| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 26 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 64 | | tagDensity | 0.406 | | leniency | 0.813 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1251 | | totalAiIsmAdverbs | 1 | | 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) | |
| 96.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1251 | | totalAiIsms | 1 | | found | | | highlights | | |
| 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 | 82 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 82 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 118 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1244 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 26 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 53 | | wordCount | 885 | | uniqueNames | 14 | | maxNameDensity | 2.37 | | worstName | "Megan" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Megan" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Thursday | 1 | | Davies | 1 | | Megan | 21 | | Rory | 17 | | Silas | 4 | | London | 1 | | Golden | 1 | | Empress | 1 | | Started | 1 | | Pre-Law | 1 | | November | 1 | | Eva | 1 |
| | persons | | 0 | "Raven" | | 1 | "Davies" | | 2 | "Megan" | | 3 | "Rory" | | 4 | "Silas" | | 5 | "Empress" | | 6 | "Eva" |
| | places | | | globalScore | 0.314 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 50 | | glossingSentenceCount | 1 | | matches | | 0 | "not quite wet—the particular expression of someone who had rehearsed this conversation and found the rehearsal useless" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.804 | | wordCount | 1244 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 118 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 66 | | mean | 18.85 | | std | 17.69 | | cv | 0.939 | | sampleLengths | | 0 | 61 | | 1 | 48 | | 2 | 3 | | 3 | 25 | | 4 | 1 | | 5 | 14 | | 6 | 87 | | 7 | 7 | | 8 | 45 | | 9 | 3 | | 10 | 35 | | 11 | 17 | | 12 | 15 | | 13 | 2 | | 14 | 27 | | 15 | 5 | | 16 | 5 | | 17 | 27 | | 18 | 41 | | 19 | 7 | | 20 | 17 | | 21 | 7 | | 22 | 4 | | 23 | 43 | | 24 | 4 | | 25 | 14 | | 26 | 24 | | 27 | 10 | | 28 | 23 | | 29 | 5 | | 30 | 2 | | 31 | 1 | | 32 | 31 | | 33 | 10 | | 34 | 20 | | 35 | 10 | | 36 | 23 | | 37 | 4 | | 38 | 31 | | 39 | 12 | | 40 | 25 | | 41 | 19 | | 42 | 3 | | 43 | 24 | | 44 | 2 | | 45 | 20 | | 46 | 26 | | 47 | 7 | | 48 | 35 | | 49 | 8 |
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| 96.71% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 82 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 154 | | matches | | |
| 21.79% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 118 | | ratio | 0.042 | | matches | | 0 | "The Thursday crowd was thin—two men nursing whiskies by the window, a woman alone with a crossword—and the green neon from outside painted the floor in sick-ward light." | | 1 | "She was the same—that was the first thought." | | 2 | "\"Passed the bar in November.\" A beat of something—pride, or an apology for it." | | 3 | "Megan's eyes were bright and not quite wet—the particular expression of someone who had rehearsed this conversation and found the rehearsal useless." | | 4 | "That was the thing she found strange, sitting here now with the years spread out between them like a map she'd never unfolded all the way—she couldn't locate any anger." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 895 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.030167597765363128 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0067039106145251395 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 118 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 118 | | mean | 10.54 | | std | 8.67 | | cv | 0.822 | | sampleLengths | | 0 | 13 | | 1 | 18 | | 2 | 30 | | 3 | 20 | | 4 | 28 | | 5 | 3 | | 6 | 4 | | 7 | 16 | | 8 | 5 | | 9 | 1 | | 10 | 6 | | 11 | 8 | | 12 | 31 | | 13 | 8 | | 14 | 24 | | 15 | 24 | | 16 | 6 | | 17 | 1 | | 18 | 19 | | 19 | 15 | | 20 | 11 | | 21 | 3 | | 22 | 7 | | 23 | 25 | | 24 | 3 | | 25 | 5 | | 26 | 12 | | 27 | 9 | | 28 | 5 | | 29 | 1 | | 30 | 2 | | 31 | 4 | | 32 | 2 | | 33 | 21 | | 34 | 5 | | 35 | 5 | | 36 | 25 | | 37 | 2 | | 38 | 6 | | 39 | 35 | | 40 | 7 | | 41 | 14 | | 42 | 3 | | 43 | 7 | | 44 | 4 | | 45 | 7 | | 46 | 22 | | 47 | 14 | | 48 | 4 | | 49 | 9 |
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| 48.87% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3389830508474576 | | totalSentences | 118 | | uniqueOpeners | 40 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 67 | | matches | | 0 | "Then she heard a voice." | | 1 | "More like recognition held at" | | 2 | "Just something without a clean" |
| | ratio | 0.045 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 67 | | matches | | 0 | "She heard the brief surge" | | 1 | "She knew it before she" | | 2 | "She was the same—that was" | | 3 | "She looked the same the" | | 4 | "She stopped at the bar" | | 5 | "She gestured at the room," | | 6 | "He didn't say anything, just" | | 7 | "She glanced at Rory's glass." | | 8 | "She took the stool and" | | 9 | "She'd hacked it off herself" | | 10 | "She was aware of that" | | 11 | "She turned to face Megan" | | 12 | "It wasn't a question." | | 13 | "It was the kindness of" | | 14 | "It always arrived dressed as" | | 15 | "She didn't resent Megan for" |
| | ratio | 0.239 | |
| 27.16% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 67 | | matches | | 0 | "The Raven's Nest was the" | | 1 | "Rory sat at the far" | | 2 | "Silas was behind the bar," | | 3 | "The Thursday crowd was thin—two" | | 4 | "The door opened." | | 5 | "Rory didn't look up." | | 6 | "She heard the brief surge" | | 7 | "She knew it before she" | | 8 | "Something in her chest did" | | 9 | "Megan Davies stood three feet" | | 10 | "She was the same—that was" | | 11 | "She looked the same the" | | 12 | "Rory set down her glass" | | 13 | "Megan crossed the room in" | | 14 | "She stopped at the bar" | | 15 | "Megan's gaze dropped to her" | | 16 | "She gestured at the room," | | 17 | "Silas set down the tumbler." | | 18 | "He didn't say anything, just" | | 19 | "Megan told him, unclasping her" |
| | ratio | 0.866 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 67 | | matches | (empty) | | ratio | 0 | |
| 32.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 4 | | matches | | 0 | "The Raven's Nest was the kind of place that collected people like sediment." | | 1 | "Silas was behind the bar, polishing a tumbler with the slow attention of someone who had nowhere else to be." | | 2 | "Megan's eyes were bright and not quite wet—the particular expression of someone who had rehearsed this conversation and found the rehearsal useless." | | 3 | "The could still, the not too late, the whole architecture of reassurance that people offered when what they meant was: I don't understand the choice you made, a…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 26 | | uselessAdditionCount | 1 | | matches | | 0 | "She turned, the bar stool squeaking under the shift of her weight" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 64 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0 | | effectiveRatio | 0 | |