| 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 | 1761 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 63.09% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1761 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "scanned" | | 1 | "flickered" | | 2 | "footsteps" | | 3 | "echoed" | | 4 | "electric" | | 5 | "calculated" | | 6 | "stomach" | | 7 | "standard" | | 8 | "silence" | | 9 | "weight" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 385 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 6 | | hedgeCount | 0 | | narrationSentences | 385 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 385 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 15 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1756 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 64 | | wordCount | 1756 | | uniqueNames | 15 | | maxNameDensity | 1.31 | | worstName | "Tomás" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Tomás" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Quinn | 1 | | Raven | 1 | | Nest | 1 | | Herrera | 1 | | Tube | 1 | | Tomás | 23 | | Christopher | 1 | | Veil | 1 | | Market | 1 | | Morris | 5 | | Harlow | 22 | | You | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Herrera" | | 3 | "Tomás" | | 4 | "Christopher" | | 5 | "Market" | | 6 | "Morris" | | 7 | "Harlow" | | 8 | "You" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0.845 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 101 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1756 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 385 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 72 | | mean | 24.39 | | std | 21.46 | | cv | 0.88 | | sampleLengths | | 0 | 72 | | 1 | 117 | | 2 | 105 | | 3 | 63 | | 4 | 36 | | 5 | 55 | | 6 | 39 | | 7 | 32 | | 8 | 41 | | 9 | 32 | | 10 | 24 | | 11 | 28 | | 12 | 47 | | 13 | 26 | | 14 | 21 | | 15 | 5 | | 16 | 17 | | 17 | 5 | | 18 | 19 | | 19 | 8 | | 20 | 26 | | 21 | 39 | | 22 | 28 | | 23 | 45 | | 24 | 28 | | 25 | 32 | | 26 | 32 | | 27 | 25 | | 28 | 32 | | 29 | 19 | | 30 | 5 | | 31 | 16 | | 32 | 4 | | 33 | 21 | | 34 | 4 | | 35 | 3 | | 36 | 13 | | 37 | 5 | | 38 | 26 | | 39 | 38 | | 40 | 19 | | 41 | 4 | | 42 | 15 | | 43 | 4 | | 44 | 38 | | 45 | 36 | | 46 | 9 | | 47 | 12 | | 48 | 3 | | 49 | 14 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 385 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 389 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 385 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1761 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 15 | | adverbRatio | 0.008517887563884156 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.001135718341851221 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 385 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 385 | | mean | 4.56 | | std | 1.91 | | cv | 0.42 | | sampleLengths | | 0 | 8 | | 1 | 3 | | 2 | 6 | | 3 | 5 | | 4 | 10 | | 5 | 9 | | 6 | 6 | | 7 | 6 | | 8 | 7 | | 9 | 4 | | 10 | 3 | | 11 | 5 | | 12 | 7 | | 13 | 6 | | 14 | 9 | | 15 | 2 | | 16 | 5 | | 17 | 15 | | 18 | 9 | | 19 | 5 | | 20 | 7 | | 21 | 5 | | 22 | 3 | | 23 | 4 | | 24 | 4 | | 25 | 2 | | 26 | 5 | | 27 | 4 | | 28 | 7 | | 29 | 5 | | 30 | 3 | | 31 | 10 | | 32 | 4 | | 33 | 2 | | 34 | 3 | | 35 | 4 | | 36 | 5 | | 37 | 4 | | 38 | 3 | | 39 | 4 | | 40 | 3 | | 41 | 4 | | 42 | 7 | | 43 | 4 | | 44 | 5 | | 45 | 2 | | 46 | 1 | | 47 | 5 | | 48 | 6 | | 49 | 4 |
| |
| 31.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 72 | | diversityRatio | 0.2051948051948052 | | totalSentences | 385 | | uniqueOpeners | 79 | |
| 19.55% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 341 | | matches | | 0 | "Then buy something." | | 1 | "Then we have work to" |
| | ratio | 0.006 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 195 | | totalSentences | 341 | | matches | | 0 | "Her boots slapped against wet" | | 1 | "She checked the worn leather" | | 2 | "She wiped water from her" | | 3 | "She scanned the shadows." | | 4 | "He favoured his left leg." | | 5 | "He vanished into the shadows" | | 6 | "She moved with military precision." | | 7 | "She swept the corner." | | 8 | "She holstered the gun." | | 9 | "She kicked the door." | | 10 | "She descended the stairs." | | 11 | "Her footsteps echoed." | | 12 | "It smelled of sulphur and" | | 13 | "She reached the platform." | | 14 | "She crept to the edge." | | 15 | "She spotted Tomás near the" | | 16 | "He touched a medallion around" | | 17 | "He handed something to a" | | 18 | "She watched the crowd." | | 19 | "Her partner Morris died three" |
| | ratio | 0.572 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 315 | | totalSentences | 341 | | matches | | 0 | "Harlow Quinn sprinted." | | 1 | "Her boots slapped against wet" | | 2 | "Breath tore at her throat." | | 3 | "She checked the worn leather" | | 4 | "She wiped water from her" | | 5 | "Salt-and-pepper hair plastered to her" | | 6 | "The sharp line of her" | | 7 | "She scanned the shadows." | | 8 | "Streetlights flickered above." | | 9 | "Puddles reflected the orange glow." | | 10 | "Olive skin gleamed under the" | | 11 | "He favoured his left leg." | | 12 | "The scar running along his" | | 13 | "He vanished into the shadows" | | 14 | "Harlow drew her service weapon." | | 15 | "The metal felt cold against" | | 16 | "She moved with military precision." | | 17 | "She swept the corner." | | 18 | "The street stood empty." | | 19 | "Steam rose from a grate." |
| | ratio | 0.924 | |
| 29.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 341 | | matches | | 0 | "Now she stood at the" | | 1 | "If she lost him, the" |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 8 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |