| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1167 | | 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) | |
| 48.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1167 | | totalAiIsms | 12 | | found | | 0 | | word | "practiced ease" | | count | 1 |
| | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | |
| | highlights | | 0 | "practiced ease" | | 1 | "gleaming" | | 2 | "footsteps" | | 3 | "echoed" | | 4 | "pulsed" | | 5 | "scanning" | | 6 | "pulse" | | 7 | "depths" | | 8 | "echoing" | | 9 | "silence" |
| |
| 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 | 2 | | narrationSentences | 151 | | matches | | 0 | "d with terror" | | 1 | "r in terror" |
| |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 151 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 155 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1167 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 96.52% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 1122 | | uniqueNames | 11 | | maxNameDensity | 1.07 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 3 | | Whitechapel | 2 | | Veil | 2 | | Market | 2 | | Tube | 2 | | Quinn | 12 | | Saint | 1 | | Christopher | 1 | | Morris | 3 | | Three | 3 | | Baton | 3 |
| | persons | | 0 | "Camden" | | 1 | "Quinn" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Morris" | | 5 | "Baton" |
| | places | | | globalScore | 0.965 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.857 | | wordCount | 1167 | | matches | | 0 | "Not wood absorbing impact, but something deeper, like striking the surface of black water" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 155 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 23.82 | | std | 15.61 | | cv | 0.656 | | sampleLengths | | 0 | 19 | | 1 | 33 | | 2 | 32 | | 3 | 15 | | 4 | 39 | | 5 | 33 | | 6 | 21 | | 7 | 24 | | 8 | 4 | | 9 | 38 | | 10 | 62 | | 11 | 46 | | 12 | 37 | | 13 | 29 | | 14 | 31 | | 15 | 40 | | 16 | 14 | | 17 | 7 | | 18 | 5 | | 19 | 35 | | 20 | 19 | | 21 | 84 | | 22 | 18 | | 23 | 33 | | 24 | 22 | | 25 | 4 | | 26 | 15 | | 27 | 22 | | 28 | 15 | | 29 | 5 | | 30 | 14 | | 31 | 7 | | 32 | 33 | | 33 | 22 | | 34 | 25 | | 35 | 32 | | 36 | 12 | | 37 | 40 | | 38 | 2 | | 39 | 22 | | 40 | 7 | | 41 | 17 | | 42 | 29 | | 43 | 5 | | 44 | 29 | | 45 | 9 | | 46 | 31 | | 47 | 25 | | 48 | 5 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 151 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 210 | | matches | | 0 | "was happening" | | 1 | "was offering" | | 2 | "was coming" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 155 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1128 | | adjectiveStacks | 1 | | stackExamples | | 0 | "behind red-draped canvas." |
| | adverbCount | 39 | | adverbRatio | 0.034574468085106384 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.007978723404255319 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 155 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 155 | | mean | 7.53 | | std | 5.42 | | cv | 0.72 | | sampleLengths | | 0 | 5 | | 1 | 14 | | 2 | 3 | | 3 | 3 | | 4 | 14 | | 5 | 13 | | 6 | 5 | | 7 | 14 | | 8 | 13 | | 9 | 4 | | 10 | 1 | | 11 | 4 | | 12 | 6 | | 13 | 1 | | 14 | 14 | | 15 | 8 | | 16 | 5 | | 17 | 3 | | 18 | 1 | | 19 | 7 | | 20 | 15 | | 21 | 2 | | 22 | 16 | | 23 | 4 | | 24 | 2 | | 25 | 1 | | 26 | 5 | | 27 | 9 | | 28 | 7 | | 29 | 9 | | 30 | 3 | | 31 | 1 | | 32 | 4 | | 33 | 4 | | 34 | 4 | | 35 | 2 | | 36 | 11 | | 37 | 8 | | 38 | 1 | | 39 | 12 | | 40 | 12 | | 41 | 4 | | 42 | 20 | | 43 | 7 | | 44 | 19 | | 45 | 7 | | 46 | 3 | | 47 | 10 | | 48 | 12 | | 49 | 5 |
| |
| 78.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.5032258064516129 | | totalSentences | 155 | | uniqueOpeners | 78 | |
| 82.64% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 121 | | matches | | 0 | "Unnaturally cold, the kind that" | | 1 | "Then the suspect turned." | | 2 | "Then she felt it." |
| | ratio | 0.025 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 121 | | matches | | 0 | "She pushed harder." | | 1 | "Her lungs burned." | | 2 | "She tracked the sound and" | | 3 | "She'd seen this pattern before," | | 4 | "She closed the gap." | | 5 | "They reached the boards and" | | 6 | "She pressed her palm flat" | | 7 | "She'd filed the paperwork, closed" | | 8 | "Her informants had whispered about" | | 9 | "She removed her worn leather" | | 10 | "She struck the boards where" | | 11 | "Her posture straightened." | | 12 | "Her footsteps echoed." | | 13 | "She slowed, baton held low," | | 14 | "They hadn't noticed her yet." | | 15 | "Her boot caught on something" | | 16 | "She stepped over it and" | | 17 | "They shoved past the vendor" | | 18 | "Her pulse spiked." |
| | ratio | 0.157 | |
| 88.10% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 90 | | totalSentences | 121 | | matches | | 0 | "Quinn's boots hammered wet pavement." | | 1 | "She pushed harder." | | 2 | "Her lungs burned." | | 3 | "Rain streamed down her face," | | 4 | "Military training, years of it," | | 5 | "The suspect knew these streets." | | 6 | "Every turn carved deeper into" | | 7 | "Puddles mirrored broken neon, painting" | | 8 | "Quinn rounded another corner." | | 9 | "Chain-link rattled somewhere ahead." | | 10 | "She tracked the sound and" | | 11 | "The suspect vaulted a rusted" | | 12 | "Quinn grabbed the mesh and" | | 13 | "Metal bit into her palms." | | 14 | "Boots splashed into mud and" | | 15 | "The suspect moved across the" | | 16 | "She'd seen this pattern before," | | 17 | "She closed the gap." | | 18 | "The suspect's hood fell back." | | 19 | "They reached the boards and" |
| | ratio | 0.744 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 121 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 2 | | matches | | 0 | "Rain ceased immediately once she descended, as if weather couldn't penetrate this far underground." | | 1 | "Two customers, their outlines wrong in ways Quinn couldn't pin down, exchanged whispered words near a stall selling bottled liquids that shifted colour on their…" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 6 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 1 | | effectiveRatio | 0.333 | |