| 82.35% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "Harlow said quietly [quietly]" |
| | dialogueSentences | 17 | | tagDensity | 0.412 | | leniency | 0.824 | | rawRatio | 0.143 | | effectiveRatio | 0.118 | |
| 92.76% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1381 | | totalAiIsmAdverbs | 2 | | 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) | |
| 74.66% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1381 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "silk" | | 1 | "shattered" | | 2 | "etched" | | 3 | "charm" | | 4 | "weight" |
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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 | 69 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 69 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 79 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 76 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1365 | | ratio | 0 | | matches | (empty) | |
| 97.22% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 1 | | matches | | 0 | "Unofficially, it breathed." |
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| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 975 | | uniqueNames | 17 | | maxNameDensity | 1.33 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Eva" | | discoveredNames | | Camden | 2 | | Market | 2 | | Quinn | 2 | | Tube | 1 | | Veil | 2 | | Kowalski | 1 | | British | 2 | | Museum | 2 | | Ancient | 1 | | History | 1 | | Oxford | 1 | | Aurora | 2 | | Harlow | 13 | | Morris | 1 | | Eva | 13 | | Compass | 1 | | Shade | 1 |
| | persons | | 0 | "Market" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Museum" | | 4 | "Aurora" | | 5 | "Harlow" | | 6 | "Morris" | | 7 | "Eva" | | 8 | "Compass" |
| | places | | 0 | "Camden" | | 1 | "British" | | 2 | "Ancient" | | 3 | "Oxford" |
| | globalScore | 0.833 | | windowScore | 0.667 | |
| 53.85% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 2 | | matches | | 0 | "something between fear and recognition" | | 1 | "seemed paler in the yellow light" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.733 | | wordCount | 1365 | | matches | | 0 | "not the dry flake of age but the wet residue of recent application" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 79 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 54.6 | | std | 38.58 | | cv | 0.707 | | sampleLengths | | 0 | 116 | | 1 | 84 | | 2 | 5 | | 3 | 114 | | 4 | 15 | | 5 | 9 | | 6 | 10 | | 7 | 114 | | 8 | 42 | | 9 | 12 | | 10 | 67 | | 11 | 80 | | 12 | 110 | | 13 | 5 | | 14 | 11 | | 15 | 74 | | 16 | 18 | | 17 | 78 | | 18 | 56 | | 19 | 99 | | 20 | 20 | | 21 | 50 | | 22 | 85 | | 23 | 64 | | 24 | 27 |
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| 84.92% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 69 | | matches | | 0 | "been emptied" | | 1 | "were held" | | 2 | "were etched" | | 3 | "being struck" | | 4 | "being folded" |
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| 82.35% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 170 | | matches | | 0 | "was not looking" | | 1 | "was looking" | | 2 | "was already pulling" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 2 | | flaggedSentences | 12 | | totalSentences | 79 | | ratio | 0.152 | | matches | | 0 | "She was forty-one, and the sharp line of her jaw looked carved from the same discipline that governed her bearing—military precision in every line." | | 1 | "Once a month, when the moon swelled to full, the Veil Market assembled in these tunnels—an underground black market where entry required a bone token and where vendors traded in enchanted goods, banned alchemical substances, and information that never touched paper." | | 2 | "Her worn leather satchel sat open at her hip, spilling old papers—museum archives, no doubt—like entrails." | | 3 | "Broken glass glittered like ice across the floor, and the air smelled of sulfur and myrrh and something sweeter—perhaps the banned substance itself, spilled from shattered vials." | | 4 | "But his body bore no wounds Harlow could see—no blood, no burn, no rupture of the kind she had come to recognize in the years since DS Morris." | | 5 | "She examined the victim’s hands—clean, unburned, the fingernails intact." | | 6 | "The needle was indeed fixed in one direction—pointing precisely toward a bricked-up archway at the tunnel’s end, a dead end that led nowhere except to the old service lines." | | 7 | "The verdigris came away faintly on her glove, not the dry flake of age but the wet residue of recent application—copper sulfate, painted on." | | 8 | "She knew the source texts; she had seen them in Eva’s satchel before, in the British Museum’s restricted archives." | | 9 | "The military precision in her posture was not aggression; it was a frame for thought." | | 10 | "Behind her, the market stirred—the distant sound of stalls being struck, silk being folded, the full moon’s influence waning even in hidden places." | | 11 | "But the nervous habit had stopped—her hair stayed where it was, and her green eyes watched Harlow with the dawning understanding that the detective was right." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 993 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.025176233635448138 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.012084592145015106 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 79 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 79 | | mean | 17.28 | | std | 14.67 | | cv | 0.849 | | sampleLengths | | 0 | 16 | | 1 | 23 | | 2 | 9 | | 3 | 24 | | 4 | 24 | | 5 | 20 | | 6 | 9 | | 7 | 3 | | 8 | 41 | | 9 | 31 | | 10 | 5 | | 11 | 27 | | 12 | 14 | | 13 | 16 | | 14 | 31 | | 15 | 26 | | 16 | 4 | | 17 | 11 | | 18 | 9 | | 19 | 10 | | 20 | 9 | | 21 | 19 | | 22 | 27 | | 23 | 23 | | 24 | 4 | | 25 | 4 | | 26 | 28 | | 27 | 2 | | 28 | 6 | | 29 | 9 | | 30 | 18 | | 31 | 7 | | 32 | 12 | | 33 | 17 | | 34 | 40 | | 35 | 5 | | 36 | 5 | | 37 | 15 | | 38 | 65 | | 39 | 5 | | 40 | 4 | | 41 | 29 | | 42 | 9 | | 43 | 12 | | 44 | 24 | | 45 | 8 | | 46 | 19 | | 47 | 5 | | 48 | 7 | | 49 | 4 |
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| 49.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.34177215189873417 | | totalSentences | 79 | | uniqueOpeners | 27 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 65 | | matches | | 0 | "Unofficially, it breathed." | | 1 | "Once a month, when the" |
| | ratio | 0.031 | |
| 66.15% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 65 | | matches | | 0 | "Her boots made no sound" | | 1 | "She was forty-one, and the" | | 2 | "She crouched near the tunnel" | | 3 | "Her worn leather satchel sat" | | 4 | "She was twenty-six, a research" | | 5 | "Her voice was soft, academic," | | 6 | "His mouth was open." | | 7 | "His eyes were open." | | 8 | "Her gloves were black leather," | | 9 | "She examined the victim’s hands—clean," | | 10 | "His pockets had been emptied" | | 11 | "It was small brass, its" | | 12 | "It should have been trembling." | | 13 | "It should have been alive." | | 14 | "She studied the compass." | | 15 | "She reached out with a" | | 16 | "She knew the source texts;" | | 17 | "Her sharp jaw was set," | | 18 | "She walked to the stall," | | 19 | "she said, her voice lower" |
| | ratio | 0.385 | |
| 67.69% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 51 | | totalSentences | 65 | | matches | | 0 | "The stairwell down from Camden" | | 1 | "Harlow Quinn took the steps" | | 2 | "Her boots made no sound" | | 3 | "She was forty-one, and the" | | 4 | "The abandoned Tube station beneath" | | 5 | "Tonight, the market was still" | | 6 | "Eva Kowalski was already there." | | 7 | "She crouched near the tunnel" | | 8 | "Her worn leather satchel sat" | | 9 | "She was twenty-six, a research" | | 10 | "Eva’s green eyes lifted to" | | 11 | "Her voice was soft, academic," | | 12 | "Harlow moved closer, her coat" | | 13 | "The victim lay in an" | | 14 | "The young man on the" | | 15 | "His mouth was open." | | 16 | "His eyes were open." | | 17 | "Her gloves were black leather," | | 18 | "She examined the victim’s hands—clean," | | 19 | "His pockets had been emptied" |
| | ratio | 0.785 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 8 | | matches | | 0 | "She was forty-one, and the sharp line of her jaw looked carved from the same discipline that governed her bearing—military precision in every line." | | 1 | "Tonight, the market was still half-assembled, its stalls draped in shadow and silk, but the air carried a wrongness that had nothing to do with the usual ozone …" | | 2 | "She crouched near the tunnel wall, her curly red hair catching the sick yellow glow of a sodium lamp that should have been dark for thirty years." | | 3 | "The victim lay in an alcove that had served, earlier that evening, as a vendor’s stall for alchemical tinctures." | | 4 | "It was small brass, its face etched with protective sigils that caught the lamplight in sharp lines." | | 5 | "The needle was indeed fixed in one direction—pointing precisely toward a bricked-up archway at the tunnel’s end, a dead end that led nowhere except to the old s…" | | 6 | "Her sharp jaw was set, her brown eyes cold with the particular clarity of a detective who had learned to distrust the easy answer." | | 7 | "And as she reached the arch, her gloved hand finding the loose brick that didn’t belong, she heard Eva set her satchel down with a soft thud." |
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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 | 7 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.412 | | leniency | 0.824 | | rawRatio | 0 | | effectiveRatio | 0 | |