| 63.01% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 27 | | adverbTagCount | 5 | | adverbTags | | 0 | "Eva tried again [again]" | | 1 | "Eva gestured vaguely [vaguely]" | | 2 | "Eva said finally [finally]" | | 3 | "you give just [just]" | | 4 | "Eva said quietly [quietly]" |
| | dialogueSentences | 73 | | tagDensity | 0.37 | | leniency | 0.74 | | rawRatio | 0.185 | | effectiveRatio | 0.137 | |
| 92.64% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1358 | | 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) | |
| 74.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1358 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "footsteps" | | 1 | "weight" | | 2 | "silence" | | 3 | "trembled" | | 4 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 83 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 83 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 124 | | 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 | 1344 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 977 | | uniqueNames | 10 | | maxNameDensity | 2.56 | | worstName | "Eva" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 3 | | Aurora | 16 | | Rory | 4 | | Silas | 4 | | Eva | 25 | | Cardiff | 2 | | You | 1 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Aurora" | | 3 | "Rory" | | 4 | "Silas" | | 5 | "Eva" | | 6 | "You" |
| | places | | 0 | "Soho" | | 1 | "Cardiff" | | 2 | "London" |
| | globalScore | 0.221 | | windowScore | 0.167 | |
| 59.09% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like the right place to stay—solid" | | 1 | "looked like she wanted to say something e" |
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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 | 1344 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 124 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 68 | | mean | 19.76 | | std | 19.08 | | cv | 0.965 | | sampleLengths | | 0 | 64 | | 1 | 40 | | 2 | 1 | | 3 | 31 | | 4 | 75 | | 5 | 11 | | 6 | 5 | | 7 | 61 | | 8 | 21 | | 9 | 2 | | 10 | 19 | | 11 | 4 | | 12 | 52 | | 13 | 13 | | 14 | 4 | | 15 | 36 | | 16 | 17 | | 17 | 55 | | 18 | 7 | | 19 | 15 | | 20 | 5 | | 21 | 9 | | 22 | 2 | | 23 | 8 | | 24 | 32 | | 25 | 3 | | 26 | 37 | | 27 | 3 | | 28 | 18 | | 29 | 1 | | 30 | 10 | | 31 | 37 | | 32 | 2 | | 33 | 6 | | 34 | 2 | | 35 | 51 | | 36 | 21 | | 37 | 5 | | 38 | 37 | | 39 | 29 | | 40 | 2 | | 41 | 3 | | 42 | 50 | | 43 | 1 | | 44 | 17 | | 45 | 6 | | 46 | 3 | | 47 | 49 | | 48 | 3 | | 49 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 83 | | matches | (empty) | |
| 99.50% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 199 | | matches | | 0 | "was wiping" | | 1 | "wasn't going" | | 2 | "was learning" |
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| 4.61% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 124 | | ratio | 0.048 | | matches | | 0 | "Silas had taught her that much—always let them come to you, observe first." | | 1 | "She knew it the way you know the sound of your own heartbeat—embedded, involuntary, unwelcome." | | 2 | "Eva had gained weight—or lost it—hard to tell with winter coats." | | 3 | "It felt like the right place to stay—solid, protective, a barrier between then and now." | | 4 | "The way she said it must have communicated something Eva recognized, something old between them that hadn't changed. Eva looked up, and for a moment she was twenty-one again, sitting in the university library, saying aurora, you can't keep doing this to yourself, you can't keep choosing people who—" | | 5 | "It's just—you still do that." |
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| 98.64% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 746 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.04155495978552279 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.014745308310991957 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 124 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 124 | | mean | 10.84 | | std | 10.33 | | cv | 0.953 | | sampleLengths | | 0 | 10 | | 1 | 30 | | 2 | 24 | | 3 | 5 | | 4 | 1 | | 5 | 13 | | 6 | 12 | | 7 | 9 | | 8 | 1 | | 9 | 12 | | 10 | 4 | | 11 | 15 | | 12 | 18 | | 13 | 8 | | 14 | 49 | | 15 | 8 | | 16 | 3 | | 17 | 5 | | 18 | 9 | | 19 | 8 | | 20 | 9 | | 21 | 11 | | 22 | 24 | | 23 | 9 | | 24 | 12 | | 25 | 2 | | 26 | 12 | | 27 | 7 | | 28 | 4 | | 29 | 30 | | 30 | 7 | | 31 | 15 | | 32 | 8 | | 33 | 5 | | 34 | 4 | | 35 | 10 | | 36 | 7 | | 37 | 7 | | 38 | 12 | | 39 | 3 | | 40 | 8 | | 41 | 6 | | 42 | 4 | | 43 | 25 | | 44 | 19 | | 45 | 7 | | 46 | 7 | | 47 | 9 | | 48 | 6 | | 49 | 5 |
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| 52.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.3709677419354839 | | totalSentences | 124 | | uniqueOpeners | 46 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 74 | | matches | | 0 | "She was wiping down the" | | 1 | "She didn't look up immediately." | | 2 | "She knew that voice." | | 3 | "She knew it the way" | | 4 | "Her eyes were the same:" | | 5 | "It felt like the right" | | 6 | "She was twenty-seven now, same" | | 7 | "She finally met Rory's eyes" | | 8 | "She watched Eva drink half" | | 9 | "She wasn't going to defend" | | 10 | "Her voice came out steady," | | 11 | "She shook her head" | | 12 | "She stopped herself" | | 13 | "It's just—you still do that." | | 14 | "They sat with that, with" | | 15 | "I help out downstairs when" | | 16 | "It's small, but it's mine." | | 17 | "I don't have to explain" | | 18 | "I don't have" | | 19 | "I mean, I'm in London" |
| | ratio | 0.297 | |
| 0.54% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 74 | | matches | | 0 | "The Raven's Nest smelled of" | | 1 | "Aurora had grown used to" | | 2 | "She was wiping down the" | | 3 | "She didn't look up immediately." | | 4 | "Silas had taught her that" | | 5 | "The footsteps were steady, confident," | | 6 | "Someone who knew the place" | | 7 | "The voice cracked on the" | | 8 | "She knew that voice." | | 9 | "She knew it the way" | | 10 | "Eva stood three feet from" | | 11 | "Blonde now, or maybe that" | | 12 | "Cardiff had been six years" | | 13 | "Eva tried again, when Rory" | | 14 | "The words came out flat," | | 15 | "Aurora set down the cloth" | | 16 | "Eva had gained weight—or lost" | | 17 | "Her eyes were the same:" | | 18 | "Eva let out a breath," | | 19 | "The silence between them filled" |
| | ratio | 0.919 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 5 | | matches | | 0 | "Cardiff had been six years ago, but the face beneath the new hair was the same face that had sat across from her in a thousand lectures, that had held her hair …" | | 1 | "Her eyes were the same: too bright, too searching, the eyes of someone who always needed to understand everything except the things that mattered." | | 2 | "The way she said it must have communicated something Eva recognized, something old between them that hadn't changed. Eva looked up, and for a moment she was twe…" | | 3 | "They sat with that, with the weight of all the years between Cardiff and this bar in Soho. The television changed channels,Programme to programme, noise to nois…" | | 4 | "The door opened again, letting in more cold air and the sound of the street. Two men came in, regulars, Silas would know them. Aurora straightened, automaticall…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 27 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 73 | | tagDensity | 0.096 | | leniency | 0.192 | | rawRatio | 0 | | effectiveRatio | 0 | |