | 12 | 66 | | 13 | 66 | | 14 | 67 |
| |
| 82.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 47 | | matches | | 0 | "was determined" | | 1 | "was left" | | 2 | "was headed" | | 3 | "was connected" |
| |
| 37.40% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 123 | | matches | | 0 | "was polishing" | | 1 | "was heading" | | 2 | "was trying" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 1 | | flaggedSentences | 4 | | totalSentences | 48 | | ratio | 0.083 | | matches | | 0 | "The bar's patrons – an assortment of shady-looking characters and regulars – turned to regard her with a mixture of curiosity and hostility." | | 1 | "But the streets above were a labyrinth; she'd never track him down again." | | 2 | "Wherever Tomás was headed, she had to assume it was connected to the strange occurrences plaguing the city – occurrences that bore an unsettling resemblance to the case that had claimed her partner's life." | | 3 | "This was it – the point of no return." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 776 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.023195876288659795 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006443298969072165 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 48 | | echoCount | 0 | | echoWords | (empty) | |
| 96.35% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 48 | | mean | 16.56 | | std | 6.47 | | cv | 0.391 | | sampleLengths | | 0 | 14 | | 1 | 20 | | 2 | 29 | | 3 | 21 | | 4 | 23 | | 5 | 20 | | 6 | 27 | | 7 | 15 | | 8 | 14 | | 9 | 23 | | 10 | 23 | | 11 | 13 | | 12 | 7 | | 13 | 7 | | 14 | 18 | | 15 | 14 | | 16 | 20 | | 17 | 3 | | 18 | 17 | | 19 | 16 | | 20 | 14 | | 21 | 13 | | 22 | 10 | | 23 | 34 | | 24 | 9 | | 25 | 21 | | 26 | 17 | | 27 | 15 | | 28 | 11 | | 29 | 11 | | 30 | 11 | | 31 | 12 | | 32 | 12 | | 33 | 20 | | 34 | 10 | | 35 | 16 | | 36 | 16 | | 37 | 15 | | 38 | 23 | | 39 | 28 | | 40 | 14 | | 41 | 19 | | 42 | 9 | | 43 | 24 | | 44 | 5 | | 45 | 17 | | 46 | 19 | | 47 | 26 |
| |
| 67.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4791666666666667 | | totalSentences | 48 | | uniqueOpeners | 23 | |
| 70.92% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 47 | | matches | | 0 | "Perhaps it was the memory" |
| | ratio | 0.021 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 6 | | totalSentences | 47 | | matches | | 0 | "She pumped her arms, her" | | 1 | "Her sharp jaw was set" | | 2 | "he growled, meeting her gaze" | | 3 | "She slipped through the doorway," | | 4 | "She descended into the unknown," | | 5 | "She found herself at the" |
| | ratio | 0.128 | |
| 77.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 36 | | totalSentences | 47 | | matches | | 0 | "Rain lashed down on the" | | 1 | "Detective Harlow Quinn sprinted through" | | 2 | "The suspect, a young man" | | 3 | "She pumped her arms, her" | | 4 | "Her sharp jaw was set" | | 5 | "The chase had been going" | | 6 | "The suspect vanished into the" | | 7 | "The warm, dimly lit interior" | | 8 | "The bar's patrons – an" | | 9 | "Harlow's eyes scanned the room," | | 10 | "The air was thick with" | | 11 | "the barkeep, Silas, bellowed after" | | 12 | "Harlow shouldered through the crowd," | | 13 | "A shelf-lined doorway, previously hidden" | | 14 | "The door creaked shut behind" | | 15 | "The hidden room." | | 16 | "A glance at Silas, who" | | 17 | "he growled, meeting her gaze" | | 18 | "Harlow's gut told her Tomás" | | 19 | "The possibilities sent a cold" |
| | ratio | 0.766 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 47 | | matches | | 0 | "Wherever Tomás was headed, she" | | 1 | "Yet, something compelled her forward." |
| | ratio | 0.043 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 4 | | matches | | 0 | "A glance at Silas, who was polishing a mug with a dirty rag, yielded no useful information." | | 1 | "Wherever Tomás was headed, she had to assume it was connected to the strange occurrences plaguing the city – occurrences that bore an unsettling resemblance to …" | | 2 | "The underground market that seemed to be a hub for the very people and things she was trying to investigate." | | 3 | "The sound of haggling and muted conversations created a constant hum, while figures darted between stalls, hawking wares that defied the laws of nature and the …" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "the barkeep Silas bellowed (bellow)" | | 1 | "he growled (growl)" |
| | dialogueSentences | 4 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |