| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 1 | | adverbTags | | 0 | "Tom called again [again]" |
| | dialogueSentences | 220 | | tagDensity | 0.105 | | leniency | 0.209 | | rawRatio | 0.043 | | effectiveRatio | 0.009 | |
| 97.91% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2395 | | 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) | |
| 85.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2395 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "warmth" | | 1 | "weight" | | 2 | "silence" | | 3 | "remarkable" | | 4 | "tracing" | | 5 | "flicker" |
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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 | 139 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 139 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 336 | | 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 | 2394 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 49 | | unquotedAttributions | 0 | | matches | (empty) | |
| 60.64% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 52 | | wordCount | 1175 | | uniqueNames | 8 | | maxNameDensity | 1.79 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Nest | 1 | | Golden | 1 | | Empress | 1 | | Cardiff | 2 | | Rory | 21 | | Tom | 16 | | Silas | 9 | | Soho | 1 |
| | persons | | 0 | "Nest" | | 1 | "Rory" | | 2 | "Tom" | | 3 | "Silas" |
| | places | | 0 | "Golden" | | 1 | "Cardiff" | | 2 | "Soho" |
| | globalScore | 0.606 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 86 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared beside them with a small plate of bread, which he set in front of Rory" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.418 | | wordCount | 2394 | | matches | | 0 | "not as a wall but as a pile of small decisions" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 336 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 250 | | mean | 9.58 | | std | 11.35 | | cv | 1.186 | | sampleLengths | | 0 | 44 | | 1 | 48 | | 2 | 9 | | 3 | 9 | | 4 | 40 | | 5 | 14 | | 6 | 4 | | 7 | 7 | | 8 | 7 | | 9 | 1 | | 10 | 52 | | 11 | 1 | | 12 | 62 | | 13 | 24 | | 14 | 8 | | 15 | 3 | | 16 | 2 | | 17 | 9 | | 18 | 30 | | 19 | 7 | | 20 | 5 | | 21 | 19 | | 22 | 5 | | 23 | 3 | | 24 | 5 | | 25 | 2 | | 26 | 25 | | 27 | 7 | | 28 | 8 | | 29 | 7 | | 30 | 10 | | 31 | 8 | | 32 | 4 | | 33 | 3 | | 34 | 4 | | 35 | 4 | | 36 | 40 | | 37 | 4 | | 38 | 21 | | 39 | 4 | | 40 | 5 | | 41 | 3 | | 42 | 41 | | 43 | 6 | | 44 | 11 | | 45 | 4 | | 46 | 1 | | 47 | 3 | | 48 | 9 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 139 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 210 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 2 | | flaggedSentences | 3 | | totalSentences | 336 | | ratio | 0.009 | | matches | | 0 | "She had known it at sixteen, when it called across the schoolyard and asked if she had done the history reading; at twenty, when it shouted over music in a Cardiff flat." | | 1 | "The man at the next table asked Silas for another pint; Silas poured it, the tap hissing in the space between them." | | 2 | "The years sat between them, not as a wall but as a pile of small decisions—unreturned calls, birthdays passed, news carried through other people’s kitchens." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1184 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.022804054054054054 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 336 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 336 | | mean | 7.13 | | std | 6.42 | | cv | 0.9 | | sampleLengths | | 0 | 11 | | 1 | 7 | | 2 | 26 | | 3 | 22 | | 4 | 8 | | 5 | 18 | | 6 | 9 | | 7 | 9 | | 8 | 5 | | 9 | 16 | | 10 | 7 | | 11 | 12 | | 12 | 8 | | 13 | 6 | | 14 | 4 | | 15 | 7 | | 16 | 7 | | 17 | 1 | | 18 | 9 | | 19 | 32 | | 20 | 11 | | 21 | 1 | | 22 | 2 | | 23 | 12 | | 24 | 17 | | 25 | 14 | | 26 | 8 | | 27 | 9 | | 28 | 10 | | 29 | 14 | | 30 | 8 | | 31 | 3 | | 32 | 2 | | 33 | 9 | | 34 | 7 | | 35 | 10 | | 36 | 13 | | 37 | 7 | | 38 | 3 | | 39 | 2 | | 40 | 8 | | 41 | 11 | | 42 | 5 | | 43 | 3 | | 44 | 5 | | 45 | 2 | | 46 | 6 | | 47 | 11 | | 48 | 8 | | 49 | 3 |
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| 42.56% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 25 | | diversityRatio | 0.20833333333333334 | | totalSentences | 336 | | uniqueOpeners | 70 | |
| 28.99% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 115 | | matches | | 0 | "Then his hand slipped from" |
| | ratio | 0.009 | |
| 66.96% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 44 | | totalSentences | 115 | | matches | | 0 | "She crossed between the stools." | | 1 | "His coat hung damp from" | | 2 | "She knew the voice before" | | 3 | "She had known it at" | | 4 | "She had known it last" | | 5 | "He had been broad once," | | 6 | "His hair, once a copper" | | 7 | "His cheeks looked hollow beneath" | | 8 | "He wore a dark wool" | | 9 | "His gaze moved from Rory" | | 10 | "He picked up a cloth" | | 11 | "She kept her hand on" | | 12 | "His eyes dropped to her" | | 13 | "She tucked her hand into" | | 14 | "She heard the old rhythm" | | 15 | "It landed between them with" | | 16 | "Its lights smeared across the" | | 17 | "She pulled out the chair" | | 18 | "He seemed to be making" | | 19 | "He turned the pint by" |
| | ratio | 0.383 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 106 | | totalSentences | 115 | | matches | | 0 | "The green neon raven above" | | 1 | "Rain shone on the pavement" | | 2 | "Rory wiped her shoes on" | | 3 | "The bar held its usual" | | 4 | "Silas stood behind the counter," | | 5 | "She crossed between the stools." | | 6 | "The man at the window" | | 7 | "His coat hung damp from" | | 8 | "Rory said, setting down the" | | 9 | "The man looked up." | | 10 | "She knew the voice before" | | 11 | "She had known it at" | | 12 | "She had known it last" | | 13 | "The chair leg caught on" | | 14 | "He had been broad once," | | 15 | "His hair, once a copper" | | 16 | "A thin white line crossed" | | 17 | "His cheeks looked hollow beneath" | | 18 | "He wore a dark wool" | | 19 | "A strip of pale skin" |
| | ratio | 0.922 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 115 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 20 | | fancyCount | 1 | | fancyTags | | 0 | "he continued (continue)" |
| | dialogueSentences | 220 | | tagDensity | 0.091 | | leniency | 0.182 | | rawRatio | 0.05 | | effectiveRatio | 0.009 | |