| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2783 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 89.22% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2783 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "weight" | | 1 | "silence" | | 2 | "tension" |
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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 | 109 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 109 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 203 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2784 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 71 | | wordCount | 1366 | | uniqueNames | 11 | | maxNameDensity | 2.2 | | worstName | "Catrin" | | maxWindowNameDensity | 5 | | worstWindowName | "Catrin" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Blackwood | 1 | | Rory | 21 | | Silas | 12 | | Central | 1 | | Europe | 1 | | Catrin | 30 | | Whitechapel | 1 | | Tuesday | 1 | | Union | 1 |
| | persons | | 0 | "Blackwood" | | 1 | "Rory" | | 2 | "Silas" | | 3 | "Catrin" | | 4 | "Union" |
| | places | | 0 | "Raven" | | 1 | "Europe" | | 2 | "Whitechapel" |
| | globalScore | 0.402 | | windowScore | 0 | |
| 56.25% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 80 | | glossingSentenceCount | 3 | | matches | | 0 | "as if searching for a border she recognised" | | 1 | "seemed closer in the low light, the men and women in them holding poses that had outlasted their lives" | | 2 | "looked like armour so much as a shed skin" |
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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 | 2784 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 203 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 156 | | mean | 17.85 | | std | 15.88 | | cv | 0.89 | | sampleLengths | | 0 | 78 | | 1 | 50 | | 2 | 42 | | 3 | 43 | | 4 | 2 | | 5 | 10 | | 6 | 1 | | 7 | 16 | | 8 | 16 | | 9 | 31 | | 10 | 45 | | 11 | 3 | | 12 | 7 | | 13 | 4 | | 14 | 11 | | 15 | 2 | | 16 | 7 | | 17 | 10 | | 18 | 4 | | 19 | 17 | | 20 | 23 | | 21 | 3 | | 22 | 2 | | 23 | 3 | | 24 | 8 | | 25 | 8 | | 26 | 23 | | 27 | 9 | | 28 | 8 | | 29 | 15 | | 30 | 2 | | 31 | 3 | | 32 | 14 | | 33 | 24 | | 34 | 2 | | 35 | 9 | | 36 | 38 | | 37 | 10 | | 38 | 28 | | 39 | 30 | | 40 | 25 | | 41 | 28 | | 42 | 6 | | 43 | 26 | | 44 | 14 | | 45 | 18 | | 46 | 4 | | 47 | 5 | | 48 | 20 | | 49 | 36 |
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| 98.83% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 109 | | matches | | 0 | "been said" | | 1 | "been left" | | 2 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 224 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 203 | | ratio | 0.01 | | matches | | 0 | "He lifted a bottle with his right hand; the silver signet ring clicked against glass." | | 1 | "The neon outside no longer smeared; it held its colour against the dark." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1369 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.02337472607742878 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0014609203798392988 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 203 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 203 | | mean | 13.71 | | std | 11.3 | | cv | 0.824 | | sampleLengths | | 0 | 22 | | 1 | 20 | | 2 | 15 | | 3 | 21 | | 4 | 14 | | 5 | 13 | | 6 | 9 | | 7 | 14 | | 8 | 13 | | 9 | 15 | | 10 | 14 | | 11 | 10 | | 12 | 17 | | 13 | 16 | | 14 | 2 | | 15 | 4 | | 16 | 6 | | 17 | 1 | | 18 | 7 | | 19 | 3 | | 20 | 6 | | 21 | 16 | | 22 | 5 | | 23 | 10 | | 24 | 16 | | 25 | 2 | | 26 | 4 | | 27 | 12 | | 28 | 27 | | 29 | 3 | | 30 | 7 | | 31 | 4 | | 32 | 5 | | 33 | 6 | | 34 | 2 | | 35 | 7 | | 36 | 10 | | 37 | 4 | | 38 | 17 | | 39 | 23 | | 40 | 3 | | 41 | 2 | | 42 | 3 | | 43 | 8 | | 44 | 8 | | 45 | 23 | | 46 | 9 | | 47 | 8 | | 48 | 15 | | 49 | 2 |
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| 41.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.28078817733990147 | | totalSentences | 203 | | uniqueOpeners | 57 | |
| 32.05% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 104 | | matches | | 0 | "Bright blue eyes held the" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 104 | | matches | | 0 | "Her black hair hung straight," | | 1 | "She turned an empty pint" | | 2 | "He lifted a bottle with" | | 3 | "She let the door close" | | 4 | "She stopped beside the empty" | | 5 | "He set them down and" | | 6 | "She unbuttoned the coat." | | 7 | "Her hair, which Rory remembered" | | 8 | "They each took a drink." | | 9 | "He did not speak." | | 10 | "She did not press." | | 11 | "They sat with the pints." | | 12 | "He caught Rory’s eye, a" | | 13 | "She looked at her hands," | | 14 | "His hazel eyes passed over" | | 15 | "They both reached for their" | | 16 | "They lapsed into a quiet" | | 17 | "He placed them with care," |
| | ratio | 0.173 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 97 | | totalSentences | 104 | | matches | | 0 | "The rain turned the pavement" | | 1 | "Maps of cities that had" | | 2 | "Rory sat with her back" | | 3 | "Her black hair hung straight," | | 4 | "She turned an empty pint" | | 5 | "The small crescent scar on" | | 6 | "Silas Blackwood stood at the" | | 7 | "He lifted a bottle with" | | 8 | "The street door opened on" | | 9 | "A woman in a long" | | 10 | "She let the door close" | | 11 | "Rory's head came up." | | 12 | "Catrin walked the length of" | | 13 | "The coat swung." | | 14 | "She stopped beside the empty" | | 15 | "Rory nodded at the stool." | | 16 | "Silas was already there, two" | | 17 | "He set them down and" | | 18 | "She unbuttoned the coat." | | 19 | "Her hair, which Rory remembered" |
| | ratio | 0.933 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 104 | | matches | (empty) | | ratio | 0 | |
| 51.95% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 7 | | matches | | 0 | "Maps of cities that had changed names covered the walls, their paper yellowed, corners lifting." | | 1 | "Underneath, a dark suit, the kind that said meetings and billable hours." | | 2 | "Catrin glanced at Silas, who was lining up glasses with the precision of someone who had lined up other things in other rooms." | | 3 | "Catrin looked at the maps, the photographs, the man behind the bar who had the air of someone who had once had other maps, other photographs." | | 4 | "The conversation continued in the pauses as much as the words, the tension of then and now sitting between them like a third person who had never left the Union…" | | 5 | "The photographs seemed closer in the low light, the men and women in them holding poses that had outlasted their lives." | | 6 | "The conversation did not so much continue as settle around them, a third presence made of old tutorials and unposted scarves, of trains caught and trains not ta…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |