| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.27% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1339 | | 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) | |
| 51.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1339 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "fractured" | | 1 | "measured" | | 2 | "mechanical" | | 3 | "weight" | | 4 | "glint" | | 5 | "stark" | | 6 | "charged" | | 7 | "echoed" | | 8 | "echoing" | | 9 | "constructed" | | 10 | "velvet" | | 11 | "pulse" |
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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 | 1 | | narrationSentences | 73 | | matches | | |
| 84.15% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 73 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 74 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 20 | | totalWords | 1333 | | ratio | 0.015 | | matches | | 0 | "Keep your head down and watch the clock, Harlow," | | 1 | "The world doesn't care about justice, but the shifts still end." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1330 | | uniqueNames | 24 | | maxNameDensity | 0.83 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | London | 2 | | Quinn | 11 | | Herrera | 8 | | Camden | 2 | | Lock | 1 | | Saint | 1 | | Christopher | 1 | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Astra | 1 | | Detective | 2 | | Sergeant | 1 | | Morris | 5 | | Victorian | 1 | | Glock | 1 | | Tube | 1 | | Blitz | 1 | | Northern | 1 | | Line | 1 | | Veil | 1 | | Market | 1 | | Thames | 1 | | Harlow | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Herrera" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Raven" | | 5 | "Astra" | | 6 | "Sergeant" | | 7 | "Morris" | | 8 | "Harlow" |
| | places | | 0 | "London" | | 1 | "Soho" | | 2 | "Line" | | 3 | "Thames" |
| | globalScore | 1 | | windowScore | 1 | |
| 30.95% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 3 | | matches | | 0 | "smelled like the cold, inexplicable frost" | | 1 | "looked like a sliver of polished animal r" | | 2 | "roots that seemed to twist when no one was touching them; she saw people—and things that moved with a terrifying, inhuman grace—trading unmarked gold coin and whispers" |
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| 49.96% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.5 | | wordCount | 1333 | | matches | | 0 | "not an alley, but a yawning mouth of crumbling Victorian masonry" | | 1 | "not the rumble of the Northern Line, but a sound like hundreds of voices murmuring at once, accompani" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 74 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 26 | | mean | 51.27 | | std | 30.49 | | cv | 0.595 | | sampleLengths | | 0 | 91 | | 1 | 63 | | 2 | 115 | | 3 | 57 | | 4 | 3 | | 5 | 99 | | 6 | 48 | | 7 | 13 | | 8 | 70 | | 9 | 60 | | 10 | 9 | | 11 | 53 | | 12 | 79 | | 13 | 32 | | 14 | 71 | | 15 | 34 | | 16 | 21 | | 17 | 6 | | 18 | 105 | | 19 | 33 | | 20 | 67 | | 21 | 23 | | 22 | 55 | | 23 | 20 | | 24 | 54 | | 25 | 52 |
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| 95.65% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 73 | | matches | | 0 | "was discovered" | | 1 | "was gone" |
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| 42.02% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 211 | | matches | | 0 | "was running" | | 1 | "wasn’t fighting" | | 2 | "was touching" | | 3 | "was stepping" | | 4 | "was still standing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 2 | | flaggedSentences | 4 | | totalSentences | 74 | | ratio | 0.054 | | matches | | 0 | "The intelligence was thin—whispers through vice channels about an unlicensed street medic patching up bodies that shouldn't have been breathing, let alone bleeding—but thin was all she had." | | 1 | "A low, resonant hum began to vibrate through the soles of her boots—not the rumble of the Northern Line, but a sound like hundreds of voices murmuring at once, accompanied by the clatter of iron and the chime of glass." | | 2 | "She saw glass jars containing liquids that gave off their own pale light; she saw bundles of dried roots that seemed to twist when no one was touching them; she saw people—and things that moved with a terrifying, inhuman grace—trading unmarked gold coin and whispers." | | 3 | "He had the answers—or at least the first link in a chain that led to the thing that had killed her partner." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1342 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.023099850968703428 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.0067064083457526085 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 74 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 74 | | mean | 18.01 | | std | 10.88 | | cv | 0.604 | | sampleLengths | | 0 | 24 | | 1 | 31 | | 2 | 36 | | 3 | 5 | | 4 | 12 | | 5 | 25 | | 6 | 21 | | 7 | 24 | | 8 | 23 | | 9 | 28 | | 10 | 40 | | 11 | 19 | | 12 | 7 | | 13 | 31 | | 14 | 3 | | 15 | 16 | | 16 | 16 | | 17 | 18 | | 18 | 49 | | 19 | 7 | | 20 | 37 | | 21 | 4 | | 22 | 6 | | 23 | 7 | | 24 | 19 | | 25 | 17 | | 26 | 19 | | 27 | 15 | | 28 | 9 | | 29 | 16 | | 30 | 35 | | 31 | 9 | | 32 | 16 | | 33 | 23 | | 34 | 14 | | 35 | 17 | | 36 | 22 | | 37 | 40 | | 38 | 16 | | 39 | 16 | | 40 | 13 | | 41 | 23 | | 42 | 4 | | 43 | 31 | | 44 | 11 | | 45 | 18 | | 46 | 5 | | 47 | 21 | | 48 | 6 | | 49 | 9 |
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| 53.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.35135135135135137 | | totalSentences | 74 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 66.58% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 73 | | matches | | 0 | "Her closely cropped salt-and-pepper hair" | | 1 | "He was fast, younger by" | | 2 | "He sprinted in erratic bursts," | | 3 | "She had waited outside that" | | 4 | "It was all she had" | | 5 | "She vaulted the low brick" | | 6 | "Her voice had the flat," | | 7 | "He threw his weight against" | | 8 | "She pressed her back to" | | 9 | "It read 11:42 PM." | | 10 | "She kicked the corrugated sheet" | | 11 | "It groaned and collapsed into" | | 12 | "It was charged, heavy with" | | 13 | "It smelled like the cold," | | 14 | "Her thumb rested on the" | | 15 | "She stepped through the threshold," | | 16 | "He handed the bone token" | | 17 | "Her breath caught in her" | | 18 | "It was an abandoned station," | | 19 | "She saw glass jars containing" |
| | ratio | 0.384 | |
| 28.49% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 73 | | matches | | 0 | "The rain over north London" | | 1 | "Harlow Quinn kept her pace" | | 2 | "Her closely cropped salt-and-pepper hair" | | 3 | "Tomás Herrera was running scared." | | 4 | "He was fast, younger by" | | 5 | "He sprinted in erratic bursts," | | 6 | "Every few strides, his hand" | | 7 | "Quinn had picked up his" | | 8 | "She had waited outside that" | | 9 | "The intelligence was thin—whispers through" | | 10 | "It was all she had" | | 11 | "Herrera cut hard to the" | | 12 | "Quinn closed the distance with" | | 13 | "She vaulted the low brick" | | 14 | "Her voice had the flat," | | 15 | "He threw his weight against" | | 16 | "The metal shrieked as it" | | 17 | "Quinn reached the archway three" | | 18 | "She pressed her back to" | | 19 | "It read 11:42 PM." |
| | ratio | 0.863 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 73 | | matches | | 0 | "If she walked out onto" | | 1 | "If she turned back to" |
| | ratio | 0.027 | |
| 60.44% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 6 | | matches | | 0 | "The intelligence was thin—whispers through vice channels about an unlicensed street medic patching up bodies that shouldn't have been breathing, let alone bleed…" | | 1 | "Beyond lay not an alley, but a yawning mouth of crumbling Victorian masonry that plunged downward into the earth." | | 2 | "But if she radioed in a pursuit into an unregistered subterranean shaft beneath Camden, the same faceless inspectors who had shredded Morris’s incident reports …" | | 3 | "With trembling fingers, he reached deep into his coat pocket and pulled out a small, curved object that looked like a sliver of polished animal rib, notched wit…" | | 4 | "She saw glass jars containing liquids that gave off their own pale light; she saw bundles of dried roots that seemed to twist when no one was touching them; she…" | | 5 | "She had heard the name twice before, both times spat through broken teeth by informants who ended up dead in the Thames before their statements could be typed." |
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| 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 | |