| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.34 | | leniency | 0.68 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1365 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 74.36% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1365 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "weight" | | 1 | "traced" | | 2 | "etched" | | 3 | "trembled" | | 4 | "crystal" | | 5 | "etching" |
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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 | 52 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 52 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 85 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 65 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1375 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 687 | | uniqueNames | 8 | | maxNameDensity | 1.16 | | worstName | "Cole" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Cole" | | discoveredNames | | Camden | 1 | | Rain | 1 | | Sergeant | 1 | | Cole | 8 | | Freckles | 1 | | Quinn | 6 | | Eva | 3 | | Morris | 1 |
| | persons | | 0 | "Rain" | | 1 | "Sergeant" | | 2 | "Cole" | | 3 | "Quinn" | | 4 | "Eva" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 0.918 | | windowScore | 0.833 | |
| 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 | 0 | | per1kWords | 0 | | wordCount | 1375 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 85 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 28.06 | | std | 27.4 | | cv | 0.977 | | sampleLengths | | 0 | 36 | | 1 | 22 | | 2 | 97 | | 3 | 23 | | 4 | 25 | | 5 | 74 | | 6 | 3 | | 7 | 4 | | 8 | 2 | | 9 | 48 | | 10 | 4 | | 11 | 6 | | 12 | 75 | | 13 | 3 | | 14 | 3 | | 15 | 15 | | 16 | 13 | | 17 | 26 | | 18 | 4 | | 19 | 5 | | 20 | 110 | | 21 | 11 | | 22 | 7 | | 23 | 37 | | 24 | 15 | | 25 | 86 | | 26 | 4 | | 27 | 51 | | 28 | 14 | | 29 | 3 | | 30 | 25 | | 31 | 32 | | 32 | 33 | | 33 | 34 | | 34 | 10 | | 35 | 32 | | 36 | 12 | | 37 | 58 | | 38 | 10 | | 39 | 23 | | 40 | 26 | | 41 | 33 | | 42 | 17 | | 43 | 18 | | 44 | 49 | | 45 | 99 | | 46 | 4 | | 47 | 19 | | 48 | 15 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 52 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 108 | | matches | (empty) | |
| 75.63% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 85 | | ratio | 0.024 | | matches | | 0 | "She took the service stair beside the dead escalator — she counted the steps without meaning to, eighty-one, a habit from another life kept as sharp as everything else about her — and came out onto a platform where white tiles had aged to the color of weak tea." | | 1 | "A small brass compass sat against the plastic, its casing furred green with verdigris, its face etched with fine sigils — kin to the chalk signs." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 689 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 11 | | adverbRatio | 0.015965166908563134 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.001451378809869376 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 85 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 85 | | mean | 16.18 | | std | 14.1 | | cv | 0.872 | | sampleLengths | | 0 | 36 | | 1 | 22 | | 2 | 22 | | 3 | 49 | | 4 | 11 | | 5 | 15 | | 6 | 23 | | 7 | 25 | | 8 | 9 | | 9 | 65 | | 10 | 3 | | 11 | 4 | | 12 | 2 | | 13 | 22 | | 14 | 13 | | 15 | 13 | | 16 | 4 | | 17 | 6 | | 18 | 54 | | 19 | 21 | | 20 | 3 | | 21 | 3 | | 22 | 4 | | 23 | 11 | | 24 | 13 | | 25 | 12 | | 26 | 14 | | 27 | 4 | | 28 | 5 | | 29 | 10 | | 30 | 59 | | 31 | 41 | | 32 | 11 | | 33 | 7 | | 34 | 28 | | 35 | 9 | | 36 | 6 | | 37 | 9 | | 38 | 10 | | 39 | 39 | | 40 | 16 | | 41 | 21 | | 42 | 4 | | 43 | 8 | | 44 | 43 | | 45 | 6 | | 46 | 8 | | 47 | 2 | | 48 | 1 | | 49 | 9 |
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| 98.04% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.5882352941176471 | | totalSentences | 85 | | uniqueOpeners | 50 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 48 | | matches | (empty) | | ratio | 0 | |
| 36.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 48 | | matches | | 0 | "She held her warrant card" | | 1 | "She took the service stair" | | 2 | "He flipped a page" | | 3 | "She crouched at the edge" | | 4 | "His collar lay clean against" | | 5 | "She tipped her head at" | | 6 | "He shifted his weight." | | 7 | "She lowered the torch until" | | 8 | "Her finger tracked the chalk" | | 9 | "She swept the light across" | | 10 | "She didn't look up from" | | 11 | "She pushed her glasses up," | | 12 | "Her chin came up" | | 13 | "She let the name sit" | | 14 | "She turned in a slow" | | 15 | "She turned again." | | 16 | "It swung back again, insistent," | | 17 | "She walked the platform with" | | 18 | "Her hand rose and tucked" | | 19 | "She looked from the compass" |
| | ratio | 0.458 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 48 | | matches | | 0 | "The cordon ran behind the" | | 1 | "She held her warrant card" | | 2 | "Rain had followed her beneath" | | 3 | "She took the service stair" | | 4 | "A poster on the far" | | 5 | "Torchlight from two scene-of-crime officers" | | 6 | "Detective Sergeant Cole straightened up" | | 7 | "He flipped a page" | | 8 | "She crouched at the edge" | | 9 | "The pool beneath the man's" | | 10 | "His collar lay clean against" | | 11 | "She tipped her head at" | | 12 | "He shifted his weight." | | 13 | "She lowered the torch until" | | 14 | "Dust held a story down" | | 15 | "Her finger tracked the chalk" | | 16 | "She swept the light across" | | 17 | "A leather satchel sat beside" | | 18 | "She didn't look up from" | | 19 | "She pushed her glasses up," |
| | ratio | 0.938 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 48 | | matches | | 0 | "Before he could answer, the" |
| | ratio | 0.021 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 1 | | matches | | 0 | "The cordon ran behind the Camden lock stalls, tape sagging between two scaffolding poles, and the constable at the end of it had the gray look of a man who'd be…" |
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| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva's voice dropped, as though the tunnel might take an interest" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.02 | | leniency | 0.04 | | rawRatio | 0 | | effectiveRatio | 0 | |