| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said softly [softly]" |
| | dialogueSentences | 28 | | tagDensity | 0.321 | | leniency | 0.643 | | rawRatio | 0.111 | | effectiveRatio | 0.071 | |
| 91.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 587 | | 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) | |
| 14.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 587 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "gloom" | | 1 | "glinting" | | 2 | "shimmered" | | 3 | "etched" | | 4 | "whisper" | | 5 | "spectral" | | 6 | "velvet" | | 7 | "silence" | | 8 | "familiar" | | 9 | "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 | 58 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 58 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 77 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 3 | | totalWords | 577 | | ratio | 0.005 | | matches | | 0 | "Returned with interest." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 52.44% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 410 | | uniqueNames | 7 | | maxNameDensity | 1.95 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Grayson" | | discoveredNames | | Harlow | 8 | | Quinn | 1 | | Grayson | 8 | | Edwardian | 1 | | Oxford | 1 | | Eva | 1 | | Kowalski | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Grayson" | | 3 | "Kowalski" |
| | places | | | globalScore | 0.524 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 32 | | 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 | 577 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 77 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 15.18 | | std | 11.52 | | cv | 0.759 | | sampleLengths | | 0 | 28 | | 1 | 22 | | 2 | 42 | | 3 | 20 | | 4 | 11 | | 5 | 23 | | 6 | 26 | | 7 | 21 | | 8 | 32 | | 9 | 41 | | 10 | 6 | | 11 | 22 | | 12 | 20 | | 13 | 22 | | 14 | 32 | | 15 | 1 | | 16 | 1 | | 17 | 13 | | 18 | 18 | | 19 | 6 | | 20 | 26 | | 21 | 2 | | 22 | 2 | | 23 | 1 | | 24 | 11 | | 25 | 7 | | 26 | 34 | | 27 | 13 | | 28 | 4 | | 29 | 5 | | 30 | 8 | | 31 | 4 | | 32 | 10 | | 33 | 6 | | 34 | 8 | | 35 | 5 | | 36 | 20 | | 37 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 58 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 78 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 77 | | ratio | 0.065 | | matches | | 0 | "The scent of burning sage and something older—wet earth, rotting parchment—curled into her nostrils." | | 1 | "The dust here wasn’t just disturbed—it swirled in lazy circles, as if stirred by an absent wind." | | 2 | "One item missing—a shallow indentation in the velvet lining, roughly compass-shaped." | | 3 | "No—not hers." | | 4 | "A familiar scar marked the inside of the wrist—three parallel lines, surgically precise." |
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| 93.13% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 418 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.04784688995215311 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.007177033492822967 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 77 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 77 | | mean | 7.49 | | std | 5.1 | | cv | 0.68 | | sampleLengths | | 0 | 14 | | 1 | 14 | | 2 | 20 | | 3 | 2 | | 4 | 16 | | 5 | 22 | | 6 | 4 | | 7 | 11 | | 8 | 4 | | 9 | 5 | | 10 | 11 | | 11 | 5 | | 12 | 2 | | 13 | 2 | | 14 | 10 | | 15 | 4 | | 16 | 11 | | 17 | 15 | | 18 | 8 | | 19 | 11 | | 20 | 2 | | 21 | 11 | | 22 | 10 | | 23 | 11 | | 24 | 6 | | 25 | 2 | | 26 | 17 | | 27 | 7 | | 28 | 1 | | 29 | 8 | | 30 | 6 | | 31 | 2 | | 32 | 20 | | 33 | 5 | | 34 | 5 | | 35 | 7 | | 36 | 3 | | 37 | 22 | | 38 | 11 | | 39 | 11 | | 40 | 10 | | 41 | 1 | | 42 | 1 | | 43 | 5 | | 44 | 8 | | 45 | 7 | | 46 | 11 | | 47 | 6 | | 48 | 4 | | 49 | 8 |
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| 98.70% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.6363636363636364 | | totalSentences | 77 | | uniqueOpeners | 49 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 46 | | matches | | 0 | "Just a frozen rictus of" | | 1 | "Somewhere in the dark, something" | | 2 | "Then the screaming started." |
| | ratio | 0.065 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 9 | | totalSentences | 46 | | matches | | 0 | "She reached for the victim’s" | | 1 | "Her fingers touched the floor’s" | | 2 | "She studied the vendor’s stall." | | 3 | "He gestured at the corpse’s" | | 4 | "She exhaled through her nose." | | 5 | "His silence stretched a beat" | | 6 | "Her reflection warped in a" | | 7 | "she said softly, peeling back" | | 8 | "She drew her sidearm." |
| | ratio | 0.196 | |
| 36.09% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 39 | | totalSentences | 46 | | matches | | 0 | "Detective Harlow Quinn kicked aside" | | 1 | "The scent of burning sage" | | 2 | "DS Grayson didn't look up" | | 3 | "Harlow thumbed the catch on" | | 4 | "The beam sliced through the" | | 5 | "Grayson nudged the victim’s shoulder" | | 6 | "The corpse rolled face-up." | | 7 | "The thing staring back at" | | 8 | "Harlow crouched, leather jacket creaking." | | 9 | "Grayson pulled a melted SD" | | 10 | "She reached for the victim’s" | | 11 | "The fabric shimmered under her" | | 12 | "Grayson held up a bone" | | 13 | "The etched runes matched the" | | 14 | "Harlow’s boot scuffed against loose" | | 15 | "The dust here wasn’t just" | | 16 | "Her fingers touched the floor’s" | | 17 | "She studied the vendor’s stall." | | 18 | "Shelves stood intact, merchandise undisturbed." | | 19 | "He gestured at the corpse’s" |
| | ratio | 0.848 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 46 | | matches | | 0 | "Whoever did this hadn’t come" |
| | ratio | 0.022 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 15 | | technicalSentenceCount | 1 | | matches | | 0 | "The beam sliced through the underground market’s gloom, glinting off brass scales and glass vials still lining the abandoned stall behind them." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.036 | | leniency | 0.071 | | rawRatio | 0 | | effectiveRatio | 0 | |