| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1134 | | 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) | |
| 64.73% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1134 | | totalAiIsms | 8 | | found | | 0 | | | 1 | | | 2 | | | 3 | | word | "the last thing" | | count | 1 |
| | 4 | | | 5 | | | 6 | | | 7 | |
| | highlights | | 0 | "shattered" | | 1 | "measured" | | 2 | "glint" | | 3 | "the last thing" | | 4 | "flickered" | | 5 | "weight" | | 6 | "standard" | | 7 | "vibrated" |
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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 | 97 | | matches | (empty) | |
| 83.95% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 97 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "happened to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 102 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1146 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 1103 | | uniqueNames | 15 | | maxNameDensity | 0.73 | | worstName | "Herrera" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Soho | 1 | | Quinn | 7 | | Saint | 1 | | Christopher | 1 | | Raven | 2 | | Nest | 2 | | St | 2 | | Herrera | 8 | | Tube | 1 | | Morris | 6 | | Camden | 1 | | God | 1 | | Thames | 1 | | London | 1 | | Victorian | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Saint" | | 2 | "Christopher" | | 3 | "Raven" | | 4 | "Herrera" | | 5 | "Morris" | | 6 | "God" |
| | places | | 0 | "Soho" | | 1 | "St" | | 2 | "Thames" | | 3 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 1 | | matches | | 0 | "leather that seemed to breathe" |
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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 | 1146 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 102 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 36.97 | | std | 25.09 | | cv | 0.679 | | sampleLengths | | 0 | 56 | | 1 | 69 | | 2 | 1 | | 3 | 56 | | 4 | 87 | | 5 | 49 | | 6 | 6 | | 7 | 11 | | 8 | 65 | | 9 | 73 | | 10 | 39 | | 11 | 29 | | 12 | 8 | | 13 | 51 | | 14 | 8 | | 15 | 26 | | 16 | 76 | | 17 | 15 | | 18 | 58 | | 19 | 79 | | 20 | 31 | | 21 | 51 | | 22 | 39 | | 23 | 8 | | 24 | 43 | | 25 | 33 | | 26 | 17 | | 27 | 31 | | 28 | 20 | | 29 | 6 | | 30 | 5 |
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| 76.32% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 8 | | totalSentences | 97 | | matches | | 0 | "being hunted" | | 1 | "been sealed" | | 2 | "were sold" | | 3 | "was obsessed" | | 4 | "been transformed" | | 5 | "was obscured" | | 6 | "been blocked" | | 7 | "been held" |
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| 89.50% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 181 | | matches | | 0 | "was grounding" | | 1 | "was talking" | | 2 | "were still growing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 102 | | ratio | 0.088 | | matches | | 0 | "Harlow Quinn's boots struck the cobblestones in a rhythm she knew from a hundred foot pursuits — measured, relentless, the kind of pace that broke men who thought they could sprint forever." | | 1 | "His jacket flared behind him — a paramedic's jacket, navy blue, faded at the shoulders." | | 2 | "The abandoned stations beneath Camden were a maze — service tunnels, old platforms, sealed corridors that went God knew where." | | 3 | "Somewhere below, a light flickered — warm, amber, nothing like the cold fluorescent of maintenance crews." | | 4 | "The steps spiral-languaged in a way that didn't match London's standard station architecture, and the walls on either side shifted from tiled Victorian to rough-hewn brick to something older — stone blocks fitted together without mortar, their surfaces carved with symbols she didn't recognise." | | 5 | "Stalls lined both platforms, their awnings made from materials that moved wrong — fabric that rippled without wind, leather that seemed to breathe." | | 6 | "Two children — if they were children — chased each other between the stalls, their laughter high and wrong, like wind through cracked glass." | | 7 | "Its eyes — if they were eyes — were solid black, no whites, no iris." | | 8 | "The vendor — an elderly man with papery skin and cloudy eyes — held one out to her between two fingers." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 248 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.03225806451612903 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.004032258064516129 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 102 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 102 | | mean | 11.24 | | std | 8.12 | | cv | 0.723 | | sampleLengths | | 0 | 24 | | 1 | 32 | | 2 | 31 | | 3 | 24 | | 4 | 7 | | 5 | 7 | | 6 | 1 | | 7 | 3 | | 8 | 2 | | 9 | 27 | | 10 | 17 | | 11 | 7 | | 12 | 12 | | 13 | 8 | | 14 | 15 | | 15 | 5 | | 16 | 19 | | 17 | 3 | | 18 | 25 | | 19 | 10 | | 20 | 7 | | 21 | 1 | | 22 | 5 | | 23 | 26 | | 24 | 3 | | 25 | 3 | | 26 | 5 | | 27 | 6 | | 28 | 13 | | 29 | 22 | | 30 | 13 | | 31 | 17 | | 32 | 14 | | 33 | 20 | | 34 | 12 | | 35 | 13 | | 36 | 5 | | 37 | 9 | | 38 | 10 | | 39 | 5 | | 40 | 5 | | 41 | 19 | | 42 | 5 | | 43 | 8 | | 44 | 16 | | 45 | 4 | | 46 | 2 | | 47 | 2 | | 48 | 11 | | 49 | 6 |
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| 53.27% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.4019607843137255 | | totalSentences | 102 | | uniqueOpeners | 41 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 92 | | matches | | 0 | "Instead, he cut left down" | | 1 | "Once outside The Raven's Nest," | | 2 | "Once at St." | | 3 | "Somewhere below, a light flickered" |
| | ratio | 0.043 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 92 | | matches | | 0 | "He moved with a strange" | | 1 | "His dark curls plastered to" | | 2 | "He didn't turn." | | 3 | "She didn't stop to check" | | 4 | "His jacket flared behind him" | | 5 | "She'd seen him twice before." | | 6 | "She pushed harder." | | 7 | "He disappeared around another corner." | | 8 | "She'd run this route in" | | 9 | "They'd found his body two" | | 10 | "His watch had stopped at" | | 11 | "She pulled her phone." | | 12 | "Her inspector thought she was" | | 13 | "Her colleagues exchanged looks when" | | 14 | "She was two weeks from" | | 15 | "She drew her baton but" | | 16 | "He was talking to the" | | 17 | "She could go back." | | 18 | "Its eyes — if they" | | 19 | "It opened its mouth, and" |
| | ratio | 0.272 | |
| 57.83% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 92 | | matches | | 0 | "Harlow Quinn's boots struck the" | | 1 | "The figure ahead of her" | | 2 | "He moved with a strange" | | 3 | "His dark curls plastered to" | | 4 | "Olive skin gone pale under" | | 5 | "He didn't turn." | | 6 | "Quinn followed, her worn leather" | | 7 | "She didn't stop to check" | | 8 | "The alley opened onto a" | | 9 | "Herrera was twenty metres ahead" | | 10 | "His jacket flared behind him" | | 11 | "She'd seen him twice before." | | 12 | "Herrera had been the one" | | 13 | "Herrera wasn't on staff anywhere." | | 14 | "Quinn's lungs burned." | | 15 | "She pushed harder." | | 16 | "He disappeared around another corner." | | 17 | "The street ended at a" | | 18 | "The entrance gaped like a" | | 19 | "A faded roundel hung at" |
| | ratio | 0.804 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 92 | | matches | (empty) | | ratio | 0 | |
| 65.22% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 5 | | matches | | 0 | "Rain hammered the pavement in sheets, turning Soho's greasy puddles into shattered mirrors that caught the neon and threw it back in ugly fragments." | | 1 | "The abandoned stations beneath Camden were a maze — service tunnels, old platforms, sealed corridors that went God knew where." | | 2 | "The steps spiral-languaged in a way that didn't match London's standard station architecture, and the walls on either side shifted from tiled Victorian to rough…" | | 3 | "The tunnel to her right had been blocked with a barrier of interwoven branches that were still growing, she realised, their tips unfurling in slow motion." | | 4 | "It opened its mouth, and the sound that came out was a language that made her teeth vibrate." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |