| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 26 | | tagDensity | 0.346 | | leniency | 0.692 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.40% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1603 | | totalAiIsmAdverbs | 5 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
| | 2 | | | 3 | | | 4 | |
| | highlights | | 0 | "slightly" | | 1 | "deliberately" | | 2 | "lazily" | | 3 | "perfectly" | | 4 | "really" |
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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) | |
| 46.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1603 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "fluttered" | | 1 | "vibrated" | | 2 | "measured" | | 3 | "traced" | | 4 | "scanned" | | 5 | "echoing" | | 6 | "perfect" | | 7 | "crystal" | | 8 | "footsteps" | | 9 | "etched" | | 10 | "pulse" | | 11 | "quickened" | | 12 | "charged" | | 13 | "stark" | | 14 | "silence" | | 15 | "familiar" | | 16 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 131 | | matches | | 0 | "looked relieved" | | 1 | "was worried" |
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| 77.43% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 4 | | narrationSentences | 131 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 148 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 14 | | totalWords | 1591 | | ratio | 0.009 | | matches | | 0 | "Property of E. Kowalski." | | 1 | "Veil" | | 2 | "Some doors you open, Harlow. Some doors open you." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 91.68% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1286 | | uniqueNames | 17 | | maxNameDensity | 1.17 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Tube | 1 | | Harlow | 15 | | Quinn | 2 | | Metropolitan | 1 | | Police | 1 | | Patel | 8 | | Underground | 1 | | Maglite | 1 | | Morris | 1 | | Whitechapel | 1 | | Kowalski | 5 | | Aurora | 1 | | Vale | 1 | | Eva | 4 | | British | 1 | | Museum | 1 | | Shoreditch | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Patel" | | 3 | "Morris" | | 4 | "Kowalski" | | 5 | "Eva" | | 6 | "Museum" |
| | places | | 0 | "Metropolitan" | | 1 | "Whitechapel" | | 2 | "British" | | 3 | "Shoreditch" |
| | globalScore | 0.917 | | windowScore | 1 | |
| 89.02% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 82 | | glossingSentenceCount | 2 | | matches | | 0 | "explorers and, apparently, the dead" | | 1 | "something like lightning after a storm" |
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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 | 1591 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 148 | | matches | | 0 | "knew that name" | | 1 | "find that door" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 30.02 | | std | 23.95 | | cv | 0.798 | | sampleLengths | | 0 | 77 | | 1 | 56 | | 2 | 11 | | 3 | 37 | | 4 | 84 | | 5 | 22 | | 6 | 49 | | 7 | 10 | | 8 | 30 | | 9 | 44 | | 10 | 54 | | 11 | 4 | | 12 | 9 | | 13 | 36 | | 14 | 54 | | 15 | 2 | | 16 | 29 | | 17 | 5 | | 18 | 72 | | 19 | 69 | | 20 | 4 | | 21 | 64 | | 22 | 16 | | 23 | 3 | | 24 | 4 | | 25 | 61 | | 26 | 13 | | 27 | 14 | | 28 | 20 | | 29 | 4 | | 30 | 37 | | 31 | 67 | | 32 | 20 | | 33 | 5 | | 34 | 5 | | 35 | 24 | | 36 | 33 | | 37 | 84 | | 38 | 43 | | 39 | 9 | | 40 | 6 | | 41 | 26 | | 42 | 40 | | 43 | 21 | | 44 | 2 | | 45 | 13 | | 46 | 35 | | 47 | 30 | | 48 | 22 | | 49 | 37 |
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| 75.80% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 11 | | totalSentences | 131 | | matches | | 0 | "been sealed" | | 1 | "been opened" | | 2 | "were cauterized" | | 3 | "been heated" | | 4 | "been smashed" | | 5 | "been carved" | | 6 | "was scorched" | | 7 | "been arranged" | | 8 | "been engraved" | | 9 | "been questioned" | | 10 | "was engraved" | | 11 | "being tucked" | | 12 | "been opened" |
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| 71.18% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 207 | | matches | | 0 | "wasn’t feeling" | | 1 | "was directing" | | 2 | "was rapidly fraying" | | 3 | "was carrying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 2 | | flaggedSentences | 11 | | totalSentences | 148 | | ratio | 0.074 | | matches | | 0 | "The abandoned Tube platform smelled of wet concrete, ozone, and something sharper—burnt wiring mixed with the metallic tang of blood." | | 1 | "Someone had dragged portable generators down here; their diesel hum vibrated through the soles of her boots." | | 2 | "His throat had been opened with surgical neatness—almost too neat." | | 3 | "They looked freshly cut; the grooves were clean, no grime inside them yet." | | 4 | "Within the burn mark, the dust had been arranged—deliberately—into the same three-circle pattern." | | 5 | "Tiny fragments glinted—shards of green glass, or perhaps crystal." | | 6 | "She had seen the symbols at his last known location—the same three interlocking circles." | | 7 | "The same Eva Kowalski who worked in the British Museum’s restricted archives and who had been questioned—but never charged—after a warehouse fire in Shoreditch that left behind melted iron and the scent of myrrh." | | 8 | "He gave her the look she hated—the one that said he was worried about her mental state." | | 9 | "Not just blood and concrete—incense." | | 10 | "And now this pendant, linked to a word she had only ever seen in connection with rumours—whispers from her confidential informants who dealt in things that shouldn’t exist." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1303 | | adjectiveStacks | 1 | | stackExamples | | 0 | "left behind melted iron" |
| | adverbCount | 49 | | adverbRatio | 0.03760552570990023 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.010744435917114352 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 148 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 148 | | mean | 10.75 | | std | 8.59 | | cv | 0.799 | | sampleLengths | | 0 | 20 | | 1 | 35 | | 2 | 20 | | 3 | 1 | | 4 | 1 | | 5 | 23 | | 6 | 16 | | 7 | 17 | | 8 | 11 | | 9 | 2 | | 10 | 16 | | 11 | 19 | | 12 | 11 | | 13 | 11 | | 14 | 11 | | 15 | 10 | | 16 | 19 | | 17 | 20 | | 18 | 2 | | 19 | 7 | | 20 | 15 | | 21 | 5 | | 22 | 17 | | 23 | 5 | | 24 | 13 | | 25 | 8 | | 26 | 1 | | 27 | 10 | | 28 | 2 | | 29 | 28 | | 30 | 3 | | 31 | 19 | | 32 | 5 | | 33 | 2 | | 34 | 7 | | 35 | 8 | | 36 | 10 | | 37 | 21 | | 38 | 10 | | 39 | 13 | | 40 | 4 | | 41 | 3 | | 42 | 6 | | 43 | 13 | | 44 | 23 | | 45 | 12 | | 46 | 11 | | 47 | 5 | | 48 | 13 | | 49 | 13 |
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| 62.39% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.4189189189189189 | | totalSentences | 148 | | uniqueOpeners | 62 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 113 | | matches | | 0 | "Instead, she reached into her" | | 1 | "Even the air seemed to" | | 2 | "Then, abruptly, they stopped." | | 3 | "Somewhere in this city, Eva" | | 4 | "Somewhere nearby, a door that" |
| | ratio | 0.044 | |
| 89.03% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 113 | | matches | | 0 | "He looked relieved to see" | | 1 | "His throat had been opened" | | 2 | "She studied the wound again." | | 3 | "she asked, voice low" | | 4 | "She said nothing." | | 5 | "Her gaze drifted across the" | | 6 | "They looked freshly cut; the" | | 7 | "She stood, knees popping slightly," | | 8 | "Her eyes narrowed at a" | | 9 | "She walked over, boots echoing." | | 10 | "He handed her a Maglite." | | 11 | "She swept the beam across" | | 12 | "She picked one up." | | 13 | "It was warm." | | 14 | "She had seen the symbols" | | 15 | "She had smelled the same" | | 16 | "She believed herself now." | | 17 | "She moved along the platform" | | 18 | "She crouched again and found" | | 19 | "Its casing was tarnished with" |
| | ratio | 0.327 | |
| 88.32% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 113 | | matches | | 0 | "The abandoned Tube platform smelled" | | 1 | "Detective Harlow Quinn stepped off" | | 2 | "The station had been sealed" | | 3 | "Someone had dragged portable generators" | | 4 | "a voice called from the" | | 5 | "DS Patel stood beside the" | | 6 | "He looked relieved to see" | | 7 | "Harlow crossed the platform in" | | 8 | "The victim lay sprawled near" | | 9 | "His throat had been opened" | | 10 | "The cut began just beneath" | | 11 | "Patel said without preamble" | | 12 | "Harlow crouched beside the corpse." | | 13 | "The man’s eyes were open," | | 14 | "She studied the wound again." | | 15 | "The edges were cauterized in" | | 16 | "she asked, voice low" | | 17 | "She said nothing." | | 18 | "The platform felt too still." | | 19 | "Her gaze drifted across the" |
| | ratio | 0.743 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 113 | | matches | (empty) | | ratio | 0 | |
| 58.11% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 59 | | technicalSentenceCount | 7 | | matches | | 0 | "The man’s eyes were open, fixed on the cracked ceiling as though surprised by his own death." | | 1 | "Childhood friend of Aurora Vale, the woman who had been hovering at the edges of three of Harlow’s strangest cases in the last eighteen months." | | 2 | "The same Eva Kowalski who worked in the British Museum’s restricted archives and who had been questioned—but never charged—after a warehouse fire in Shoreditch …" | | 3 | "And now this pendant, linked to a word she had only ever seen in connection with rumours—whispers from her confidential informants who dealt in things that shou…" | | 4 | "She thought of Eva Kowalski’s face the one time they had met: round glasses, curly red hair always being tucked behind her left ear, a worn leather satchel bulg…" | | 5 | "The compass in her coat pocket grew warm against her ribs, as though in agreement." | | 6 | "Harlow Quinn straightened her shoulders, feeling the familiar weight of the leather watch on her wrist like an anchor to a reality that was rapidly fraying at t…" |
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| 13.89% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 2 | | matches | | 0 | "she asked, voice low" | | 1 | "Harlow traced, not touching the mark" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 26 | | tagDensity | 0.269 | | leniency | 0.538 | | rawRatio | 0.143 | | effectiveRatio | 0.077 | |