| 46.15% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 4 | | adverbTags | | 0 | "Julian glanced around [around]" | | 1 | "Silas leaned back [back]" | | 2 | "Silas asked softly [softly]" | | 3 | "Silas said quietly [quietly]" |
| | dialogueSentences | 52 | | tagDensity | 0.442 | | leniency | 0.885 | | rawRatio | 0.174 | | effectiveRatio | 0.154 | |
| 92.49% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1332 | | totalAiIsmAdverbs | 2 | | 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) | |
| 51.20% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1332 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "warmth" | | 1 | "familiar" | | 2 | "throb" | | 3 | "reminder" | | 4 | "scanning" | | 5 | "lilt" | | 6 | "silence" | | 7 | "tracing" | | 8 | "flicked" | | 9 | "echo" | | 10 | "efficient" | | 11 | "pristine" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 67 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 67 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1330 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 54 | | wordCount | 871 | | uniqueNames | 16 | | maxNameDensity | 2.41 | | worstName | "Silas" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Julian" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Blackwood | 1 | | Amber | 1 | | Prague | 2 | | Carter | 1 | | Golden | 1 | | Empress | 1 | | Cardiff | 1 | | Julian | 16 | | Rory | 3 | | Silas | 21 | | Laphroaig | 1 | | Oxfords | 1 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Blackwood" | | 2 | "Amber" | | 3 | "Carter" | | 4 | "Julian" | | 5 | "Rory" | | 6 | "Silas" |
| | places | | 0 | "Soho" | | 1 | "Prague" | | 2 | "Cardiff" | | 3 | "London" |
| | globalScore | 0.294 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.752 | | wordCount | 1330 | | matches | | 0 | "not in distinguished patches, but in jagged, stressed streaks" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 26.6 | | std | 18.79 | | cv | 0.706 | | sampleLengths | | 0 | 18 | | 1 | 66 | | 2 | 8 | | 3 | 53 | | 4 | 34 | | 5 | 12 | | 6 | 40 | | 7 | 30 | | 8 | 21 | | 9 | 12 | | 10 | 55 | | 11 | 28 | | 12 | 26 | | 13 | 36 | | 14 | 30 | | 15 | 7 | | 16 | 4 | | 17 | 4 | | 18 | 64 | | 19 | 18 | | 20 | 60 | | 21 | 13 | | 22 | 39 | | 23 | 5 | | 24 | 19 | | 25 | 13 | | 26 | 56 | | 27 | 14 | | 28 | 30 | | 29 | 3 | | 30 | 63 | | 31 | 5 | | 32 | 3 | | 33 | 57 | | 34 | 42 | | 35 | 23 | | 36 | 35 | | 37 | 5 | | 38 | 41 | | 39 | 14 | | 40 | 34 | | 41 | 1 | | 42 | 33 | | 43 | 9 | | 44 | 50 | | 45 | 7 | | 46 | 33 | | 47 | 11 | | 48 | 24 | | 49 | 22 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 67 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 134 | | matches | (empty) | |
| 83.33% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 96 | | ratio | 0.021 | | matches | | 0 | "His left knee gave its familiar, dull throb—a damp-weather reminder of a rooftop in Prague thirty years past." | | 1 | "The tight muscle beneath his left eye twitched—the old tell." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 881 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 23 | | adverbRatio | 0.026106696935300794 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007945516458569807 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 13.85 | | std | 8.69 | | cv | 0.627 | | sampleLengths | | 0 | 18 | | 1 | 20 | | 2 | 28 | | 3 | 18 | | 4 | 8 | | 5 | 21 | | 6 | 14 | | 7 | 18 | | 8 | 12 | | 9 | 22 | | 10 | 8 | | 11 | 4 | | 12 | 15 | | 13 | 11 | | 14 | 14 | | 15 | 11 | | 16 | 19 | | 17 | 17 | | 18 | 4 | | 19 | 7 | | 20 | 5 | | 21 | 16 | | 22 | 25 | | 23 | 14 | | 24 | 28 | | 25 | 18 | | 26 | 8 | | 27 | 28 | | 28 | 8 | | 29 | 13 | | 30 | 17 | | 31 | 7 | | 32 | 2 | | 33 | 2 | | 34 | 4 | | 35 | 7 | | 36 | 28 | | 37 | 12 | | 38 | 17 | | 39 | 15 | | 40 | 3 | | 41 | 36 | | 42 | 24 | | 43 | 7 | | 44 | 6 | | 45 | 28 | | 46 | 11 | | 47 | 5 | | 48 | 9 | | 49 | 10 |
| |
| 58.68% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3958333333333333 | | totalSentences | 96 | | uniqueOpeners | 38 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 65 | | matches | | 0 | "His left knee gave its" | | 1 | "She tugged at the sleeve" | | 2 | "He smoothed a hand over" | | 3 | "His voice sat an octave" | | 4 | "He bypassed the handshake, clapping" | | 5 | "They retreated to a booth" | | 6 | "He slid out of the" | | 7 | "He caught himself instantly, his" | | 8 | "He smoothed his tie with" | | 9 | "He saw the silver creeping" | | 10 | "He saw the faint blue" | | 11 | "He pushed the heavy oak" | | 12 | "He reached out, took his" | | 13 | "He ran his thumb over" |
| | ratio | 0.215 | |
| 6.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 65 | | matches | | 0 | "Rain slicked the Soho pavement," | | 1 | "Silas Blackwood wiped down the" | | 2 | "His left knee gave its" | | 3 | "The bell above the heavy" | | 4 | "Aurora Carter looked up from" | | 5 | "She tugged at the sleeve" | | 6 | "A tall man stepped over" | | 7 | "He smoothed a hand over" | | 8 | "Silas froze, the rag motionless" | | 9 | "The newcomer stood unmoving, his" | | 10 | "The slouch that had defined" | | 11 | "The soft, apologetic curve of" | | 12 | "the man said" | | 13 | "His voice sat an octave" | | 14 | "Silas dragged his left leg" | | 15 | "Julian stepped forward, offering a" | | 16 | "The gesture was stiff, formal." | | 17 | "Silas looked down at the" | | 18 | "He bypassed the handshake, clapping" | | 19 | "They retreated to a booth" |
| | ratio | 0.908 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 1 | | matches | | 0 | "Julian turned toward the door, his movements fluid, efficient, devoid of the warmth that used to make him laugh until he choked on bad lager." |
| |
| 59.78% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 3 | | matches | | 0 | "Julian took, his thumb tracing the rim of the glass" | | 1 | "Silas took, the peat burning his throat" | | 2 | "Rory asked, her voice cautious" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 2 | | fancyTags | | 0 | "Silas chuckled (chuckle)" | | 1 | "Julian whispered (whisper)" |
| | dialogueSentences | 52 | | tagDensity | 0.192 | | leniency | 0.385 | | rawRatio | 0.2 | | effectiveRatio | 0.077 | |