| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 1 | | adverbTags | | 0 | "She pointed back [back]" |
| | dialogueSentences | 60 | | tagDensity | 0.367 | | leniency | 0.733 | | rawRatio | 0.045 | | effectiveRatio | 0.033 | |
| 89.63% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1929 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "lazily" | | 1 | "very" | | 2 | "completely" | | 3 | "perfectly" |
| |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 58.53% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1929 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "echoed" | | 1 | "weight" | | 2 | "perfect" | | 3 | "scanning" | | 4 | "etched" | | 5 | "silence" | | 6 | "shimmered" | | 7 | "traced" | | 8 | "pulsed" | | 9 | "resonated" | | 10 | "flickered" | | 11 | "mechanical" | | 12 | "stomach" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 213 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 213 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 251 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1929 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 73 | | wordCount | 1429 | | uniqueNames | 18 | | maxNameDensity | 1.61 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 23 | | Quinn | 1 | | Patel | 19 | | Tube | 1 | | Camden | 1 | | Morris | 5 | | Affairs | 1 | | Rolex | 1 | | Eva | 7 | | Veil | 3 | | Compass | 2 | | British | 1 | | Museum | 1 | | Brown | 1 | | Oxford | 1 | | Early | 1 | | Market | 1 | | Wrong | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Patel" | | 3 | "Morris" | | 4 | "Affairs" | | 5 | "Rolex" | | 6 | "Eva" | | 7 | "Brown" | | 8 | "Market" |
| | places | | | globalScore | 0.695 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 112 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1929 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 251 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 77 | | mean | 25.05 | | std | 15.1 | | cv | 0.603 | | sampleLengths | | 0 | 42 | | 1 | 40 | | 2 | 52 | | 3 | 12 | | 4 | 46 | | 5 | 29 | | 6 | 47 | | 7 | 23 | | 8 | 34 | | 9 | 30 | | 10 | 56 | | 11 | 21 | | 12 | 22 | | 13 | 13 | | 14 | 28 | | 15 | 7 | | 16 | 52 | | 17 | 50 | | 18 | 13 | | 19 | 3 | | 20 | 5 | | 21 | 42 | | 22 | 16 | | 23 | 28 | | 24 | 40 | | 25 | 12 | | 26 | 30 | | 27 | 16 | | 28 | 51 | | 29 | 52 | | 30 | 37 | | 31 | 15 | | 32 | 17 | | 33 | 55 | | 34 | 16 | | 35 | 13 | | 36 | 9 | | 37 | 21 | | 38 | 24 | | 39 | 26 | | 40 | 52 | | 41 | 6 | | 42 | 23 | | 43 | 22 | | 44 | 1 | | 45 | 39 | | 46 | 3 | | 47 | 10 | | 48 | 24 | | 49 | 14 |
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| 98.67% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 213 | | matches | | 0 | "been sealed" | | 1 | "was gone" | | 2 | "been welded" | | 3 | "been removed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 235 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 251 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1434 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 54 | | adverbRatio | 0.03765690376569038 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.011157601115760111 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 251 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 251 | | mean | 7.69 | | std | 6.05 | | cv | 0.787 | | sampleLengths | | 0 | 13 | | 1 | 29 | | 2 | 18 | | 3 | 7 | | 4 | 15 | | 5 | 4 | | 6 | 7 | | 7 | 1 | | 8 | 1 | | 9 | 15 | | 10 | 18 | | 11 | 3 | | 12 | 1 | | 13 | 2 | | 14 | 9 | | 15 | 3 | | 16 | 5 | | 17 | 15 | | 18 | 22 | | 19 | 1 | | 20 | 2 | | 21 | 1 | | 22 | 2 | | 23 | 27 | | 24 | 8 | | 25 | 22 | | 26 | 8 | | 27 | 2 | | 28 | 3 | | 29 | 4 | | 30 | 17 | | 31 | 6 | | 32 | 4 | | 33 | 6 | | 34 | 24 | | 35 | 17 | | 36 | 4 | | 37 | 9 | | 38 | 12 | | 39 | 2 | | 40 | 6 | | 41 | 9 | | 42 | 8 | | 43 | 7 | | 44 | 12 | | 45 | 8 | | 46 | 13 | | 47 | 10 | | 48 | 12 | | 49 | 8 |
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| 66.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.42231075697211157 | | totalSentences | 251 | | uniqueOpeners | 106 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 174 | | matches | | 0 | "Then the lights went out" | | 1 | "Just the smell and a" | | 2 | "Then it vanished." | | 3 | "Instead of a weapon, the" | | 4 | "Only the fresh blood on" | | 5 | "Perfectly ordinary welded metal once" |
| | ratio | 0.034 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 174 | | matches | | 0 | "He shifted his weight, boots" | | 1 | "She studied the dead man's" | | 2 | "She touched one." | | 3 | "Her words came clipped, military" | | 4 | "She straightened, scanning the platform." | | 5 | "She recognised the shape from" | | 6 | "She held up the token" | | 7 | "His jacket strained across broad" | | 8 | "Her sharp jaw tightened." | | 9 | "She had never told anyone" | | 10 | "She pointed back at the" | | 11 | "His silence carried weight." | | 12 | "She stopped at a maintenance" | | 13 | "She produced a small torch" | | 14 | "She kept her voice level" | | 15 | "She pressed her palm against" | | 16 | "Her fingers tingled." | | 17 | "It pulsed once under her" | | 18 | "It resonated in her bones," | | 19 | "His hand moved toward his" |
| | ratio | 0.259 | |
| 57.70% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 140 | | totalSentences | 174 | | matches | | 0 | "The body lay sprawled across" | | 1 | "Detective Harlow Quinn crouched beside" | | 2 | "DS Patel's voice echoed off" | | 3 | "He shifted his weight, boots" | | 4 | "Harlow did not answer." | | 5 | "She studied the dead man's" | | 6 | "The kind that had never" | | 7 | "She touched one." | | 8 | "Her words came clipped, military" | | 9 | "She straightened, scanning the platform." | | 10 | "The air tasted of rust" | | 11 | "The old Camden station had" | | 12 | "Harlow moved to the edge" | | 13 | "A bone token lay half-buried" | | 14 | "She recognised the shape from" | | 15 | "She held up the token" | | 16 | "Patel crossed his arms." | | 17 | "His jacket strained across broad" | | 18 | "Harlow slipped the token into" | | 19 | "Her sharp jaw tightened." |
| | ratio | 0.805 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 174 | | matches | (empty) | | ratio | 0 | |
| 80.75% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 4 | | matches | | 0 | "Yet fresh calluses marked the base of each finger, four perfect ridges that spoke of recent, repetitive work." | | 1 | "A bone token lay half-buried in the grime near the yellow line, small, etched with symbols that hurt to look at directly." | | 2 | "Internal Affairs preferred simpler explanations, ones that didn't involve things that shouldn't exist." | | 3 | "It pulsed once under her touch, a faint blue glow that died instantly." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "Patel whispered (whisper)" |
| | dialogueSentences | 60 | | tagDensity | 0.017 | | leniency | 0.033 | | rawRatio | 1 | | effectiveRatio | 0.033 | |