| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.94% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1231 | | totalAiIsmAdverbs | 1 | | 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) | |
| 55.32% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1231 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "measured" | | 2 | "familiar" | | 3 | "gloom" | | 4 | "maw" | | 5 | "weight" | | 6 | "glint" | | 7 | "standard" | | 8 | "vibrated" | | 9 | "echoing" | | 10 | "tracing" |
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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 | 67 | | matches | (empty) | |
| 78.89% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 67 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 67 | | 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 | 1 | | markdownWords | 12 | | totalWords | 1225 | | ratio | 0.01 | | matches | | 0 | "If you follow the line, Harlow, don't stop when the tracks end." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 1220 | | uniqueNames | 22 | | maxNameDensity | 0.9 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | Harlow | 2 | | Quinn | 11 | | Metropolitan | 1 | | Police | 1 | | November | 1 | | Herrera | 8 | | Soho | 1 | | Seville | 1 | | Northern | 1 | | Blitz | 1 | | Saint | 1 | | Christopher | 1 | | London | 1 | | Thames | 1 | | Morris | 4 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Scotland | 1 | | Yard | 1 | | Tomás | 2 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" | | 7 | "Yard" | | 8 | "Tomás" |
| | places | | 0 | "Metropolitan" | | 1 | "Soho" | | 2 | "Seville" | | 3 | "London" | | 4 | "Thames" | | 5 | "Scotland" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 1 | | matches | | 0 | "roots that seemed to twitch in their twine bindings, and vendors whispering over parchment maps with ink that flowed and shifted across the page" |
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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 | 1225 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 67 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 42.24 | | std | 28.94 | | cv | 0.685 | | sampleLengths | | 0 | 28 | | 1 | 82 | | 2 | 24 | | 3 | 2 | | 4 | 122 | | 5 | 21 | | 6 | 52 | | 7 | 18 | | 8 | 28 | | 9 | 19 | | 10 | 67 | | 11 | 43 | | 12 | 79 | | 13 | 17 | | 14 | 71 | | 15 | 25 | | 16 | 12 | | 17 | 33 | | 18 | 61 | | 19 | 41 | | 20 | 7 | | 21 | 104 | | 22 | 40 | | 23 | 7 | | 24 | 40 | | 25 | 57 | | 26 | 46 | | 27 | 21 | | 28 | 58 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 67 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 188 | | matches | | 0 | "was currently swinging" | | 1 | "was staring" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 67 | | ratio | 0.06 | | matches | | 0 | "Herrera moved with an agile, frantic grace—curly dark brown hair plastered to his skull by the downpour, a faded canvas duffel bag clutched against his ribs." | | 1 | "As she descended, the low rumble of street-level traffic died away, replaced by an unsettling hum that vibrated in the fillings of her teeth—a low, thrumming murmur of hundreds of voices echoing through tiled tunnels." | | 2 | "Quinn watched through the shadows as the former paramedic reached into his jacket, pulled up his left sleeve—exposing a jagged, pale scar that ran the length of his forearm—and retrieved a small, polished object from his pocket." | | 3 | "Stalls fashioned from salvage—old railway cars, shipping crates, hand-carved mahogany panels—were illuminated by flickering oil lamps and glass globes filled with cold, emerald phosphorescence." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1238 | | adjectiveStacks | 2 | | stackExamples | | 0 | "exact same burnt-wire sweetness." | | 1 | "narrow, shadow-drenched gap" |
| | adverbCount | 19 | | adverbRatio | 0.015347334410339256 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.007269789983844911 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 67 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 67 | | mean | 18.28 | | std | 10.34 | | cv | 0.565 | | sampleLengths | | 0 | 28 | | 1 | 21 | | 2 | 24 | | 3 | 20 | | 4 | 17 | | 5 | 24 | | 6 | 2 | | 7 | 38 | | 8 | 26 | | 9 | 37 | | 10 | 9 | | 11 | 12 | | 12 | 21 | | 13 | 18 | | 14 | 34 | | 15 | 18 | | 16 | 3 | | 17 | 25 | | 18 | 19 | | 19 | 8 | | 20 | 15 | | 21 | 22 | | 22 | 22 | | 23 | 9 | | 24 | 4 | | 25 | 13 | | 26 | 17 | | 27 | 26 | | 28 | 30 | | 29 | 12 | | 30 | 11 | | 31 | 17 | | 32 | 16 | | 33 | 20 | | 34 | 35 | | 35 | 25 | | 36 | 12 | | 37 | 10 | | 38 | 23 | | 39 | 9 | | 40 | 37 | | 41 | 15 | | 42 | 11 | | 43 | 21 | | 44 | 9 | | 45 | 7 | | 46 | 11 | | 47 | 24 | | 48 | 11 | | 49 | 58 |
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| 76.12% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4925373134328358 | | totalSentences | 67 | | uniqueOpeners | 33 | |
| 50.51% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 66 | | matches | | 0 | "Only the padlock was currently" |
| | ratio | 0.015 | |
| 98.79% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 66 | | matches | | 0 | "She checked the alleyway mouth" | | 1 | "She had been on his" | | 2 | "She’d pulled his file three" | | 3 | "He grabbed the edge of" | | 4 | "His olive skin was pale" | | 5 | "It wasn't the dead, damp" | | 6 | "It smelled of ozone, scorched" | | 7 | "They had found his badge" | | 8 | "She drew a deep, steadying" | | 9 | "Her beam cut through hanging" | | 10 | "It was pale and notched," | | 11 | "He pressed the bone token" | | 12 | "She had heard the name" | | 13 | "She looked back up the" | | 14 | "She had no backup, no" | | 15 | "Her left hand moved to" | | 16 | "She remembered Morris handing her" | | 17 | "She checked the clasp on" | | 18 | "She did not run." | | 19 | "She moved with quiet, deliberate" |
| | ratio | 0.303 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 66 | | matches | | 0 | "The rain over Camden did" | | 1 | "Detective Harlow Quinn wiped a" | | 2 | "She checked the alleyway mouth" | | 3 | "She had been on his" | | 4 | "Herrera moved with an agile," | | 5 | "She’d pulled his file three" | | 6 | "Quinn rounded the corner of" | | 7 | "Herrera was already halfway down" | | 8 | "Herrera didn't hesitate." | | 9 | "He grabbed the edge of" | | 10 | "Quinn barked, the command sharp" | | 11 | "Herrera paused at the threshold" | | 12 | "His olive skin was pale" | | 13 | "Quinn caught the glint of" | | 14 | "Quinn reached the gap in" | | 15 | "The opening smelled wrong." | | 16 | "It wasn't the dead, damp" | | 17 | "It smelled of ozone, scorched" | | 18 | "They had found his badge" | | 19 | "The department had ruled it" |
| | ratio | 0.712 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 66 | | matches | | 0 | "Before her lay an iron" | | 1 | "If she died down here," | | 2 | "*If you follow the line," |
| | ratio | 0.045 | |
| 32.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 8 | | matches | | 0 | "Quinn rounded the corner of the hoarding, her hand resting instinctively on the grip of the baton concealed beneath her coat." | | 1 | "His olive skin was pale with exhaustion, his warm brown eyes wide with an emotion that wasn't guilt, but sheer, unadulterated dread." | | 2 | "As she descended, the low rumble of street-level traffic died away, replaced by an unsettling hum that vibrated in the fillings of her teeth—a low, thrumming mu…" | | 3 | "At the base of the stairs, the platform corridor opened into a vast, vaulted subterranean hall that shouldn't have fit beneath the foundations of Camden." | | 4 | "Quinn watched through the shadows as the former paramedic reached into his jacket, pulled up his left sleeve—exposing a jagged, pale scar that ran the length of…" | | 5 | "Through the haze of aromatic smoke, she saw things that defied the logic of eighteen years on the force: jars of thick, shimmering liquids that glowed without a…" | | 6 | "She had heard the name whispered in the interrogation rooms by informants who ended up dead within forty-eight hours of speaking it." | | 7 | "A black market that moved with the lunar cycle, impossible to map, impossible to police." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |