| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 85.99% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1071 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "really" |
| |
| 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) | |
| 29.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1071 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "perfect" | | 1 | "pulse" | | 2 | "echoed" | | 3 | "weight" | | 4 | "charged" | | 5 | "etched" | | 6 | "scanned" | | 7 | "pulsed" | | 8 | "rhythmic" | | 9 | "structure" | | 10 | "could feel" | | 11 | "resonated" | | 12 | "silence" |
| |
| 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 | 154 | | matches | | |
| 87.20% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 5 | | hedgeCount | 1 | | narrationSentences | 154 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 154 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 20 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1071 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 4 | | matches | | 0 | "Overdose, he said." | | 1 | "What is that, Miller asked." | | 2 | "The Market is open, she said." | | 3 | "You know, she said." |
| |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 57 | | wordCount | 1071 | | uniqueNames | 9 | | maxNameDensity | 1.87 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 20 | | Miller | 17 | | Camden | 1 | | Town | 1 | | Market | 3 | | Veil | 2 | | Morris | 3 | | Quinn | 1 | | You | 9 |
| | persons | | 0 | "Harlow" | | 1 | "Miller" | | 2 | "Morris" | | 3 | "Quinn" | | 4 | "You" |
| | places | | | globalScore | 0.566 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like grinding stones" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.934 | | wordCount | 1071 | | matches | | 0 | "not at the body, but down the tunnel, deeper into the dark" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 154 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 65 | | mean | 16.48 | | std | 15.73 | | cv | 0.954 | | sampleLengths | | 0 | 63 | | 1 | 22 | | 2 | 8 | | 3 | 33 | | 4 | 5 | | 5 | 8 | | 6 | 45 | | 7 | 7 | | 8 | 7 | | 9 | 6 | | 10 | 23 | | 11 | 68 | | 12 | 13 | | 13 | 5 | | 14 | 2 | | 15 | 2 | | 16 | 1 | | 17 | 13 | | 18 | 6 | | 19 | 11 | | 20 | 48 | | 21 | 5 | | 22 | 8 | | 23 | 3 | | 24 | 15 | | 25 | 41 | | 26 | 6 | | 27 | 4 | | 28 | 8 | | 29 | 2 | | 30 | 34 | | 31 | 10 | | 32 | 8 | | 33 | 26 | | 34 | 8 | | 35 | 28 | | 36 | 7 | | 37 | 6 | | 38 | 17 | | 39 | 35 | | 40 | 4 | | 41 | 10 | | 42 | 5 | | 43 | 7 | | 44 | 25 | | 45 | 9 | | 46 | 12 | | 47 | 40 | | 48 | 9 | | 49 | 47 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 154 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 207 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 154 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1071 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.026143790849673203 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004668534080298786 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 154 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 154 | | mean | 6.95 | | std | 4.35 | | cv | 0.626 | | sampleLengths | | 0 | 18 | | 1 | 14 | | 2 | 18 | | 3 | 13 | | 4 | 15 | | 5 | 7 | | 6 | 3 | | 7 | 5 | | 8 | 3 | | 9 | 20 | | 10 | 3 | | 11 | 7 | | 12 | 5 | | 13 | 4 | | 14 | 2 | | 15 | 1 | | 16 | 1 | | 17 | 3 | | 18 | 14 | | 19 | 9 | | 20 | 5 | | 21 | 14 | | 22 | 7 | | 23 | 3 | | 24 | 4 | | 25 | 6 | | 26 | 13 | | 27 | 3 | | 28 | 7 | | 29 | 6 | | 30 | 15 | | 31 | 17 | | 32 | 12 | | 33 | 18 | | 34 | 5 | | 35 | 8 | | 36 | 5 | | 37 | 2 | | 38 | 2 | | 39 | 1 | | 40 | 6 | | 41 | 7 | | 42 | 6 | | 43 | 11 | | 44 | 6 | | 45 | 14 | | 46 | 5 | | 47 | 9 | | 48 | 5 | | 49 | 9 |
| |
| 37.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.2662337662337662 | | totalSentences | 154 | | uniqueOpeners | 41 | |
| 71.43% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 140 | | matches | | 0 | "Maybe a fall." | | 1 | "Just like this one." | | 2 | "Then why are you shaking?" |
| | ratio | 0.021 | |
| 57.14% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 57 | | totalSentences | 140 | | matches | | 0 | "She stepped over the prone" | | 1 | "It sat there, a perfect," | | 2 | "He held a clipboard like" | | 3 | "She crouched beside the body," | | 4 | "He leaned in, squinting." | | 5 | "She pulled a pair of" | | 6 | "She lifted the victim's collar." | | 7 | "You're tired, Harlow." | | 8 | "You've been on this beat" | | 9 | "She walked to the edge" | | 10 | "She reached into her coat" | | 11 | "It spun wildly, then locked" | | 12 | "You think this is a" | | 13 | "I think you're missing the" | | 14 | "She knelt again, ignoring the" | | 15 | "She scanned the victim's pockets." | | 16 | "She picked up the token." | | 17 | "It was warm, vibrating slightly" | | 18 | "It's Camden Town, Harlow." | | 19 | "We know the map." |
| | ratio | 0.407 | |
| 10.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 126 | | totalSentences | 140 | | matches | | 0 | "The copper scent hit Harlow" | | 1 | "She stepped over the prone" | | 2 | "The blood pooling beneath the" | | 3 | "It sat there, a perfect," | | 4 | "DS Miller stood by the" | | 5 | "He held a clipboard like" | | 6 | "Overdose, he said." | | 7 | "Junkie tripped on the tracks." | | 8 | "Harlow ignored him." | | 9 | "She crouched beside the body," | | 10 | "The skin was cold, grey," | | 11 | "He leaned in, squinting." | | 12 | "She pulled a pair of" | | 13 | "The sound echoed too loudly" | | 14 | "She lifted the victim's collar." | | 15 | "The skin beneath was unbroken," | | 16 | "Suicide doesn't leave the windpipe" | | 17 | "Head hit the wall." | | 18 | "The wall is ten feet" | | 19 | "Miller shifted his weight, his" |
| | ratio | 0.9 | |
| 35.71% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 140 | | matches | | | ratio | 0.007 | |
| 99.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 2 | | matches | | 0 | "Miller shifted his weight, his eyes darting to the shadows lining the tunnel." | | 1 | "The casing had a patina of verdigris, the face etched with protective sigils that caught the dim light." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |