| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 30 | | adverbTagCount | 3 | | adverbTags | | 0 | "She turned back [back]" | | 1 | "Patel said finally [finally]" | | 2 | "he said slowly [slowly]" |
| | dialogueSentences | 71 | | tagDensity | 0.423 | | leniency | 0.845 | | rawRatio | 0.1 | | effectiveRatio | 0.085 | |
| 79.56% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1223 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "precisely" | | 1 | "gently" | | 2 | "slowly" | | 3 | "very" |
| |
| 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) | |
| 63.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1223 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "echoed" | | 1 | "weight" | | 2 | "perfect" | | 3 | "familiar" | | 4 | "silence" | | 5 | "navigated" | | 6 | "pulsed" |
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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 | 108 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 108 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 140 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1223 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.27% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 836 | | uniqueNames | 23 | | maxNameDensity | 1.67 | | worstName | "Patel" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Venetian | 1 | | Carnival | 1 | | Patel | 14 | | Tube | 1 | | Detective | 1 | | Harlow | 1 | | Quinn | 13 | | Morris | 3 | | Northern | 1 | | Line | 1 | | Photographs | 1 | | Want | 1 | | Thirteen-pointed | 1 | | Silence | 1 | | Exclusive | 1 | | Look | 1 | | Internal | 1 | | Affairs | 1 | | Sanskrit | 1 | | Queen | 1 | | Jubilee | 1 | | Camden | 1 | | Full | 1 |
| | persons | | 0 | "Patel" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Morris" | | 4 | "Line" | | 5 | "Silence" | | 6 | "Look" | | 7 | "Affairs" | | 8 | "Queen" | | 9 | "Jubilee" | | 10 | "Camden" | | 11 | "Full" |
| | places | | | globalScore | 0.663 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 51 | | 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 | 1223 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 140 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 65 | | mean | 18.82 | | std | 14.65 | | cv | 0.779 | | sampleLengths | | 0 | 19 | | 1 | 28 | | 2 | 39 | | 3 | 9 | | 4 | 11 | | 5 | 37 | | 6 | 4 | | 7 | 30 | | 8 | 3 | | 9 | 38 | | 10 | 13 | | 11 | 6 | | 12 | 3 | | 13 | 51 | | 14 | 1 | | 15 | 24 | | 16 | 11 | | 17 | 26 | | 18 | 11 | | 19 | 63 | | 20 | 11 | | 21 | 5 | | 22 | 29 | | 23 | 4 | | 24 | 33 | | 25 | 28 | | 26 | 6 | | 27 | 41 | | 28 | 1 | | 29 | 3 | | 30 | 19 | | 31 | 17 | | 32 | 7 | | 33 | 4 | | 34 | 42 | | 35 | 20 | | 36 | 6 | | 37 | 21 | | 38 | 6 | | 39 | 25 | | 40 | 48 | | 41 | 15 | | 42 | 37 | | 43 | 4 | | 44 | 41 | | 45 | 6 | | 46 | 18 | | 47 | 29 | | 48 | 10 | | 49 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 108 | | matches | (empty) | |
| 73.42% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 158 | | matches | | 0 | "was already running" | | 1 | "was holding" | | 2 | "was already walking" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 140 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 552 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.021739130434782608 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0036231884057971015 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 140 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 140 | | mean | 8.74 | | std | 8.54 | | cv | 0.977 | | sampleLengths | | 0 | 6 | | 1 | 2 | | 2 | 2 | | 3 | 9 | | 4 | 19 | | 5 | 9 | | 6 | 9 | | 7 | 12 | | 8 | 16 | | 9 | 1 | | 10 | 1 | | 11 | 6 | | 12 | 3 | | 13 | 4 | | 14 | 7 | | 15 | 11 | | 16 | 11 | | 17 | 6 | | 18 | 3 | | 19 | 3 | | 20 | 3 | | 21 | 4 | | 22 | 20 | | 23 | 10 | | 24 | 3 | | 25 | 30 | | 26 | 8 | | 27 | 3 | | 28 | 3 | | 29 | 7 | | 30 | 6 | | 31 | 2 | | 32 | 1 | | 33 | 10 | | 34 | 2 | | 35 | 2 | | 36 | 25 | | 37 | 12 | | 38 | 1 | | 39 | 9 | | 40 | 15 | | 41 | 10 | | 42 | 1 | | 43 | 9 | | 44 | 2 | | 45 | 2 | | 46 | 13 | | 47 | 11 | | 48 | 21 | | 49 | 30 |
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| 86.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5285714285714286 | | totalSentences | 140 | | uniqueOpeners | 74 | |
| 80.32% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 83 | | matches | | 0 | "More of that prime number" | | 1 | "More isn't some university paranormal" |
| | ratio | 0.024 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 83 | | matches | | 0 | "Her leather watch pressed cold" | | 1 | "She'd seen tokens like that" | | 2 | "Her jaw tightened." | | 3 | "He gestured at the arched" | | 4 | "Her knees clicked." | | 5 | "She pointed at the chest" | | 6 | "She moved her finger to" | | 7 | "She didn't touch it yet" | | 8 | "She indicated scuff patterns in" | | 9 | "She turned back to the" | | 10 | "She pointed at the feathers" | | 11 | "He stepped away to answer," | | 12 | "She crouched again, her knees" | | 13 | "She needed to40" | | 14 | "She needed to see the" | | 15 | "Her gloved fingers extracted it" | | 16 | "Her chest constricted." | | 17 | "She knew this token. Knew" | | 18 | "She watched him try. His" | | 19 | "he said slowly" |
| | ratio | 0.277 | |
| 80.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 83 | | matches | | 0 | "The corpse wore a Venetian" | | 1 | "A cheap souvenir from a" | | 2 | "DS Patel's voice echoed off" | | 3 | "Detective Harlow Quinn didn't look" | | 4 | "Her leather watch pressed cold" | | 5 | "The victim, male, late twenties," | | 6 | "Patel shifted his weight." | | 7 | "Quinn's fingers hovered over the" | | 8 | "A bone token, smooth and" | | 9 | "She'd seen tokens like that" | | 10 | "The Morris case." | | 11 | "Her jaw tightened." | | 12 | "Patel consulted his notepad, though" | | 13 | "He gestured at the arched" | | 14 | "Quinn finally stood." | | 15 | "Her knees clicked." | | 16 | "She pointed at the chest" | | 17 | "She moved her finger to" | | 18 | "Quinn pulled latex gloves from" | | 19 | "Patel leaned closer, his initial" |
| | ratio | 0.759 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 83 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 17 | | technicalSentenceCount | 4 | | matches | | 0 | "Silence filled the abandoned station. Deeper than quiet. The kind of silence that lived underground, thick with dust and old secrets." | | 1 | "She watched him try. His eyes moved from the body to the scaffolding to the service door she'd indicated earlier. A sharp detective, Patel. Only twenty-nine but…" | | 2 | "Quinn moved first. Her shoes found the spiral staircase that led to the surface, the metal grating ringing with each step. Patel followed, radio in hand, callin…" | | 3 | "Quinn memorised the silhouette before it vanished around a corner. Short. Female. Frightened posture but deliberate route. She'd navigated Camden's back alleys …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 28 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 71 | | tagDensity | 0.099 | | leniency | 0.197 | | rawRatio | 0 | | effectiveRatio | 0 | |