| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 2 | | adverbTags | | 0 | "Marcus said finally [finally]" | | 1 | "Silas said quietly [quietly]" |
| | dialogueSentences | 52 | | tagDensity | 0.346 | | leniency | 0.692 | | rawRatio | 0.111 | | effectiveRatio | 0.077 | |
| 89.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1374 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 49.05% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1374 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "throb" | | 1 | "scanning" | | 2 | "calculating" | | 3 | "weight" | | 4 | "comfortable" | | 5 | "flicker" | | 6 | "familiar" | | 7 | "whisper" | | 8 | "silence" | | 9 | "warmth" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "air was thick with" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "the air was thick with" | | 1 | "hung in the air" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 80 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 80 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1366 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 732 | | uniqueNames | 9 | | maxNameDensity | 2.73 | | worstName | "Marcus" | | maxWindowNameDensity | 6 | | worstWindowName | "Marcus" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Blackwood | 1 | | Marcus | 20 | | Reid | 1 | | Silas | 20 | | Dnieper | 1 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Blackwood" | | 3 | "Marcus" | | 4 | "Reid" | | 5 | "Silas" |
| | places | | 0 | "Soho" | | 1 | "Dnieper" | | 2 | "London" |
| | globalScore | 0.134 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.732 | | wordCount | 1366 | | matches | | 0 | "not much, but it’s a place to hang your coat" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 116 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 27.32 | | std | 18.82 | | cv | 0.689 | | sampleLengths | | 0 | 74 | | 1 | 59 | | 2 | 11 | | 3 | 48 | | 4 | 12 | | 5 | 22 | | 6 | 29 | | 7 | 24 | | 8 | 16 | | 9 | 48 | | 10 | 15 | | 11 | 2 | | 12 | 45 | | 13 | 41 | | 14 | 30 | | 15 | 3 | | 16 | 58 | | 17 | 17 | | 18 | 27 | | 19 | 61 | | 20 | 38 | | 21 | 47 | | 22 | 9 | | 23 | 41 | | 24 | 43 | | 25 | 9 | | 26 | 20 | | 27 | 36 | | 28 | 14 | | 29 | 10 | | 30 | 3 | | 31 | 67 | | 32 | 5 | | 33 | 46 | | 34 | 3 | | 35 | 22 | | 36 | 53 | | 37 | 22 | | 38 | 11 | | 39 | 7 | | 40 | 12 | | 41 | 33 | | 42 | 28 | | 43 | 15 | | 44 | 24 | | 45 | 10 | | 46 | 24 | | 47 | 11 | | 48 | 49 | | 49 | 12 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 80 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 139 | | matches | | |
| 19.70% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 116 | | ratio | 0.043 | | matches | | 0 | "Silas didn’t look up at first—he’d learned long ago that most entrances meant nothing." | | 1 | "The man stepped forward, and the dim light caught his face—hollow cheeks, a nose that had been broken more than once and set badly, eyes that had gone from calculating to haunted." | | 2 | "The bar was quiet—only a couple in the corner, heads bent together, and an old man nursing a pint near the window." | | 3 | "The name came back—a whisper in a language he’d tried to forget." | | 4 | "He thought about the years before the bar, before the knee, when he’d believed in something—country, justice, the thin line between order and chaos." |
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| 98.08% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 711 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.04219409282700422 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.009845288326300985 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 11.78 | | std | 8.71 | | cv | 0.74 | | sampleLengths | | 0 | 20 | | 1 | 21 | | 2 | 17 | | 3 | 16 | | 4 | 12 | | 5 | 10 | | 6 | 14 | | 7 | 8 | | 8 | 15 | | 9 | 5 | | 10 | 6 | | 11 | 32 | | 12 | 9 | | 13 | 7 | | 14 | 12 | | 15 | 9 | | 16 | 9 | | 17 | 4 | | 18 | 14 | | 19 | 15 | | 20 | 11 | | 21 | 13 | | 22 | 13 | | 23 | 3 | | 24 | 5 | | 25 | 10 | | 26 | 22 | | 27 | 11 | | 28 | 10 | | 29 | 5 | | 30 | 2 | | 31 | 22 | | 32 | 7 | | 33 | 16 | | 34 | 11 | | 35 | 3 | | 36 | 27 | | 37 | 9 | | 38 | 21 | | 39 | 3 | | 40 | 27 | | 41 | 31 | | 42 | 5 | | 43 | 12 | | 44 | 15 | | 45 | 12 | | 46 | 13 | | 47 | 48 | | 48 | 16 | | 49 | 22 |
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| 47.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.33620689655172414 | | totalSentences | 116 | | uniqueOpeners | 39 | |
| 46.95% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 71 | | matches | | 0 | "Then Marcus nodded, once." |
| | ratio | 0.014 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 71 | | matches | | 0 | "His limp flared tonight, a" | | 1 | "He stood there, scanning the" | | 2 | "He wore a cheap raincoat," | | 3 | "His posture had lost its" | | 4 | "He tried a smile that" | | 5 | "He just held the glass," | | 6 | "He set it down with" | | 7 | "He finished the whisky, pushed" | | 8 | "He saw the lines in" | | 9 | "He’d been thirty-three then, still" | | 10 | "He’d given an order." | | 11 | "Her body had washed up" | | 12 | "They sat in silence." | | 13 | "He didn’t usually, but tonight" | | 14 | "He thought about the years" |
| | ratio | 0.211 | |
| 16.34% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 71 | | matches | | 0 | "The neon-green sign above The" | | 1 | "Silas Blackwood stood behind the" | | 2 | "His limp flared tonight, a" | | 3 | "The door swung open, bringing" | | 4 | "A man hesitated on the" | | 5 | "Silas didn’t look up at" | | 6 | "He stood there, scanning the" | | 7 | "Silas set the glass down." | | 8 | "The rag hung from his" | | 9 | "The man stepped forward, and" | | 10 | "He wore a cheap raincoat," | | 11 | "His posture had lost its" | | 12 | "The name came out flat," | | 13 | "Marcus Reid stopped a few" | | 14 | "He tried a smile that" | | 15 | "Silas picked up another glass," | | 16 | "Marcus slid onto a stool," | | 17 | "Silas poured two fingers of" | | 18 | "Marcus took it, didn’t sip." | | 19 | "He just held the glass," |
| | ratio | 0.887 | |
| 70.42% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 71 | | matches | | 0 | "Now he believed in rent," |
| | ratio | 0.014 | |
| 68.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 3 | | matches | | 0 | "Silas Blackwood stood behind the bar, polishing a glass with a rag that had seen better decades." | | 1 | "His limp flared tonight, a dull throb in his left knee that promised rain by morning." | | 2 | "The man stepped forward, and the dim light caught his face—hollow cheeks, a nose that had been broken more than once and set badly, eyes that had gone from calc…" |
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| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 2 | | matches | | 0 | "Marcus slid, the leather creaking" | | 1 | "Marcus held up, not drinking" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 52 | | tagDensity | 0.154 | | leniency | 0.308 | | rawRatio | 0 | | effectiveRatio | 0 | |