| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 95.96% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2474 | | totalAiIsmAdverbs | 2 | | 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) | |
| 5.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2474 | | totalAiIsms | 47 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | | | 23 | | | 24 | | | 25 | |
| | highlights | | 0 | "electric" | | 1 | "familiar" | | 2 | "reminder" | | 3 | "weight" | | 4 | "footsteps" | | 5 | "scanned" | | 6 | "traced" | | 7 | "measured" | | 8 | "race" | | 9 | "silence" | | 10 | "comfortable" | | 11 | "tapestry" | | 12 | "implication" | | 13 | "shattered" | | 14 | "fractured" | | 15 | "navigate" | | 16 | "calculate" | | 17 | "structure" | | 18 | "trembled" | | 19 | "tension" | | 20 | "predictable" | | 21 | "echoed" | | 22 | "calculating" | | 23 | "flicker" | | 24 | "pulsed" | | 25 | "unspoken" |
| |
| 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 | 405 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 5 | | hedgeCount | 0 | | narrationSentences | 405 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 405 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2474 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 81 | | wordCount | 2474 | | uniqueNames | 8 | | maxNameDensity | 2.67 | | worstName | "You" | | maxWindowNameDensity | 7 | | worstWindowName | "You" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Thursday | 1 | | November | 1 | | Prague | 2 | | Silas | 8 | | You | 66 |
| | persons | | | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "November" | | 3 | "Prague" |
| | globalScore | 0.166 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 188 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a question mark" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 2474 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 405 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 85 | | mean | 29.11 | | std | 17.66 | | cv | 0.607 | | sampleLengths | | 0 | 92 | | 1 | 77 | | 2 | 17 | | 3 | 74 | | 4 | 9 | | 5 | 17 | | 6 | 55 | | 7 | 9 | | 8 | 8 | | 9 | 31 | | 10 | 11 | | 11 | 29 | | 12 | 33 | | 13 | 20 | | 14 | 9 | | 15 | 24 | | 16 | 35 | | 17 | 12 | | 18 | 36 | | 19 | 4 | | 20 | 26 | | 21 | 38 | | 22 | 3 | | 23 | 21 | | 24 | 35 | | 25 | 18 | | 26 | 12 | | 27 | 22 | | 28 | 38 | | 29 | 33 | | 30 | 3 | | 31 | 36 | | 32 | 32 | | 33 | 16 | | 34 | 29 | | 35 | 14 | | 36 | 47 | | 37 | 3 | | 38 | 50 | | 39 | 22 | | 40 | 39 | | 41 | 31 | | 42 | 41 | | 43 | 17 | | 44 | 41 | | 45 | 12 | | 46 | 20 | | 47 | 23 | | 48 | 32 | | 49 | 43 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 405 | | matches | | 0 | "is broken" | | 1 | "was yellowed" | | 2 | "were hurried" | | 3 | "are gone" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 527 | | matches | | 0 | "was holding" | | 1 | "were breaking" | | 2 | "were building" | | 3 | "were becoming" | | 4 | "was surviving" | | 5 | "were running" | | 6 | "was beginning" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 405 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2475 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 41 | | adverbRatio | 0.016565656565656565 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.0032323232323232323 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 405 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 405 | | mean | 6.11 | | std | 3.4 | | cv | 0.557 | | sampleLengths | | 0 | 25 | | 1 | 27 | | 2 | 11 | | 3 | 16 | | 4 | 13 | | 5 | 15 | | 6 | 20 | | 7 | 17 | | 8 | 12 | | 9 | 6 | | 10 | 7 | | 11 | 9 | | 12 | 4 | | 13 | 2 | | 14 | 2 | | 15 | 6 | | 16 | 11 | | 17 | 11 | | 18 | 14 | | 19 | 8 | | 20 | 6 | | 21 | 18 | | 22 | 9 | | 23 | 6 | | 24 | 7 | | 25 | 4 | | 26 | 4 | | 27 | 5 | | 28 | 9 | | 29 | 24 | | 30 | 13 | | 31 | 5 | | 32 | 4 | | 33 | 3 | | 34 | 5 | | 35 | 16 | | 36 | 7 | | 37 | 5 | | 38 | 3 | | 39 | 5 | | 40 | 6 | | 41 | 7 | | 42 | 6 | | 43 | 7 | | 44 | 3 | | 45 | 3 | | 46 | 3 | | 47 | 6 | | 48 | 8 | | 49 | 4 |
| |
| 25.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 184 | | diversityRatio | 0.11604938271604938 | | totalSentences | 405 | | uniqueOpeners | 47 | |
| 16.88% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 395 | | matches | | 0 | "Somewhere you would not recognize." | | 1 | "Elsewhere is a comfortable word." |
| | ratio | 0.005 | |
| 5.32% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 212 | | totalSentences | 395 | | matches | | 0 | "His left leg carried a" | | 1 | "He did not look up" | | 2 | "He knew the weight of" | | 3 | "He knew the rhythm of" | | 4 | "She stepped into the amber" | | 5 | "You look like you are" | | 6 | "I am waiting for a" | | 7 | "You should fix it." | | 8 | "His hazel eyes tracked the" | | 9 | "He remembered the girl who" | | 10 | "He remembered the way she" | | 11 | "I fixed it in November." | | 12 | "You were not here." | | 13 | "I was elsewhere." | | 14 | "He poured a measure of" | | 15 | "He kept his hands visible." | | 16 | "It covers a multitude of" | | 17 | "Her fingers traced the rim" | | 18 | "She studied the maps on" | | 19 | "It covers a multitude of" |
| | ratio | 0.537 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 374 | | totalSentences | 395 | | matches | | 0 | "The green neon sign above" | | 1 | "Maps pinned to the walls" | | 2 | "The place held its breath," | | 3 | "Silas stood behind the scarred" | | 4 | "His left leg carried a" | | 5 | "The silver signet ring on" | | 6 | "He did not look up" | | 7 | "He knew the weight of" | | 8 | "He knew the rhythm of" | | 9 | "The footsteps stopped at the" | | 10 | "She stepped into the amber" | | 11 | "The bright blue eyes scanned" | | 12 | "A small crescent scar traced" | | 13 | "The fabric of her coat" | | 14 | "The posture carried a different" | | 15 | "Years had filed down the" | | 16 | "You look like you are" | | 17 | "I am waiting for a" | | 18 | "The tap is broken on" | | 19 | "You should fix it." |
| | ratio | 0.947 | |
| 63.29% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 5 | | totalSentences | 395 | | matches | | 0 | "To memorize the rhythm of" | | 1 | "To recognize when a person" | | 2 | "Even when they were breaking." | | 3 | "Even when you were the" | | 4 | "Now you measure everything." |
| | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 1 | | matches | | 0 | "He remembered the girl who used to race down the stairs above the bar, late for lectures, muttering about contract law and broken promises." |
| |
| 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 | |