| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 33 | | tagDensity | 0.394 | | leniency | 0.788 | | rawRatio | 0.077 | | effectiveRatio | 0.061 | |
| 92.07% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1261 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 48.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1261 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "electric" | | 1 | "silence" | | 2 | "gloom" | | 3 | "weight" | | 4 | "reminder" | | 5 | "trembled" | | 6 | "flickered" | | 7 | "fractured" | | 8 | "gleaming" | | 9 | "unspoken" |
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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 | 0 | | narrationSentences | 58 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 78 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1261 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 97.37% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 855 | | uniqueNames | 18 | | maxNameDensity | 1.05 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Soho | 1 | | Rory | 9 | | Eva | 1 | | Cardiff | 1 | | Evan | 1 | | Yu-Fei | 1 | | Cheung | 1 | | Golden | 1 | | Empress | 1 | | Blackwood | 1 | | Carter | 2 | | Irish | 1 | | Ellis | 1 | | Welsh | 1 | | Silas | 4 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Rory" | | 2 | "Eva" | | 3 | "Evan" | | 4 | "Yu-Fei" | | 5 | "Cheung" | | 6 | "Blackwood" | | 7 | "Carter" | | 8 | "Ellis" | | 9 | "Silas" |
| | places | | 0 | "Nest" | | 1 | "Soho" | | 2 | "Cardiff" | | 3 | "Golden" | | 4 | "London" |
| | globalScore | 0.974 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 41.40% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.586 | | wordCount | 1261 | | matches | | 0 | "not marked among them, but she saw the absence in his posture" | | 1 | "neither crossing fully into the bar nor" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 78 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 42.03 | | std | 28.02 | | cv | 0.667 | | sampleLengths | | 0 | 90 | | 1 | 82 | | 2 | 4 | | 3 | 109 | | 4 | 1 | | 5 | 21 | | 6 | 34 | | 7 | 21 | | 8 | 31 | | 9 | 25 | | 10 | 51 | | 11 | 19 | | 12 | 31 | | 13 | 21 | | 14 | 46 | | 15 | 38 | | 16 | 68 | | 17 | 25 | | 18 | 61 | | 19 | 55 | | 20 | 61 | | 21 | 39 | | 22 | 15 | | 23 | 70 | | 24 | 17 | | 25 | 28 | | 26 | 40 | | 27 | 26 | | 28 | 22 | | 29 | 110 |
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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 | 137 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 78 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 867 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 30 | | adverbRatio | 0.03460207612456748 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.00922722029988466 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 78 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 78 | | mean | 16.17 | | std | 10.94 | | cv | 0.677 | | sampleLengths | | 0 | 22 | | 1 | 5 | | 2 | 7 | | 3 | 22 | | 4 | 16 | | 5 | 18 | | 6 | 13 | | 7 | 2 | | 8 | 4 | | 9 | 41 | | 10 | 10 | | 11 | 6 | | 12 | 6 | | 13 | 4 | | 14 | 19 | | 15 | 12 | | 16 | 20 | | 17 | 23 | | 18 | 35 | | 19 | 1 | | 20 | 21 | | 21 | 7 | | 22 | 26 | | 23 | 1 | | 24 | 13 | | 25 | 8 | | 26 | 3 | | 27 | 16 | | 28 | 12 | | 29 | 9 | | 30 | 16 | | 31 | 8 | | 32 | 12 | | 33 | 15 | | 34 | 5 | | 35 | 11 | | 36 | 8 | | 37 | 11 | | 38 | 3 | | 39 | 17 | | 40 | 11 | | 41 | 14 | | 42 | 7 | | 43 | 15 | | 44 | 31 | | 45 | 6 | | 46 | 14 | | 47 | 18 | | 48 | 7 | | 49 | 15 |
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| 55.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.38461538461538464 | | totalSentences | 78 | | uniqueOpeners | 30 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 56 | | matches | | 0 | "Maybe closer to four." | | 1 | "Then she saw him." |
| | ratio | 0.036 | |
| 27.14% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 56 | | matches | | 0 | "She pushed through the door." | | 1 | "She had lived in the" | | 2 | "She never used the front" | | 3 | "She never crossed into this" | | 4 | "His grey-streaked auburn hair caught" | | 5 | "His neatly trimmed beard matched" | | 6 | "He wore a dark shirt," | | 7 | "His left leg bore a" | | 8 | "His voice carried the same" | | 9 | "She touched her left wrist" | | 10 | "He set the untouched glass" | | 11 | "She stepped closer." | | 12 | "He did not smile" | | 13 | "They had wanted a barrister." | | 14 | "They had not wanted a" | | 15 | "She pulled her wet coat" | | 16 | "He tapped the silver signet" | | 17 | "She looked at the old" | | 18 | "He stepped around the bar," | | 19 | "She kept her voice low," |
| | ratio | 0.482 | |
| 13.57% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 56 | | matches | | 0 | "The green neon sign of" | | 1 | "She pushed through the door." | | 2 | "The latch clicked behind her" | | 3 | "Rory stood at the threshold," | | 4 | "She had lived in the" | | 5 | "Every night she climbed the" | | 6 | "She never used the front" | | 7 | "She never crossed into this" | | 8 | "Silas Blackwood leaned against the" | | 9 | "His grey-streaked auburn hair caught" | | 10 | "His neatly trimmed beard matched" | | 11 | "He wore a dark shirt," | | 12 | "His left leg bore a" | | 13 | "His voice carried the same" | | 14 | "She touched her left wrist" | | 15 | "The small crescent-shaped scar from" | | 16 | "He set the untouched glass" | | 17 | "She stepped closer." | | 18 | "The bar between them felt" | | 19 | "He did not smile" |
| | ratio | 0.893 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 75.89% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 3 | | matches | | 0 | "His left leg bore a slight limp when he shifted his weight, an old knee injury that had not existed in the man who had once taught her to read a room before ent…" | | 1 | "The small crescent-shaped scar from her childhood accident felt cold against her palm, a half-moon reminder of a girl who had once believed in straight lines." | | 2 | "Jennifer Carter née Ellis, the Welsh teacher who had read Rory bedtime stories about justice." |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "She pulled, water dripping onto the floorboards" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "he corrected (correct)" |
| | dialogueSentences | 33 | | tagDensity | 0.03 | | leniency | 0.061 | | rawRatio | 1 | | effectiveRatio | 0.061 | |