| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 87.34% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1185 | | totalAiIsmAdverbs | 3 | | 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) | |
| 24.05% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1185 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "depths" | | 1 | "standard" | | 2 | "structure" | | 3 | "rhythmic" | | 4 | "velvet" | | 5 | "sinister" | | 6 | "familiar" | | 7 | "weight" | | 8 | "comforting" | | 9 | "chaotic" | | 10 | "footsteps" | | 11 | "quickened" | | 12 | "echo" | | 13 | "silence" | | 14 | "echoed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 119 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 119 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 123 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1183 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 1119 | | uniqueNames | 11 | | maxNameDensity | 0.63 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 7 | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Morris | 2 | | Veil | 1 | | Market | 1 | | Met | 1 | | Tube | 1 | | Coyle | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Morris" | | 4 | "Coyle" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 57.41% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 3 | | matches | | 0 | "something like a low, mournful chant" | | 1 | "looked like walking shadows" | | 2 | "felt like a physical presence" |
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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 | 1183 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 123 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 33.8 | | std | 29.73 | | cv | 0.879 | | sampleLengths | | 0 | 47 | | 1 | 39 | | 2 | 45 | | 3 | 39 | | 4 | 10 | | 5 | 42 | | 6 | 41 | | 7 | 47 | | 8 | 34 | | 9 | 10 | | 10 | 48 | | 11 | 55 | | 12 | 17 | | 13 | 3 | | 14 | 139 | | 15 | 36 | | 16 | 28 | | 17 | 45 | | 18 | 11 | | 19 | 5 | | 20 | 125 | | 21 | 7 | | 22 | 38 | | 23 | 19 | | 24 | 15 | | 25 | 36 | | 26 | 8 | | 27 | 11 | | 28 | 14 | | 29 | 9 | | 30 | 14 | | 31 | 25 | | 32 | 5 | | 33 | 44 | | 34 | 72 |
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| 99.37% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 119 | | matches | | 0 | "was gone" | | 1 | "been overwhelmed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 180 | | matches | | 0 | "was selling" | | 1 | "was walking" |
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| 73.17% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 123 | | ratio | 0.024 | | matches | | 0 | "The smell hit her first—wet brick, stale beer, and something else, something metallic and cold, like old blood." | | 1 | "It wasn't chaotic; it was a layered, structured sound." | | 2 | "From inside, she could hear the echo of a scuffle—a grunt, a muffled curse." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1128 | | adjectiveStacks | 2 | | stackExamples | | 0 | "small, bone-coloured token." | | 1 | "thick, iron-grey beard," |
| | adverbCount | 18 | | adverbRatio | 0.015957446808510637 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005319148936170213 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 123 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 123 | | mean | 9.62 | | std | 5.52 | | cv | 0.574 | | sampleLengths | | 0 | 15 | | 1 | 10 | | 2 | 22 | | 3 | 15 | | 4 | 14 | | 5 | 10 | | 6 | 19 | | 7 | 13 | | 8 | 4 | | 9 | 9 | | 10 | 3 | | 11 | 9 | | 12 | 9 | | 13 | 18 | | 14 | 3 | | 15 | 4 | | 16 | 3 | | 17 | 15 | | 18 | 9 | | 19 | 9 | | 20 | 9 | | 21 | 16 | | 22 | 5 | | 23 | 9 | | 24 | 4 | | 25 | 7 | | 26 | 14 | | 27 | 2 | | 28 | 12 | | 29 | 3 | | 30 | 5 | | 31 | 11 | | 32 | 5 | | 33 | 29 | | 34 | 2 | | 35 | 8 | | 36 | 4 | | 37 | 4 | | 38 | 6 | | 39 | 12 | | 40 | 22 | | 41 | 8 | | 42 | 16 | | 43 | 11 | | 44 | 20 | | 45 | 6 | | 46 | 11 | | 47 | 3 | | 48 | 20 | | 49 | 3 |
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| 34.55% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.2845528455284553 | | totalSentences | 123 | | uniqueOpeners | 35 | |
| 85.47% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 117 | | matches | | 0 | "Instead, her senses sharpened." | | 1 | "Then he stopped." | | 2 | "Then a voice, low and" |
| | ratio | 0.026 | |
| 69.57% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 44 | | totalSentences | 117 | | matches | | 0 | "Her focus was a single" | | 1 | "Her worn leather watch, soaked" | | 2 | "He turned a corner onto" | | 3 | "He didn't stop there." | | 4 | "He ran past, a shadow" | | 5 | "She pushed harder, the alley" | | 6 | "She paused at the edge," | | 7 | "Her training screamed at her." | | 8 | "You smoked them out or" | | 9 | "Her jaw tightened." | | 10 | "Her gut, a knot of" | | 11 | "She drew her standard-issue radio." | | 12 | "She holstered the radio." | | 13 | "She took the first step" | | 14 | "She pulled the heavy fabric" | | 15 | "She had heard whispers of" | | 16 | "It sprawled in an abandoned" | | 17 | "She saw people in fine" | | 18 | "He was walking quickly, nervously," | | 19 | "He kept looking over his" |
| | ratio | 0.376 | |
| 41.20% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 98 | | totalSentences | 117 | | matches | | 0 | "Detective Harlow Quinn ignored the" | | 1 | "Her focus was a single" | | 2 | "The suspect vaulted a bollard," | | 3 | "Quinn followed, her boots finding" | | 4 | "Her worn leather watch, soaked" | | 5 | "He turned a corner onto" | | 6 | "The Raven’s Nest, a green" | | 7 | "He didn't stop there." | | 8 | "He ran past, a shadow" | | 9 | "Quinn’s lungs burned." | | 10 | "She pushed harder, the alley" | | 11 | "The smell hit her first—wet" | | 12 | "The alley ended." | | 13 | "A wrought-iron grate, rusted and" | | 14 | "A set of stairs spiralled" | | 15 | "A faint, flickering orange light" | | 16 | "She paused at the edge," | | 17 | "Her training screamed at her." | | 18 | "Foxes had their holes." | | 19 | "You smoked them out or" |
| | ratio | 0.838 | |
| 42.74% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 117 | | matches | | 0 | "If she let him disappear" |
| | ratio | 0.009 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 1 | | matches | | 0 | "She saw people in fine silks bargaining with things that looked like walking shadows." |
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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 | |