| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "a voice hissed directly [directly]" |
| | dialogueSentences | 21 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.143 | | effectiveRatio | 0.095 | |
| 96.05% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1266 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 13.11% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1266 | | totalAiIsms | 22 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "rhythmic" | | 1 | "pounding" | | 2 | "echoed" | | 3 | "glint" | | 4 | "standard" | | 5 | "calculated" | | 6 | "scanned" | | 7 | "mechanical" | | 8 | "depths" | | 9 | "oppressive" | | 10 | "silence" | | 11 | "familiar" | | 12 | "velvet" | | 13 | "footsteps" | | 14 | "chaotic" | | 15 | "testament" | | 16 | "weight" | | 17 | "silk" | | 18 | "grave" |
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| 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 | 108 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 108 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 122 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1266 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 1130 | | uniqueNames | 5 | | maxNameDensity | 1.33 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 15 | | London | 1 | | Camden | 1 | | Tube | 1 | | Morris | 1 |
| | persons | | | places | | | globalScore | 0.836 | | windowScore | 0.833 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 6 | | matches | | 0 | "sounded like a collective murmur, a thousa" | | 1 | "felt like stepping through a veil of co" | | 2 | "silence that seemed to press against her eardrums" | | 3 | "something akin to crushed violets and old coppe" | | 4 | "quite kill" | | 5 | "sounded like grinding stones" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1266 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 122 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 24.35 | | std | 17.24 | | cv | 0.708 | | sampleLengths | | 0 | 62 | | 1 | 54 | | 2 | 38 | | 3 | 1 | | 4 | 33 | | 5 | 44 | | 6 | 18 | | 7 | 56 | | 8 | 32 | | 9 | 2 | | 10 | 52 | | 11 | 49 | | 12 | 39 | | 13 | 41 | | 14 | 36 | | 15 | 9 | | 16 | 27 | | 17 | 7 | | 18 | 4 | | 19 | 10 | | 20 | 33 | | 21 | 18 | | 22 | 31 | | 23 | 59 | | 24 | 34 | | 25 | 5 | | 26 | 57 | | 27 | 8 | | 28 | 45 | | 29 | 16 | | 30 | 18 | | 31 | 1 | | 32 | 42 | | 33 | 3 | | 34 | 10 | | 35 | 20 | | 36 | 13 | | 37 | 22 | | 38 | 26 | | 39 | 6 | | 40 | 21 | | 41 | 15 | | 42 | 22 | | 43 | 17 | | 44 | 19 | | 45 | 15 | | 46 | 3 | | 47 | 29 | | 48 | 12 | | 49 | 14 |
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| 98.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 108 | | matches | | 0 | "was gone" | | 1 | "were replaced" |
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| 20.79% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 186 | | matches | | 0 | "were sliding" | | 1 | "was selling" | | 2 | "was meticulously arranging" | | 3 | "wasn't complying" | | 4 | "was beckoning" |
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| 96.02% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 122 | | ratio | 0.016 | | matches | | 0 | "They weren't the glances of curious onlookers; they were the hungry, predatory stares of things waiting for a slip, a mistake, a sign of weakness." | | 1 | "He didn't walk; he glided, the distance between them closing with impossible speed." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1131 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, white, jagged bone" |
| | adverbCount | 25 | | adverbRatio | 0.022104332449160036 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.007073386383731211 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 122 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 122 | | mean | 10.38 | | std | 5.61 | | cv | 0.54 | | sampleLengths | | 0 | 18 | | 1 | 24 | | 2 | 20 | | 3 | 5 | | 4 | 10 | | 5 | 5 | | 6 | 20 | | 7 | 14 | | 8 | 19 | | 9 | 8 | | 10 | 11 | | 11 | 1 | | 12 | 8 | | 13 | 5 | | 14 | 20 | | 15 | 3 | | 16 | 11 | | 17 | 13 | | 18 | 17 | | 19 | 14 | | 20 | 4 | | 21 | 14 | | 22 | 14 | | 23 | 14 | | 24 | 14 | | 25 | 9 | | 26 | 3 | | 27 | 20 | | 28 | 2 | | 29 | 18 | | 30 | 19 | | 31 | 15 | | 32 | 11 | | 33 | 8 | | 34 | 14 | | 35 | 16 | | 36 | 7 | | 37 | 14 | | 38 | 13 | | 39 | 5 | | 40 | 12 | | 41 | 17 | | 42 | 12 | | 43 | 12 | | 44 | 13 | | 45 | 7 | | 46 | 4 | | 47 | 9 | | 48 | 2 | | 49 | 13 |
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| 37.70% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.23770491803278687 | | totalSentences | 122 | | uniqueOpeners | 29 | |
| 32.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 103 | | matches | | 0 | "Instead, he leaned closer to" |
| | ratio | 0.01 | |
| 56.89% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 103 | | matches | | 0 | "He turned a sharp corner" | | 1 | "Her lungs burned, each breath" | | 2 | "She didn't call for backup." | | 3 | "She focused on the target," | | 4 | "Her leather watch caught a" | | 5 | "She checked the time, though" | | 6 | "He vaulted over a rusted" | | 7 | "She gripped the chain-link, her" | | 8 | "Her military training took over," | | 9 | "She cleared the top, her" | | 10 | "She tracked a fresh set" | | 11 | "It stood partially ajar, a" | | 12 | "It wasn't mechanical." | | 13 | "It sounded like a collective" | | 14 | "They were replaced by a" | | 15 | "She stood on the edge" | | 16 | "She moved closer, her footsteps" | | 17 | "He didn't look up as" | | 18 | "He didn't even blink." | | 19 | "He leaned against the damp" |
| | ratio | 0.408 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 96 | | totalSentences | 103 | | matches | | 0 | "Boot heels thudded against the" | | 1 | "The man in the charcoal" | | 2 | "He turned a sharp corner" | | 3 | "Quinn pushed her legs harder." | | 4 | "Her lungs burned, each breath" | | 5 | "She didn't call for backup." | | 6 | "The radio had sputtered into" | | 7 | "She focused on the target," | | 8 | "Her leather watch caught a" | | 9 | "She checked the time, though" | | 10 | "The pursuit had moved beyond" | | 11 | "The command left her throat," | | 12 | "The man didn't even flinch." | | 13 | "He vaulted over a rusted" | | 14 | "Quinn didn't hesitate." | | 15 | "She gripped the chain-link, her" | | 16 | "Her military training took over," | | 17 | "She cleared the top, her" | | 18 | "The alley terminated in a" | | 19 | "The man was gone." |
| | ratio | 0.932 | |
| 97.09% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 103 | | matches | | 0 | "To her left, a woman" | | 1 | "To her right, a man" |
| | ratio | 0.019 | |
| 32.02% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 9 | | matches | | 0 | "Boot heels thudded against the wet pavement, a rhythmic percussion that matched the frantic pounding in Quinn's chest." | | 1 | "The man in the charcoal coat surged ahead, his movements unnaturally fluid, as if he were sliding through the rain rather than fighting it." | | 2 | "The radio had sputtered into static three blocks back, a hollow, dead sound that echoed the emptiness in her gut." | | 3 | "Her military training took over, a cold, calculated autopilot that bypassed her exhaustion." | | 4 | "They were replaced by a heavy, oppressive silence that seemed to press against her eardrums." | | 5 | "Stalls fashioned from scavenged wood and heavy velvet draped the narrow passageway that stretched into the tunnel." | | 6 | "He had been moving with a purpose that felt ancient, something that bypassed the laws of physics she had spent her life upholding." | | 7 | "It was a slow, wide expression that revealed too many teeth." | | 8 | "She gasped, her lungs seizing, her vision splintering into shards of white light." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn snapped, her hand hovering over her weapon" | | 1 | "Quinn said, her voice dropping to a dangerous low" |
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| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn snapped (snap)" | | 1 | "he whispered (whisper)" | | 2 | "a voice hissed directly (hiss)" |
| | dialogueSentences | 21 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0.5 | | effectiveRatio | 0.286 | |