| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.09% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1162 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | | 2 | | adverb | "deliberately" | | count | 1 |
|
| | highlights | | 0 | "cautiously" | | 1 | "slightly" | | 2 | "deliberately" |
| |
| 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) | |
| 65.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1162 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "methodical" | | 1 | "flickered" | | 2 | "footsteps" | | 3 | "echoed" | | 4 | "structure" | | 5 | "glint" |
| |
| 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 | 110 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 110 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 118 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1157 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 79.64% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1066 | | uniqueNames | 10 | | maxNameDensity | 1.41 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Quinn | 15 | | Greek | 1 | | Street | 1 | | Garden | 1 | | Young | 1 | | Tube | 2 | | Morris | 1 | | Water | 3 | | Eighteen | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Water" |
| | places | | 0 | "Soho" | | 1 | "Greek" | | 2 | "Street" | | 3 | "Garden" |
| | globalScore | 0.796 | | windowScore | 0.833 | |
| 85.90% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 2 | | matches | | 0 | "shadows that seemed to shift with each step" | | 1 | "looked like an older brick structure" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1157 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 118 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 33.06 | | std | 20.13 | | cv | 0.609 | | sampleLengths | | 0 | 61 | | 1 | 63 | | 2 | 41 | | 3 | 58 | | 4 | 59 | | 5 | 15 | | 6 | 61 | | 7 | 33 | | 8 | 41 | | 9 | 44 | | 10 | 39 | | 11 | 41 | | 12 | 24 | | 13 | 7 | | 14 | 32 | | 15 | 9 | | 16 | 9 | | 17 | 58 | | 18 | 13 | | 19 | 11 | | 20 | 13 | | 21 | 18 | | 22 | 52 | | 23 | 45 | | 24 | 55 | | 25 | 9 | | 26 | 56 | | 27 | 10 | | 28 | 55 | | 29 | 15 | | 30 | 36 | | 31 | 50 | | 32 | 15 | | 33 | 8 | | 34 | 1 |
| |
| 98.88% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 110 | | matches | | 0 | "been trained" | | 1 | "were warped" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 173 | | matches | | |
| 46.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 118 | | ratio | 0.034 | | matches | | 0 | "Her training kicked in—scan corners, watch for movement, stay unpredictable." | | 1 | "The air coming from below carried a smell she couldn't identify immediately—damp, certainly, but something else underneath." | | 2 | "The beam of her torch caught a glint of something metallic—old railway tracks, she realized." | | 3 | "And sound—music, voices, the ambient noise of a crowd." |
| |
| 98.24% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1071 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 45 | | adverbRatio | 0.04201680672268908 | | lyAdverbCount | 18 | | lyAdverbRatio | 0.01680672268907563 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 118 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 118 | | mean | 9.81 | | std | 6.31 | | cv | 0.643 | | sampleLengths | | 0 | 16 | | 1 | 26 | | 2 | 19 | | 3 | 8 | | 4 | 20 | | 5 | 5 | | 6 | 19 | | 7 | 6 | | 8 | 5 | | 9 | 13 | | 10 | 15 | | 11 | 4 | | 12 | 9 | | 13 | 6 | | 14 | 14 | | 15 | 6 | | 16 | 19 | | 17 | 13 | | 18 | 5 | | 19 | 6 | | 20 | 14 | | 21 | 19 | | 22 | 15 | | 23 | 3 | | 24 | 12 | | 25 | 4 | | 26 | 11 | | 27 | 23 | | 28 | 7 | | 29 | 16 | | 30 | 4 | | 31 | 3 | | 32 | 3 | | 33 | 3 | | 34 | 20 | | 35 | 9 | | 36 | 10 | | 37 | 13 | | 38 | 7 | | 39 | 1 | | 40 | 1 | | 41 | 8 | | 42 | 4 | | 43 | 12 | | 44 | 8 | | 45 | 12 | | 46 | 5 | | 47 | 1 | | 48 | 15 | | 49 | 12 |
| |
| 52.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3813559322033898 | | totalSentences | 118 | | uniqueOpeners | 45 | |
| 33.33% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 100 | | matches | | 0 | "Instead, they veered right, down" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 100 | | matches | | 0 | "She'd been following the lead" | | 1 | "She believed in footwork, in" | | 2 | "Her breathing remained steady." | | 3 | "Her hand rested near the" | | 4 | "They paused for just a" | | 5 | "It was enough." | | 6 | "She descended the concrete ramp," | | 7 | "Her footsteps echoed off the" | | 8 | "She moved deeper into the" | | 9 | "Her training kicked in—scan corners," | | 10 | "She passed level B1, then" | | 11 | "It was a painted mural" | | 12 | "They stepped toward the mural" | | 13 | "Their shoulders rose and fell" | | 14 | "They turned and descended into" | | 15 | "She pulled out her torch," | | 16 | "She was standing at the" | | 17 | "Her mind flashed back to" | | 18 | "She'd dismissed it as urban" | | 19 | "She took another step into" |
| | ratio | 0.21 | |
| 25.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 87 | | totalSentences | 100 | | matches | | 0 | "The rain fell in sheets" | | 1 | "Detective Quinn pulled her collar" | | 2 | "The figure she'd been tracking" | | 3 | "She'd been following the lead" | | 4 | "A witness had placed someone" | | 5 | "Quinn didn't believe in coincidence." | | 6 | "She believed in footwork, in" | | 7 | "That's how she'd solved seventeen" | | 8 | "That's how she'd been trained." | | 9 | "The suspect moved fast through" | | 10 | "Quinn increased her pace, her" | | 11 | "Her breathing remained steady." | | 12 | "Her hand rested near the" | | 13 | "The alley opened onto another" | | 14 | "Covent Garden spilled out to" | | 15 | "The suspect didn't head toward" | | 16 | "This one led to the" | | 17 | "A dead end, most likely." | | 18 | "Quinn pushed forward, her jaw" | | 19 | "The rain intensified, hammering down" |
| | ratio | 0.87 | |
| 50.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 100 | | matches | | 0 | "Now the suspect was moving" |
| | ratio | 0.01 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 6 | | matches | | 0 | "She believed in footwork, in patience, in the methodical accumulation of facts that would eventually pin this case down." | | 1 | "Quinn increased her pace, her shoes splashing through puddles that collected in the uneven pavement." | | 2 | "The suspect stood motionless, as if they'd hit a dead end themselves." | | 3 | "Young face, angular features, eyes that reflected the faint light strangely." | | 4 | "She'd dismissed it as urban legend, the kind of nonsense that distracted from real police work." | | 5 | "The platform itself was remarkably intact, as if someone had maintained it deliberately." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |