| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "She stepped back [back]" |
| | dialogueSentences | 35 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0.143 | | effectiveRatio | 0.057 | |
| 85.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1755 | | totalAiIsmAdverbs | 5 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
| | 2 | | | 3 | |
| | highlights | | 0 | "slightly" | | 1 | "deliberately" | | 2 | "carefully" | | 3 | "lazily" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 74.36% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1755 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "processed" | | 1 | "perfect" | | 2 | "etched" | | 3 | "etch" | | 4 | "resolve" | | 5 | "weight" | | 6 | "standard" | | 7 | "structure" |
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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 | 124 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 124 | | filterMatches | (empty) | | hedgeMatches | | 0 | "happened to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 151 | | 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 | 1768 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 89.94% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1332 | | uniqueNames | 9 | | maxNameDensity | 1.2 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 16 | | Camden | 1 | | Okonkwo | 8 | | Tube | 2 | | Victorian-era | 1 | | Underground | 1 | | Henderson | 1 | | John | 1 | | Doe | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Okonkwo" | | 2 | "Henderson" | | 3 | "John" | | 4 | "Doe" |
| | places | | | globalScore | 0.899 | | windowScore | 1 | |
| 94.44% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 90 | | glossingSentenceCount | 2 | | matches | | 0 | "something close to it" | | 1 | "lines that seemed to shift when viewed from different angles" |
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| 86.88% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.131 | | wordCount | 1768 | | matches | | 0 | "Not unusual underground, but the timing felt pointed" | | 1 | "not north but deeper into the tunnel" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 151 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 30.48 | | std | 21.72 | | cv | 0.713 | | sampleLengths | | 0 | 65 | | 1 | 34 | | 2 | 7 | | 3 | 7 | | 4 | 44 | | 5 | 2 | | 6 | 28 | | 7 | 42 | | 8 | 85 | | 9 | 44 | | 10 | 4 | | 11 | 19 | | 12 | 31 | | 13 | 4 | | 14 | 25 | | 15 | 21 | | 16 | 54 | | 17 | 9 | | 18 | 19 | | 19 | 63 | | 20 | 4 | | 21 | 66 | | 22 | 5 | | 23 | 38 | | 24 | 52 | | 25 | 39 | | 26 | 8 | | 27 | 51 | | 28 | 6 | | 29 | 11 | | 30 | 7 | | 31 | 11 | | 32 | 56 | | 33 | 13 | | 34 | 39 | | 35 | 22 | | 36 | 51 | | 37 | 23 | | 38 | 25 | | 39 | 17 | | 40 | 74 | | 41 | 56 | | 42 | 61 | | 43 | 15 | | 44 | 55 | | 45 | 17 | | 46 | 12 | | 47 | 6 | | 48 | 4 | | 49 | 21 |
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| 93.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 124 | | matches | | 0 | "been placed" | | 1 | "was singed" | | 2 | "was scorched" | | 3 | "been opened" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 211 | | matches | | 0 | "was already walking" | | 1 | "were making" | | 2 | "was going" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 151 | | ratio | 0.073 | | matches | | 0 | "His clothes were clean — a dark coat, pressed slacks, leather shoes." | | 1 | "Not blood — it was too uniform, too black." | | 2 | "Beneath, the skin wasn't charred — it was smooth, pale, and marked with a pattern of concentric rings that faded from deep red at the centre to nothing at the perimeter." | | 3 | "Within the circle, etched with impossible delicacy, was a symbol — three interlocking crescents radiating from a central point." | | 4 | "The crescent motif repeated, but variations appeared — spirals, geometric shapes that hurt the eye if she looked too long, lines that seemed to shift when viewed from different angles." | | 5 | "Not an official maintenance hatch or an emergency exit — a door set into the tunnel wall, wooden, with iron hinges that had no business existing in a Victorian-era Underground station." | | 6 | "It turned, but the door didn't open — something on the other side held it fast." | | 7 | "The gap revealed a rush of warm air and a smell she couldn't place — herbs and smoke and something metallic." | | 8 | "The frame was set flush against the brick, but the mortar around it was wrong — too new, too clean." | | 9 | "The expression was one of expectation — of someone who believed they were about to receive something." | | 10 | "DI Henderson's reports called the underground market a rumour — something informants whispered about in exchange for reduced sentences." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1324 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.027190332326283987 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.0075528700906344415 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 151 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 151 | | mean | 11.71 | | std | 8.47 | | cv | 0.724 | | sampleLengths | | 0 | 18 | | 1 | 14 | | 2 | 24 | | 3 | 9 | | 4 | 10 | | 5 | 24 | | 6 | 7 | | 7 | 7 | | 8 | 13 | | 9 | 31 | | 10 | 2 | | 11 | 28 | | 12 | 3 | | 13 | 18 | | 14 | 21 | | 15 | 12 | | 16 | 15 | | 17 | 15 | | 18 | 12 | | 19 | 11 | | 20 | 20 | | 21 | 5 | | 22 | 11 | | 23 | 9 | | 24 | 4 | | 25 | 3 | | 26 | 11 | | 27 | 1 | | 28 | 4 | | 29 | 14 | | 30 | 5 | | 31 | 7 | | 32 | 7 | | 33 | 3 | | 34 | 2 | | 35 | 12 | | 36 | 4 | | 37 | 25 | | 38 | 8 | | 39 | 6 | | 40 | 7 | | 41 | 19 | | 42 | 9 | | 43 | 11 | | 44 | 4 | | 45 | 3 | | 46 | 8 | | 47 | 9 | | 48 | 5 | | 49 | 14 |
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| 51.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.33112582781456956 | | totalSentences | 151 | | uniqueOpeners | 50 | |
| 29.50% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 113 | | matches | | 0 | "More of the dark circle," |
| | ratio | 0.009 | |
| 60.71% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 113 | | matches | | 0 | "Her flashlight carved a pale" | | 1 | "He was a broad man" | | 2 | "He led her along the" | | 3 | "She kept her torch fixed" | | 4 | "She ducked under the yellow" | | 5 | "His clothes were clean —" | | 6 | "His face was angular, sharp" | | 7 | "She leaned closer, angling her" | | 8 | "She checked his neck for" | | 9 | "He'd either lain down deliberately" | | 10 | "She turned the beam downward" | | 11 | "She crouched again and touched" | | 12 | "It came away clean." | | 13 | "He peered over her shoulder." | | 14 | "She followed the circle's edge" | | 15 | "She checked beneath the body's" | | 16 | "They turned the body carefully" | | 17 | "She photographed it from multiple" | | 18 | "She lowered herself to eye" | | 19 | "It had gone down." |
| | ratio | 0.398 | |
| 48.50% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 113 | | matches | | 0 | "The steel door groaned against" | | 1 | "The air turned wet and" | | 2 | "Her flashlight carved a pale" | | 3 | "Platform 4 hadn't seen a" | | 4 | "Sergeant Okonkwo met her at" | | 5 | "He was a broad man" | | 6 | "He led her along the" | | 7 | "Quinn said nothing." | | 8 | "She kept her torch fixed" | | 9 | "The tunnel mouth gaped like" | | 10 | "She ducked under the yellow" | | 11 | "The unit had set up" | | 12 | "A man lay on his" | | 13 | "His clothes were clean —" | | 14 | "His face was angular, sharp" | | 15 | "Quinn crouched beside the body." | | 16 | "The man's eyes were indeed" | | 17 | "She leaned closer, angling her" | | 18 | "She checked his neck for" | | 19 | "Quinn stood and surveyed the" |
| | ratio | 0.823 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 113 | | matches | (empty) | | ratio | 0 | |
| 74.18% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 5 | | matches | | 0 | "His face was angular, sharp cheekbones, a mouth slightly parted as though he'd been mid-sentence when whatever happened took him." | | 1 | "The crescent motif repeated, but variations appeared — spirals, geometric shapes that hurt the eye if she looked too long, lines that seemed to shift when viewe…" | | 2 | "Not an official maintenance hatch or an emergency exit — a door set into the tunnel wall, wooden, with iron hinges that had no business existing in a Victorian-…" | | 3 | "Her fingers found a small brass compass, cold and heavy, its face etched with protective sigils that matched the symbols on the tunnel walls." | | 4 | "But here was a dead man with no cause of death, lying in a scorch mark that shouldn't exist, holding a tool that pointed toward a door that had no place being i…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.057 | | leniency | 0.114 | | rawRatio | 0 | | effectiveRatio | 0 | |