| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 8 | | tagDensity | 0.75 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 81.45% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1078 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "suddenly" | | 1 | "sharply" | | 2 | "quickly" |
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| 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1078 | | totalAiIsms | 26 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | word | "down her spine" | | count | 1 |
| | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | | | 23 | | | 24 | |
| | highlights | | 0 | "symphony" | | 1 | "scanned" | | 2 | "kaleidoscope" | | 3 | "pounding" | | 4 | "cacophony" | | 5 | "glint" | | 6 | "gloom" | | 7 | "loomed" | | 8 | "facade" | | 9 | "chill" | | 10 | "down her spine" | | 11 | "resolve" | | 12 | "etched" | | 13 | "echoing" | | 14 | "palpable" | | 15 | "spectral" | | 16 | "familiar" | | 17 | "warmth" | | 18 | "depths" | | 19 | "solitary" | | 20 | "echo" | | 21 | "pulse" | | 22 | "delving" | | 23 | "determined" | | 24 | "synchronized" |
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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 | 1 | | narrationSentences | 57 | | matches | | |
| 67.67% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 57 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 59 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1069 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 95.81% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 1015 | | uniqueNames | 15 | | maxNameDensity | 1.08 | | worstName | "Harlow" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Harlow" | | discoveredNames | | London | 2 | | Harlow | 11 | | Quinn | 2 | | Morris | 2 | | Metropolitan | 1 | | Veil | 2 | | Market | 5 | | Tube | 1 | | Ignoring | 1 | | Tomás | 3 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Seville | 1 | | Hesitance | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Veil" | | 4 | "Tomás" | | 5 | "Herrera" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Hesitance" |
| | places | | 0 | "London" | | 1 | "Market" | | 2 | "Seville" |
| | globalScore | 0.958 | | windowScore | 1 | |
| 16.07% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 3 | | matches | | 0 | "quite grasp or let go" | | 1 | "door that seemed to hang ajar like a gaping wound in the city's facade" | | 2 | "seemed carved from the dull stone the tunnels birthed, his dark curls tousled from the Market's claustrophobic warmth" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.935 | | wordCount | 1069 | | matches | | 0 | "not just an answer but perhaps something of herself, eclipsed once too often by the" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 59 | | matches | | 0 | "make that understanding" |
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| 31.07% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 20 | | mean | 53.45 | | std | 13.83 | | cv | 0.259 | | sampleLengths | | 0 | 71 | | 1 | 65 | | 2 | 71 | | 3 | 43 | | 4 | 61 | | 5 | 59 | | 6 | 54 | | 7 | 72 | | 8 | 62 | | 9 | 57 | | 10 | 48 | | 11 | 33 | | 12 | 56 | | 13 | 24 | | 14 | 59 | | 15 | 53 | | 16 | 30 | | 17 | 57 | | 18 | 62 | | 19 | 32 |
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| 99.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 57 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 164 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 2 | | flaggedSentences | 9 | | totalSentences | 59 | | ratio | 0.153 | | matches | | 0 | "There was a glimpse of the suspect—a flash of shadowy movement that danced at the periphery of Harlow's vision." | | 1 | "As she rounded the corner, the suspect turned back, the glimmer of nocturnal streetlights catching the glint of mischief—or perhaps fear—in his eyes." | | 2 | "Harlow skidded to a halt at the threshold; her gaze caught the faint, eerie glow of pale light flickering from beyond the opening." | | 3 | "Harlow’s breath sucked in sharply as she realized the descent led into one of those whispers she’d heard obstructed by Metropolitan walls—the Veil Market." | | 4 | "Candles pooled in nacreous wax, casting the few patrons—figures draped in shadow or faces threaded with the implements of secrecy—into relief against walls that might once have been part of a forgotten Tube station." | | 5 | "She remembered the whispers of entry requirements—bone tokens, beguiling markers essential for passage." | | 6 | "Lacking one wasn't an option now; her quarry had slipped inside, and she had followed a spectral line that couldn’t be abandoned." | | 7 | "Ahead, between the swathes of shadows, she spotted a familiar figure—Tomás Herrera." | | 8 | "She felt the pulse of destiny or danger—lines blurred by secrets that were no longer tethered to the light above." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1027 | | adjectiveStacks | 1 | | stackExamples | | 0 | "pressing cold against her" |
| | adverbCount | 34 | | adverbRatio | 0.033106134371957155 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005842259006815969 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 59 | | echoCount | 0 | | echoWords | (empty) | |
| 80.22% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 59 | | mean | 18.12 | | std | 6.35 | | cv | 0.351 | | sampleLengths | | 0 | 25 | | 1 | 29 | | 2 | 17 | | 3 | 22 | | 4 | 19 | | 5 | 24 | | 6 | 15 | | 7 | 25 | | 8 | 22 | | 9 | 9 | | 10 | 23 | | 11 | 20 | | 12 | 19 | | 13 | 24 | | 14 | 18 | | 15 | 26 | | 16 | 23 | | 17 | 10 | | 18 | 25 | | 19 | 12 | | 20 | 17 | | 21 | 17 | | 22 | 11 | | 23 | 24 | | 24 | 20 | | 25 | 12 | | 26 | 16 | | 27 | 34 | | 28 | 3 | | 29 | 8 | | 30 | 11 | | 31 | 13 | | 32 | 22 | | 33 | 11 | | 34 | 17 | | 35 | 9 | | 36 | 11 | | 37 | 16 | | 38 | 17 | | 39 | 12 | | 40 | 21 | | 41 | 23 | | 42 | 11 | | 43 | 13 | | 44 | 25 | | 45 | 21 | | 46 | 13 | | 47 | 16 | | 48 | 21 | | 49 | 16 |
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| 93.79% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5932203389830508 | | totalSentences | 59 | | uniqueOpeners | 35 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 57 | | matches | | 0 | "Suddenly the suspect veered sharply" | | 1 | "Perhaps brazen in the movement," |
| | ratio | 0.035 | |
| 79.65% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 57 | | matches | | 0 | "Her sharp eyes scanned the" | | 1 | "she shouted, her voice cutting" | | 2 | "She sped up, weaving through" | | 3 | "Her quarry, a lithe silhouette" | | 4 | "She leapt over a toppled" | | 5 | "She cursed under her breath," | | 6 | "Her partner, DS Morris, loomed" | | 7 | "She entered the passage with" | | 8 | "She found herself in a" | | 9 | "Her suspect had vanished into" | | 10 | "She remembered the whispers of" | | 11 | "Her gaze caught a brusque" | | 12 | "he crooned, the words sliding" | | 13 | "His olive skin seemed carved" | | 14 | "she greeted, breaking through the" | | 15 | "His eyes, reminiscent of the" | | 16 | "She sensed in him the" | | 17 | "Her history with Morris reminded" | | 18 | "she eased, a faint nod" | | 19 | "She felt the pulse of" |
| | ratio | 0.351 | |
| 91.58% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 57 | | matches | | 0 | "Rain pounded the London streets" | | 1 | "Detective Harlow Quinn, drenched to" | | 2 | "Her sharp eyes scanned the" | | 3 | "she shouted, her voice cutting" | | 4 | "She sped up, weaving through" | | 5 | "Her quarry, a lithe silhouette" | | 6 | "A sensory cacophony enveloped Harlow" | | 7 | "She leapt over a toppled" | | 8 | "She cursed under her breath," | | 9 | "Harlow muttered, recalling the whisperings" | | 10 | "Her partner, DS Morris, loomed" | | 11 | "Whatever supernatural strings had tangled" | | 12 | "Harlow skidded to a halt" | | 13 | "A chill curled its way" | | 14 | "She entered the passage with" | | 15 | "She found herself in a" | | 16 | "Each echoing step seemed to" | | 17 | "Harlow’s breath sucked in sharply" | | 18 | "A place where reality twisted" | | 19 | "Stalls lined with glittering oddities" |
| | ratio | 0.737 | |
| 87.72% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 57 | | matches | | 0 | "Before she could close the" |
| | ratio | 0.018 | |
| 51.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 47 | | technicalSentenceCount | 6 | | matches | | 0 | "Her sharp eyes scanned the kaleidoscope of umbrellas and blurred faces that filled the busy pavement ahead." | | 1 | "There was a glimpse of the suspect—a flash of shadowy movement that danced at the periphery of Harlow's vision." | | 2 | "Candles pooled in nacreous wax, casting the few patrons—figures draped in shadow or faces threaded with the implements of secrecy—into relief against walls that…" | | 3 | "Lacking one wasn't an option now; her quarry had slipped inside, and she had followed a spectral line that couldn’t be abandoned." | | 4 | "She sensed in him the knowledge of being an outsider who played with the wondrous and the wicked outside sanctioned lines." | | 5 | "Step by determined step, she pursued the threads laid before her, each heartbeat synchronized to the will of a woman who refused to let the veil conceal what sh…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "he crooned, the words sliding oily from his mouth" | | 1 | "Tomás replied, his voice smooth but filled with subtext" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "Harlow muttered (mutter)" |
| | dialogueSentences | 8 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0.667 | | effectiveRatio | 0.5 | |