| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 32 | | tagDensity | 0.563 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1036 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 37.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1036 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "chill" | | 1 | "familiar" | | 2 | "glinting" | | 3 | "stark" | | 4 | "scanning" | | 5 | "etched" | | 6 | "flicker" | | 7 | "weight" | | 8 | "furrowed" | | 9 | "tracing" | | 10 | "pulsed" | | 11 | "newfound" | | 12 | "palpable" |
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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 | 60 | | matches | (empty) | |
| 95.24% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 60 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 73 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1035 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 34.44% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 649 | | uniqueNames | 11 | | maxNameDensity | 2.31 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 15 | | Detective | 1 | | Sergeant | 1 | | Davies | 9 | | Tube | 2 | | Veil | 2 | | Market | 1 | | Eva | 2 | | Kowalski | 1 | | Morris | 1 | | Compass | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Sergeant" | | 2 | "Davies" | | 3 | "Eva" | | 4 | "Kowalski" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 0.344 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.966 | | wordCount | 1035 | | matches | | 0 | "Not the frenzied hacking of a madman, but the deliberate, practiced strokes of someone who knew exactl" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 73 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 41.4 | | std | 23.15 | | cv | 0.559 | | sampleLengths | | 0 | 61 | | 1 | 53 | | 2 | 17 | | 3 | 30 | | 4 | 88 | | 5 | 82 | | 6 | 25 | | 7 | 64 | | 8 | 51 | | 9 | 28 | | 10 | 57 | | 11 | 10 | | 12 | 8 | | 13 | 66 | | 14 | 12 | | 15 | 56 | | 16 | 32 | | 17 | 39 | | 18 | 18 | | 19 | 64 | | 20 | 9 | | 21 | 53 | | 22 | 44 | | 23 | 14 | | 24 | 54 |
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| 76.02% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 60 | | matches | | 0 | "been corroborated" | | 1 | "was arranged" | | 2 | "were scrawled" | | 3 | "was etched" | | 4 | "being woven" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 103 | | matches | | |
| 64.58% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 73 | | ratio | 0.027 | | matches | | 0 | "“Supernatural rifts, you say?” she murmured, a flicker of memory surfacing – DS Morris, his last, rambling words about doors that shouldn't be opened." | | 1 | "The symbols weren’t random; they followed a distinct pattern, a narrative being woven in blood." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 650 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.03076923076923077 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.012307692307692308 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 73 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 73 | | mean | 14.18 | | std | 9.83 | | cv | 0.693 | | sampleLengths | | 0 | 20 | | 1 | 20 | | 2 | 21 | | 3 | 12 | | 4 | 22 | | 5 | 19 | | 6 | 17 | | 7 | 20 | | 8 | 10 | | 9 | 13 | | 10 | 3 | | 11 | 3 | | 12 | 4 | | 13 | 31 | | 14 | 23 | | 15 | 11 | | 16 | 17 | | 17 | 19 | | 18 | 8 | | 19 | 14 | | 20 | 24 | | 21 | 15 | | 22 | 10 | | 23 | 23 | | 24 | 2 | | 25 | 15 | | 26 | 24 | | 27 | 13 | | 28 | 2 | | 29 | 1 | | 30 | 11 | | 31 | 24 | | 32 | 8 | | 33 | 20 | | 34 | 11 | | 35 | 5 | | 36 | 21 | | 37 | 15 | | 38 | 5 | | 39 | 7 | | 40 | 3 | | 41 | 2 | | 42 | 6 | | 43 | 41 | | 44 | 25 | | 45 | 5 | | 46 | 7 | | 47 | 6 | | 48 | 36 | | 49 | 5 |
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| 87.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5342465753424658 | | totalSentences | 73 | | uniqueOpeners | 39 | |
| 62.89% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 53 | | matches | | 0 | "Only, there was something off." |
| | ratio | 0.019 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 53 | | matches | | 0 | "She pushed through the throng" | | 1 | "He gestured towards the centre" | | 2 | "She’d never imagined it would" | | 3 | "His body was arranged in" | | 4 | "They seemed to writhe in" | | 5 | "she murmured, a flicker of" | | 6 | "She knelt beside the body," | | 7 | "She examined the wounds again." | | 8 | "It was too clean, too" | | 9 | "She indicated a dark, narrow" | | 10 | "She stood, the compass still" | | 11 | "She rose, her short, salt-and-pepper" |
| | ratio | 0.226 | |
| 16.60% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 53 | | matches | | 0 | "The reek of ozone and" | | 1 | "She pushed through the throng" | | 2 | "The chill in the air" | | 3 | "a familiar voice, sharp and" | | 4 | "Detective Sergeant Davies, his perpetually" | | 5 | "He gestured towards the centre" | | 6 | "Quinn’s voice was level, betraying" | | 7 | "Davies began, his gaze flicking" | | 8 | "Quinn stepped under the tape," | | 9 | "The Veil Market." | | 10 | "The information about this place," | | 11 | "Eva had given her an" | | 12 | "She’d never imagined it would" | | 13 | "The air here was thick," | | 14 | "A man, or what was" | | 15 | "His body was arranged in" | | 16 | "Quinn asked, her eyes scanning" | | 17 | "They seemed to writhe in" | | 18 | "Davies held up a small," | | 19 | "The face was etched with" |
| | ratio | 0.887 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 53 | | matches | (empty) | | ratio | 0 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 2 | | matches | | 0 | "The air here was thick, heavy with a cloying perfume that overlaid the metallic tang of blood." | | 1 | "Not the frenzied hacking of a madman, but the deliberate, practiced strokes of someone who knew exactly what they were doing." |
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| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn stated, her voice low" | | 1 | "Quinn said, her fingers tracing the sigils" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 6 | | fancyTags | | 0 | "she murmured (murmur)" | | 1 | "Davies confirmed (confirm)" | | 2 | "Quinn stated (state)" | | 3 | "Davies assured (assure)" | | 4 | "Quinn retorted (retort)" | | 5 | "Davies protested (protest)" |
| | dialogueSentences | 32 | | tagDensity | 0.281 | | leniency | 0.563 | | rawRatio | 0.667 | | effectiveRatio | 0.375 | |