| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.12% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1165 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "truly" | | 1 | "quickly" | | 2 | "slowly" |
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| 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) | |
| 39.91% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1165 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "scanning" | | 1 | "crystalline" | | 2 | "chill" | | 3 | "throbbed" | | 4 | "pulsed" | | 5 | "warmth" | | 6 | "echoed" | | 7 | "pulse" | | 8 | "charged" | | 9 | "measured" |
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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 | 192 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 0 | | narrationSentences | 192 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 192 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1165 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 1144 | | uniqueNames | 11 | | maxNameDensity | 0.35 | | worstName | "London" | | maxWindowNameDensity | 1 | | worstWindowName | "London" | | discoveredNames | | Park | 1 | | Carter | 1 | | London | 4 | | Golden | 1 | | Empress | 1 | | November | 1 | | May | 1 | | Evan | 2 | | Aurora | 3 | | Steady | 3 | | Closer | 3 |
| | persons | | 0 | "Carter" | | 1 | "November" | | 2 | "Evan" | | 3 | "Aurora" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1165 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 192 | | matches | | |
| 30.54% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 11 | | mean | 105.91 | | std | 27.21 | | cv | 0.257 | | sampleLengths | | 0 | 143 | | 1 | 129 | | 2 | 143 | | 3 | 136 | | 4 | 107 | | 5 | 87 | | 6 | 76 | | 7 | 76 | | 8 | 64 | | 9 | 99 | | 10 | 105 |
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| 99.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 192 | | matches | | 0 | "was supposed" | | 1 | "been scrawled" | | 2 | "been given" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 203 | | matches | | 0 | "wasn’t running" | | 1 | "wasn’t just reacting" | | 2 | "was reacting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 192 | | ratio | 0.005 | | matches | | 0 | "It didn’t just shift; it thinned, then thickened, tasting of petrichor, crushed violets, and something metallic, like old copper." |
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| 92.95% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1082 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 52 | | adverbRatio | 0.04805914972273567 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.00831792975970425 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 192 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 192 | | mean | 6.07 | | std | 5.69 | | cv | 0.938 | | sampleLengths | | 0 | 6 | | 1 | 12 | | 2 | 16 | | 3 | 9 | | 4 | 21 | | 5 | 9 | | 6 | 16 | | 7 | 20 | | 8 | 34 | | 9 | 7 | | 10 | 17 | | 11 | 13 | | 12 | 5 | | 13 | 4 | | 14 | 19 | | 15 | 6 | | 16 | 1 | | 17 | 1 | | 18 | 10 | | 19 | 13 | | 20 | 3 | | 21 | 8 | | 22 | 7 | | 23 | 7 | | 24 | 2 | | 25 | 6 | | 26 | 3 | | 27 | 6 | | 28 | 2 | | 29 | 10 | | 30 | 2 | | 31 | 3 | | 32 | 9 | | 33 | 9 | | 34 | 3 | | 35 | 2 | | 36 | 3 | | 37 | 13 | | 38 | 2 | | 39 | 1 | | 40 | 14 | | 41 | 22 | | 42 | 19 | | 43 | 6 | | 44 | 6 | | 45 | 1 | | 46 | 1 | | 47 | 3 | | 48 | 3 | | 49 | 3 |
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| 48.61% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.3541666666666667 | | totalSentences | 192 | | uniqueOpeners | 68 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 140 | | matches | | 0 | "Just the drip of condensation" | | 1 | "Then, a sound." | | 2 | "Then a skip." | | 3 | "Too many joints." | | 4 | "Only the scratch of bark," | | 5 | "Just a shift in the" | | 6 | "Just the wildflowers, the trees," |
| | ratio | 0.05 | |
| 62.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 55 | | totalSentences | 140 | | matches | | 0 | "She knew exactly where she" | | 1 | "She pressed a gloved hand" | | 2 | "They were ancient oaks, stripped" | | 3 | "It didn’t just shift; it" | | 4 | "They bloomed year-round in this" | | 5 | "Her watch ticked, but the" | | 6 | "She didn’t have time to" | | 7 | "She moved deeper." | | 8 | "She told herself it was" | | 9 | "She rubbed it through her" | | 10 | "She kept walking." | | 11 | "She pulled her scarf tighter." | | 12 | "They curved inward, like ribs." | | 13 | "She counted them out of" | | 14 | "She looked down at her" | | 15 | "Her knuckles were white around" | | 16 | "She worked at the restaurant" | | 17 | "She had fled Evan." | | 18 | "She had fled to London." | | 19 | "She wasn’t running anymore." |
| | ratio | 0.393 | |
| 77.86% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 107 | | totalSentences | 140 | | matches | | 0 | "Night air bit through her" | | 1 | "Richmond Park was a black" | | 2 | "Aurora Carter adjusted the strap" | | 3 | "She knew exactly where she" | | 4 | "The coordinates had been scrawled" | | 5 | "She pressed a gloved hand" | | 6 | "The deep crimson heartstone had" | | 7 | "Thumbnail-sized, heavy as a guilty" | | 8 | "The boundary markers weren’t stone" | | 9 | "They were ancient oaks, stripped" | | 10 | "Frost rimmed the grass ahead," | | 11 | "Aurora stepped between the trunks." | | 12 | "The air changed instantly." | | 13 | "It didn’t just shift; it" | | 14 | "Wildflowers pushed through the dark" | | 15 | "A cluster of silver-edged leaves" | | 16 | "They bloomed year-round in this" | | 17 | "Time felt loose." | | 18 | "Her watch ticked, but the" | | 19 | "The second hand dragged, then" |
| | ratio | 0.764 | |
| 35.71% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 140 | | matches | | | ratio | 0.007 | |
| 20.41% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 6 | | matches | | 0 | "Thumbnail-sized, heavy as a guilty thought, it had been given to her by a stranger who left it on the counter of the Golden Empress and vanished before she coul…" | | 1 | "They were ancient oaks, stripped and weathered into pillars that leaned into each other like tired elders." | | 2 | "A cluster of silver-edged leaves that shouldn’t exist outside May." | | 3 | "Nothing but shadows and the unnatural bloom of flowers that caught moonlight like glass." | | 4 | "She worked at the restaurant until two, delivered soups to students who barely looked up from their laptops, lived in a cramped flat above a bar that smelled of…" | | 5 | "The flowers at her feet were pressing inward, stems bending as if tracking her." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |