| 33.33% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 1 | | adverbTags | | 0 | "She inhaled sharply [sharply]" |
| | dialogueSentences | 12 | | tagDensity | 0.417 | | leniency | 0.833 | | rawRatio | 0.2 | | effectiveRatio | 0.167 | |
| 94.97% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 994 | | 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) | |
| 84.91% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 994 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "constructed" | | 1 | "porcelain" | | 2 | "flicked" |
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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 | 75 | | matches | (empty) | |
| 85.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 75 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 977 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 93.31% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 882 | | uniqueNames | 19 | | maxNameDensity | 1.13 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Harlow | 2 | | Quinn | 10 | | Morris | 3 | | Brixton | 1 | | Barbour | 1 | | Tube | 1 | | Metropolitan | 1 | | Police | 1 | | Spanish | 1 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Glock | 1 | | Tomás | 2 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Police" | | 4 | "Herrera" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Tomás" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Brixton" | | 4 | "Veil" | | 5 | "Market" |
| | globalScore | 0.933 | | windowScore | 1 | |
| 94.44% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | glossingSentenceCount | 1 | | matches | | 0 | "sigils that seemed to spin when she looked directly at them" |
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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 | 977 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 81 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 39.08 | | std | 29.66 | | cv | 0.759 | | sampleLengths | | 0 | 104 | | 1 | 78 | | 2 | 2 | | 3 | 72 | | 4 | 8 | | 5 | 106 | | 6 | 16 | | 7 | 1 | | 8 | 38 | | 9 | 27 | | 10 | 27 | | 11 | 59 | | 12 | 32 | | 13 | 10 | | 14 | 75 | | 15 | 22 | | 16 | 50 | | 17 | 42 | | 18 | 61 | | 19 | 31 | | 20 | 18 | | 21 | 55 | | 22 | 15 | | 23 | 12 | | 24 | 16 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 75 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 152 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 81 | | ratio | 0.099 | | matches | | 0 | "The leather watch on her left wrist—DS Morris’s old watch, its face cracked, its band worn smooth—dug into her bone as she pumped her arms." | | 1 | "The suspect—a wiry figure in a waxed Barbour, hood pulled low—vaulted a chain-link fence bordering the railway embankment." | | 2 | "Concrete walls dripped with condensation that smelled of wet stone and something older—myrrh, rotting orchids, the burnt-hair scent of shorted electronics." | | 3 | "A figure blocked the archway leading from the platform into the market proper—a gatekeeper seven feet tall, shoulders wrapped in a shawl of woven hair, face hidden behind a porcelain fox mask." | | 4 | "Behind the gate, the runner produced an ivory disk from his pocket—a bone token carved with spiralling sigils that seemed to spin when she looked directly at them." | | 5 | "The proximity revealed details—etchings on the fox mask depicting scenes of pursuit, hunters becoming hunted, teeth growing from eyes." | | 6 | "The scar on his left forearm—she remembered it from his NHS file, the knife attack that had preceded his dismissal—peeked from beneath his rolled sleeve." | | 7 | "Beyond the iron bars, the runner had reached the far wall of the station, where a temporary wooden door led deeper—into the Veil Market’s shifting heart, the place that moved every full moon according to whispers Quinn had always dismissed as junkie prophecy." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 899 | | adjectiveStacks | 1 | | stackExamples | | 0 | "same copper-sweet stink" |
| | adverbCount | 12 | | adverbRatio | 0.013348164627363738 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0033370411568409346 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 81 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 81 | | mean | 12.06 | | std | 9.42 | | cv | 0.781 | | sampleLengths | | 0 | 17 | | 1 | 24 | | 2 | 25 | | 3 | 38 | | 4 | 18 | | 5 | 7 | | 6 | 4 | | 7 | 23 | | 8 | 5 | | 9 | 21 | | 10 | 2 | | 11 | 5 | | 12 | 21 | | 13 | 10 | | 14 | 3 | | 15 | 2 | | 16 | 3 | | 17 | 28 | | 18 | 8 | | 19 | 8 | | 20 | 17 | | 21 | 17 | | 22 | 14 | | 23 | 17 | | 24 | 33 | | 25 | 6 | | 26 | 10 | | 27 | 1 | | 28 | 6 | | 29 | 32 | | 30 | 9 | | 31 | 14 | | 32 | 4 | | 33 | 20 | | 34 | 7 | | 35 | 28 | | 36 | 6 | | 37 | 3 | | 38 | 22 | | 39 | 6 | | 40 | 3 | | 41 | 4 | | 42 | 19 | | 43 | 8 | | 44 | 1 | | 45 | 1 | | 46 | 25 | | 47 | 25 | | 48 | 14 | | 49 | 11 |
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| 53.09% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.4074074074074074 | | totalSentences | 81 | | uniqueOpeners | 33 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 71 | | matches | | 0 | "Her sharp jaw tightened." | | 1 | "She grabbed the freezing metal," | | 2 | "Her torch beam cut a" | | 3 | "She emerged onto a platform" | | 4 | "Her voice carried the snap" | | 5 | "He pressed it to the" | | 6 | "She stepped closer." | | 7 | "His Saint Christopher medallion caught" | | 8 | "He clutched a medical bag," | | 9 | "He used her first name" | | 10 | "She inhaled sharply" | | 11 | "His warm brown eyes flicked" | | 12 | "He didn’t deny it." | | 13 | "He was purchasing something from" | | 14 | "He was getting away." | | 15 | "She looked at the gate." | | 16 | "She looked down." | | 17 | "She looked up at the" | | 18 | "Her sharp jaw set." | | 19 | "Her military precision demanded closure." |
| | ratio | 0.296 | |
| 16.34% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 71 | | matches | | 0 | "Detective Harlow Quinn’s boots struck" | | 1 | "The leather watch on her" | | 2 | "The suspect—a wiry figure in" | | 3 | "Quinn hit the barrier two" | | 4 | "Her sharp jaw tightened." | | 5 | "She grabbed the freezing metal," | | 6 | "Mud sucked at her boots." | | 7 | "The runner didn’t look back," | | 8 | "The air turned to soup." | | 9 | "Her torch beam cut a" | | 10 | "The architecture shifted." | | 11 | "The walls bowed outward, lined" | | 12 | "She emerged onto a platform" | | 13 | "The abandoned Tube station stretched" | | 14 | "Vendors crowded the tracks where" | | 15 | "A woman with skin like" | | 16 | "A man with too many" | | 17 | "The runner was already twenty" | | 18 | "Quinn’s hand moved to her" | | 19 | "The Metropolitan Police warrant card" |
| | ratio | 0.887 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 12.99% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 6 | | matches | | 0 | "Three years since Morris had died screaming in that warehouse in Brixton, three years of unexplained blood patterns and shadows that moved against the light, an…" | | 1 | "Concrete walls dripped with condensation that smelled of wet stone and something older—myrrh, rotting orchids, the burnt-hair scent of shorted electronics." | | 2 | "The walls bowed outward, lined with ceramic tiles that should have been white but instead displayed an oil-slick iridescence, colours that had no names pulsing …" | | 3 | "Vaulted arches soared overhead, dripping with bioluminescent fungus that painted the scene in shades of infected turquoise." | | 4 | "The scar on his left forearm—she remembered it from his NHS file, the knife attack that had preceded his dismissal—peeked from beneath his rolled sleeve." | | 5 | "Beyond the iron bars, the runner had reached the far wall of the station, where a temporary wooden door led deeper—into the Veil Market’s shifting heart, the pl…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |