| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 41 | | tagDensity | 0.415 | | leniency | 0.829 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.09% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1019 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 80.37% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1019 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "etched" | | 1 | "flicker" | | 2 | "flickered" |
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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 | 65 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 65 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 89 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1019 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 645 | | uniqueNames | 7 | | maxNameDensity | 1.55 | | worstName | "Achebe" | | maxWindowNameDensity | 3 | | worstWindowName | "Achebe" | | discoveredNames | | Harlow | 1 | | Quinn | 7 | | Achebe | 10 | | Peckham | 1 | | Light | 1 | | Danny | 1 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Achebe" | | 3 | "Danny" | | 4 | "Morris" |
| | places | | | globalScore | 0.725 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 34 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 3.73% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.963 | | wordCount | 1019 | | matches | | 0 | "Not settling, not pointing north, but rotating in slow, deliberate arcs, the way a lighthouse beam" | | 1 | "not pointing north, but rotating in slow, deliberate arcs, the way a lighthouse beam" |
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| 91.76% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 89 | | matches | | 0 | "smelled that sweetness" | | 1 | "repointed that section" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 25.48 | | std | 25.68 | | cv | 1.008 | | sampleLengths | | 0 | 5 | | 1 | 43 | | 2 | 31 | | 3 | 60 | | 4 | 4 | | 5 | 22 | | 6 | 42 | | 7 | 5 | | 8 | 3 | | 9 | 44 | | 10 | 16 | | 11 | 50 | | 12 | 2 | | 13 | 28 | | 14 | 38 | | 15 | 4 | | 16 | 2 | | 17 | 3 | | 18 | 70 | | 19 | 4 | | 20 | 34 | | 21 | 2 | | 22 | 10 | | 23 | 76 | | 24 | 7 | | 25 | 39 | | 26 | 1 | | 27 | 57 | | 28 | 1 | | 29 | 3 | | 30 | 74 | | 31 | 11 | | 32 | 104 | | 33 | 7 | | 34 | 39 | | 35 | 16 | | 36 | 19 | | 37 | 1 | | 38 | 7 | | 39 | 35 |
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| 89.07% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 65 | | matches | | 0 | "been pried" | | 1 | "been stripped" | | 2 | "been sealed" |
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| 79.88% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 111 | | matches | | 0 | "was swinging" | | 1 | "was flickering" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 89 | | ratio | 0.011 | | matches | | 0 | "Her knee protested; the platform was colder than it had any right to be, and her joints knew it." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 514 | | adjectiveStacks | 1 | | stackExamples | | 0 | "sweet, burnt-sugar air," |
| | adverbCount | 13 | | adverbRatio | 0.02529182879377432 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.009727626459143969 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 89 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 89 | | mean | 11.45 | | std | 10.74 | | cv | 0.938 | | sampleLengths | | 0 | 5 | | 1 | 10 | | 2 | 20 | | 3 | 6 | | 4 | 7 | | 5 | 3 | | 6 | 26 | | 7 | 2 | | 8 | 16 | | 9 | 44 | | 10 | 4 | | 11 | 22 | | 12 | 2 | | 13 | 13 | | 14 | 2 | | 15 | 25 | | 16 | 3 | | 17 | 2 | | 18 | 3 | | 19 | 23 | | 20 | 21 | | 21 | 7 | | 22 | 9 | | 23 | 12 | | 24 | 19 | | 25 | 19 | | 26 | 2 | | 27 | 8 | | 28 | 1 | | 29 | 16 | | 30 | 3 | | 31 | 2 | | 32 | 7 | | 33 | 29 | | 34 | 4 | | 35 | 2 | | 36 | 3 | | 37 | 7 | | 38 | 4 | | 39 | 19 | | 40 | 3 | | 41 | 4 | | 42 | 33 | | 43 | 4 | | 44 | 8 | | 45 | 26 | | 46 | 2 | | 47 | 4 | | 48 | 6 | | 49 | 5 |
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| 88.39% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.550561797752809 | | totalSentences | 89 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 51 | | matches | (empty) | | ratio | 0 | |
| 55.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 51 | | matches | | 0 | "She counted twice." | | 1 | "Her worn leather watch dug" | | 2 | "He nodded toward a leather" | | 3 | "She'd smelled that sweetness once" | | 4 | "She had read it twice" | | 5 | "She crossed to the bench" | | 6 | "Her knee protested; the platform" | | 7 | "She lifted it" | | 8 | "She opened it." | | 9 | "She turned it over" | | 10 | "She tilted it." | | 11 | "It swung until it pointed" | | 12 | "She pointed at the etched" | | 13 | "He had a hold-it-loosely sort" | | 14 | "He held up an evidence" | | 15 | "It held steady now, fixed" | | 16 | "She stepped off the platform," | | 17 | "Her torch beam found the" | | 18 | "She'd seen a socket like" | | 19 | "she said, low" |
| | ratio | 0.412 | |
| 28.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 51 | | matches | | 0 | "The body had no shadow." | | 1 | "Detective Harlow Quinn saw it" | | 2 | "The floodlamps threw hard light" | | 3 | "She counted twice." | | 4 | "Her worn leather watch dug" | | 5 | "DS Achebe held his notebook" | | 6 | "He nodded toward a leather" | | 7 | "The station smelled of rust" | | 8 | "She'd smelled that sweetness once" | | 9 | "She had read it twice" | | 10 | "Achebe followed her gaze to" | | 11 | "She crossed to the bench" | | 12 | "Her knee protested; the platform" | | 13 | "She lifted it" | | 14 | "She opened it." | | 15 | "A dead torch, its glass" | | 16 | "She turned it over" | | 17 | "The needle was swinging." | | 18 | "She tilted it." | | 19 | "The needle ignored her." |
| | ratio | 0.863 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 51 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 1 | | matches | | 0 | "He had a hold-it-loosely sort of faith, the kind that let him file a sigil in a murder report without complaint." |
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| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 41 | | tagDensity | 0.122 | | leniency | 0.244 | | rawRatio | 0 | | effectiveRatio | 0 | |