| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 2 | | adverbTags | | 0 | "She gestured around [around]" | | 1 | "Silas turned back [back]" |
| | dialogueSentences | 49 | | tagDensity | 0.51 | | leniency | 1 | | rawRatio | 0.08 | | effectiveRatio | 0.08 | |
| 87.45% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1594 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | adverb | "barely above a whisper" | | count | 1 |
| | 2 | |
| | highlights | | 0 | "really" | | 1 | "barely above a whisper" | | 2 | "gently" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 43.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1594 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "scanned" | | 1 | "familiar" | | 2 | "efficient" | | 3 | "navigating" | | 4 | "etched" | | 5 | "flickered" | | 6 | "measured" | | 7 | "weight" | | 8 | "silence" | | 9 | "traced" | | 10 | "stomach" | | 11 | "silk" | | 12 | "whisper" | | 13 | "reminder" | | 14 | "comfortable" | | 15 | "warmth" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 64 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 64 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 88 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1585 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 920 | | uniqueNames | 11 | | maxNameDensity | 1.52 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Carter | 1 | | London | 3 | | Golden | 1 | | Empress | 1 | | Blackwood | 1 | | Cardiff | 1 | | Aurora | 14 | | Silas | 12 |
| | persons | | 0 | "Carter" | | 1 | "Empress" | | 2 | "Blackwood" | | 3 | "Aurora" | | 4 | "Silas" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "London" | | 3 | "Golden" | | 4 | "Cardiff" |
| | globalScore | 0.739 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed insignificant compared to the fractures in her adult life" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1585 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 88 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 45.29 | | std | 24.02 | | cv | 0.53 | | sampleLengths | | 0 | 88 | | 1 | 72 | | 2 | 86 | | 3 | 18 | | 4 | 36 | | 5 | 72 | | 6 | 18 | | 7 | 47 | | 8 | 49 | | 9 | 19 | | 10 | 75 | | 11 | 50 | | 12 | 66 | | 13 | 71 | | 14 | 78 | | 15 | 6 | | 16 | 47 | | 17 | 55 | | 18 | 68 | | 19 | 34 | | 20 | 64 | | 21 | 37 | | 22 | 50 | | 23 | 57 | | 24 | 9 | | 25 | 29 | | 26 | 56 | | 27 | 24 | | 28 | 35 | | 29 | 44 | | 30 | 11 | | 31 | 26 | | 32 | 1 | | 33 | 18 | | 34 | 69 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 64 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 143 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 88 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 927 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 25 | | adverbRatio | 0.02696871628910464 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.010787486515641856 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 88 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 88 | | mean | 18.01 | | std | 9.31 | | cv | 0.517 | | sampleLengths | | 0 | 23 | | 1 | 26 | | 2 | 21 | | 3 | 18 | | 4 | 16 | | 5 | 20 | | 6 | 18 | | 7 | 18 | | 8 | 8 | | 9 | 9 | | 10 | 21 | | 11 | 29 | | 12 | 19 | | 13 | 15 | | 14 | 3 | | 15 | 6 | | 16 | 26 | | 17 | 4 | | 18 | 13 | | 19 | 21 | | 20 | 30 | | 21 | 8 | | 22 | 14 | | 23 | 4 | | 24 | 25 | | 25 | 22 | | 26 | 23 | | 27 | 26 | | 28 | 15 | | 29 | 4 | | 30 | 16 | | 31 | 24 | | 32 | 35 | | 33 | 17 | | 34 | 33 | | 35 | 34 | | 36 | 15 | | 37 | 17 | | 38 | 20 | | 39 | 36 | | 40 | 15 | | 41 | 5 | | 42 | 50 | | 43 | 23 | | 44 | 6 | | 45 | 19 | | 46 | 28 | | 47 | 10 | | 48 | 11 | | 49 | 34 |
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| 71.97% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4659090909090909 | | totalSentences | 88 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 63 | | matches | | 0 | "Her bright blue eyes scanned" | | 1 | "She moved with the efficient," | | 2 | "His hazel eyes narrowed, then" | | 3 | "He set the glass down" | | 4 | "His grey-streaked auburn beard was" | | 5 | "He paused, choosing his words" | | 6 | "She traced the rim of" | | 7 | "He looked at her, really" | | 8 | "She laughed, a short, humorless" | | 9 | "She gestured around the dim" | | 10 | "He wasn't the glamorous spy" | | 11 | "He was just a man" | | 12 | "she admitted, her voice barely" | | 13 | "He reached under the bar" | | 14 | "he tapped his chest" | | 15 | "They gleamed in the dim" | | 16 | "He cut her off gently" | | 17 | "She looked up at Silas," | | 18 | "she said, the words feeling" | | 19 | "he said without looking back" |
| | ratio | 0.333 | |
| 7.62% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 63 | | matches | | 0 | "The green neon sign above" | | 1 | "Aurora Carter pushed through the" | | 2 | "Her bright blue eyes scanned" | | 3 | "She moved with the efficient," | | 4 | "A delivery bag from the" | | 5 | "Silas Blackwood looked up from" | | 6 | "His hazel eyes narrowed, then" | | 7 | "He set the glass down" | | 8 | "The slight limp in his" | | 9 | "His grey-streaked auburn beard was" | | 10 | "The name left his lips" | | 11 | "Aurora stopped three feet from" | | 12 | "The fluorescent light from the" | | 13 | "Silas leaned against the bar," | | 14 | "The silver signet ring on" | | 15 | "He paused, choosing his words" | | 16 | "Aurora's voice remained level, cool-headed" | | 17 | "Silas studied her, his gaze" | | 18 | "Aurora placed the delivery bag" | | 19 | "Silas poured two fingers of" |
| | ratio | 0.905 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 99.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 2 | | matches | | 0 | "She moved with the efficient, guarded gait of someone who spent too many nights navigating London's backstreets alone." | | 1 | "Aurora looked down at her hands, at the scar on her wrist, a permanent reminder of a childhood accident that seemed insignificant compared to the fractures in h…" |
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| 5.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 6 | | matches | | 0 | "Aurora placed, the plastic crinkling in the silence" | | 1 | "Silas rubbed, the old injury flaring in the damp London air" | | 2 | "Silas straightened, his quiet authority filling the space between them" | | 3 | "she admitted, her voice barely above a whisper" | | 4 | "she said, the words feeling foreign on her tongue" | | 5 | "Silas turned back, his limp less noticeable as he moved with purpose" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "She laughed (laugh)" | | 1 | "she admitted (admit)" |
| | dialogueSentences | 49 | | tagDensity | 0.102 | | leniency | 0.204 | | rawRatio | 0.4 | | effectiveRatio | 0.082 | |