| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn's voice grew dangerously [dangerously]" |
| | dialogueSentences | 55 | | tagDensity | 0.382 | | leniency | 0.764 | | rawRatio | 0.048 | | effectiveRatio | 0.036 | |
| 82.17% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1402 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "lazily" | | 1 | "slightly" | | 2 | "slowly" | | 3 | "suddenly" | | 4 | "perfectly" |
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| 60.00% | 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) | |
| 64.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1402 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "fluttered" | | 1 | "perfect" | | 2 | "etched" | | 3 | "footsteps" | | 4 | "echoed" | | 5 | "flicked" | | 6 | "warmth" | | 7 | "weight" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
|
| | highlights | | 0 | "eyes widened" | | 1 | "eyes narrowed" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 108 | | matches | (empty) | |
| 89.95% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 108 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 141 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1401 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 61 | | wordCount | 863 | | uniqueNames | 11 | | maxNameDensity | 2.67 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Eva" | | discoveredNames | | Harlow | 1 | | Quinn | 23 | | Tube | 1 | | Police | 1 | | Camden | 1 | | Patel | 8 | | Vale | 3 | | Maglite | 1 | | Kowalski | 1 | | Eva | 19 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Patel" | | 3 | "Vale" | | 4 | "Kowalski" | | 5 | "Eva" | | 6 | "Morris" |
| | places | (empty) | | globalScore | 0.167 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | 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 | 1401 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 141 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 25.02 | | std | 15.76 | | cv | 0.63 | | sampleLengths | | 0 | 4 | | 1 | 69 | | 2 | 37 | | 3 | 39 | | 4 | 54 | | 5 | 21 | | 6 | 52 | | 7 | 7 | | 8 | 29 | | 9 | 59 | | 10 | 44 | | 11 | 17 | | 12 | 22 | | 13 | 44 | | 14 | 36 | | 15 | 31 | | 16 | 6 | | 17 | 14 | | 18 | 23 | | 19 | 24 | | 20 | 10 | | 21 | 19 | | 22 | 10 | | 23 | 20 | | 24 | 39 | | 25 | 19 | | 26 | 22 | | 27 | 19 | | 28 | 34 | | 29 | 30 | | 30 | 24 | | 31 | 12 | | 32 | 43 | | 33 | 13 | | 34 | 51 | | 35 | 16 | | 36 | 3 | | 37 | 11 | | 38 | 42 | | 39 | 40 | | 40 | 33 | | 41 | 8 | | 42 | 33 | | 43 | 6 | | 44 | 16 | | 45 | 22 | | 46 | 35 | | 47 | 22 | | 48 | 24 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 108 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 151 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 141 | | ratio | 0.007 | | matches | | 0 | "\"Three years of dreams about things with too many joints and not enough faces. Morris didn't die, Evie. He was taken. And this—\" She gestured at the impossible crime scene \"—is the first real lead I've had.\"" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 776 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.029639175257731958 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.00902061855670103 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 141 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 141 | | mean | 9.94 | | std | 6.92 | | cv | 0.697 | | sampleLengths | | 0 | 4 | | 1 | 23 | | 2 | 22 | | 3 | 24 | | 4 | 16 | | 5 | 8 | | 6 | 13 | | 7 | 4 | | 8 | 4 | | 9 | 2 | | 10 | 16 | | 11 | 13 | | 12 | 7 | | 13 | 1 | | 14 | 2 | | 15 | 15 | | 16 | 6 | | 17 | 6 | | 18 | 17 | | 19 | 4 | | 20 | 17 | | 21 | 3 | | 22 | 13 | | 23 | 25 | | 24 | 11 | | 25 | 7 | | 26 | 5 | | 27 | 24 | | 28 | 3 | | 29 | 19 | | 30 | 12 | | 31 | 1 | | 32 | 11 | | 33 | 13 | | 34 | 6 | | 35 | 14 | | 36 | 24 | | 37 | 8 | | 38 | 9 | | 39 | 12 | | 40 | 10 | | 41 | 6 | | 42 | 19 | | 43 | 19 | | 44 | 9 | | 45 | 12 | | 46 | 15 | | 47 | 6 | | 48 | 6 | | 49 | 19 |
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| 72.34% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.46808510638297873 | | totalSentences | 141 | | uniqueOpeners | 66 | |
| 35.46% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 94 | | matches | | | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 94 | | matches | | 0 | "His torch beam danced across" | | 1 | "She recognised the victim." | | 2 | "She studied the wound across" | | 3 | "She reached for the small" | | 4 | "She slipped it into an" | | 5 | "Her freckled face paled further" | | 6 | "She watched Eva's eyes dart" | | 7 | "Her brown eyes remained fixed" | | 8 | "She worried her lower lip." | | 9 | "She turned slowly, studying the" | | 10 | "She examined Vale's hands." | | 11 | "She indicated faint marks on" | | 12 | "Her green eyes widened behind" | | 13 | "She gestured at the impossible" | | 14 | "Its needle snapped to point" | | 15 | "Her face settled into something" | | 16 | "She reached into her satchel" | | 17 | "She thought of Morris's last" | | 18 | "She drew her baton." |
| | ratio | 0.202 | |
| 34.47% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 80 | | totalSentences | 94 | | matches | | 0 | "The blood smelled wrong." | | 1 | "Detective Harlow Quinn crouched beside" | | 2 | "The metallic tang carried notes" | | 3 | "DS Patel said, hovering a" | | 4 | "His torch beam danced across" | | 5 | "Quinn's sharp jaw tightened." | | 6 | "She recognised the victim." | | 7 | "The kind of man who" | | 8 | "She studied the wound across" | | 9 | "The edges of the cut" | | 10 | "Blood had pooled beneath him" | | 11 | "Quinn said nothing." | | 12 | "She reached for the small" | | 13 | "The casing bore a patina" | | 14 | "The needle spun lazily, not" | | 15 | "She slipped it into an" | | 16 | "The wrong place." | | 17 | "Quinn's gaze travelled along the" | | 18 | "The official report still called" | | 19 | "Footsteps echoed from the access" |
| | ratio | 0.851 | |
| 53.19% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 94 | | matches | | 0 | "As though he'd seen his" |
| | ratio | 0.011 | |
| 44.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 4 | | matches | | 0 | "Metropolitan Police tape fluttered uselessly at the entrance to the disused Camden platform, doing nothing to stop the damp that seeped through her coat." | | 1 | "Small-time fence who moved items between the ordinary world and places most coppers didn't know existed." | | 2 | "The casing bore a patina of verdigris, its face etched with protective sigils that made her teeth ache when she looked at them too long." | | 3 | "Of the salt-and-pepper hair that had appeared in her mirror far too early." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Patel continued (continue)" |
| | dialogueSentences | 55 | | tagDensity | 0.036 | | leniency | 0.073 | | rawRatio | 0.5 | | effectiveRatio | 0.036 | |