| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 73 | | tagDensity | 0.096 | | leniency | 0.192 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.68% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1803 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "very" | | 1 | "lightly" | | 2 | "really" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 63.95% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1803 | | totalAiIsms | 13 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | word | "practiced ease" | | count | 1 |
| | 7 | | | 8 | | | 9 | |
| | highlights | | 0 | "warmth" | | 1 | "familiar" | | 2 | "footsteps" | | 3 | "lilt" | | 4 | "tinge" | | 5 | "silence" | | 6 | "practiced ease" | | 7 | "eyebrow" | | 8 | "coded" | | 9 | "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 | 103 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 103 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 169 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1818 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1108 | | uniqueNames | 15 | | maxNameDensity | 0.72 | | worstName | "Tommy" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | London | 1 | | Raven | 2 | | Nest | 2 | | Silas | 6 | | Cardiff | 3 | | Welsh | 1 | | Vaughan | 1 | | Tommy | 8 | | Constitutional | 1 | | Law | 1 | | Rory | 7 | | Taf | 1 | | Cathays | 1 | | Tom | 2 | | Waits | 2 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Vaughan" | | 4 | "Tommy" | | 5 | "Rory" | | 6 | "Tom" | | 7 | "Waits" |
| | places | | 0 | "London" | | 1 | "Cardiff" | | 2 | "Constitutional" | | 3 | "Taf" | | 4 | "Cathays" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.55 | | wordCount | 1818 | | matches | | 0 | "Not the awkward silence of strangers, but the heavy, textured silence of two people who remembered the" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 169 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 91 | | mean | 19.98 | | std | 22.66 | | cv | 1.134 | | sampleLengths | | 0 | 71 | | 1 | 39 | | 2 | 2 | | 3 | 15 | | 4 | 1 | | 5 | 9 | | 6 | 95 | | 7 | 44 | | 8 | 1 | | 9 | 52 | | 10 | 2 | | 11 | 1 | | 12 | 77 | | 13 | 92 | | 14 | 3 | | 15 | 3 | | 16 | 21 | | 17 | 9 | | 18 | 1 | | 19 | 11 | | 20 | 10 | | 21 | 25 | | 22 | 45 | | 23 | 9 | | 24 | 1 | | 25 | 19 | | 26 | 19 | | 27 | 6 | | 28 | 45 | | 29 | 5 | | 30 | 10 | | 31 | 16 | | 32 | 46 | | 33 | 4 | | 34 | 3 | | 35 | 39 | | 36 | 22 | | 37 | 22 | | 38 | 4 | | 39 | 33 | | 40 | 58 | | 41 | 17 | | 42 | 2 | | 43 | 1 | | 44 | 62 | | 45 | 5 | | 46 | 2 | | 47 | 1 | | 48 | 10 | | 49 | 50 |
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| 91.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 103 | | matches | | 0 | "was cropped" | | 1 | "being asked" | | 2 | "being noticed" | | 3 | "being asked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 184 | | matches | (empty) | |
| 7.61% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 169 | | ratio | 0.047 | | matches | | 0 | "He raised a glass in return, already pouring her usual — a half-pint of dark ale." | | 1 | "She stared at the crescent scar on her left wrist — that old mark from when she was nine, fell off the garden wall in Cardiff, landed on a broken plant pot — and for a moment she was back there." | | 2 | "Not the voice itself — deeper now, rougher — but the way it shaped her name." | | 3 | "Only his eyes were the same — pale green, warm, startled." | | 4 | "He used to play guitar — badly, enthusiastically — at open mic nights at the Taf in Cathays." | | 5 | "Not cruel — she could hear the absence of malice in his voice — but honest in a way that burned." | | 6 | "Someone fed coins into the jukebox in the corner — Tom Waits, gravelly and aching." | | 7 | "That was the thing about Tommy — he delivered his heaviest lines like they weighed nothing, and you had to catch them on the way down or they'd hit the floor and shatter." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 897 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.033444816053511704 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007803790412486065 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 169 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 169 | | mean | 10.76 | | std | 10.37 | | cv | 0.964 | | sampleLengths | | 0 | 20 | | 1 | 26 | | 2 | 5 | | 3 | 1 | | 4 | 1 | | 5 | 18 | | 6 | 7 | | 7 | 16 | | 8 | 16 | | 9 | 2 | | 10 | 15 | | 11 | 1 | | 12 | 9 | | 13 | 15 | | 14 | 7 | | 15 | 9 | | 16 | 41 | | 17 | 23 | | 18 | 5 | | 19 | 3 | | 20 | 17 | | 21 | 19 | | 22 | 1 | | 23 | 7 | | 24 | 16 | | 25 | 13 | | 26 | 12 | | 27 | 4 | | 28 | 2 | | 29 | 1 | | 30 | 15 | | 31 | 30 | | 32 | 32 | | 33 | 4 | | 34 | 34 | | 35 | 24 | | 36 | 19 | | 37 | 11 | | 38 | 3 | | 39 | 3 | | 40 | 4 | | 41 | 3 | | 42 | 14 | | 43 | 9 | | 44 | 1 | | 45 | 8 | | 46 | 3 | | 47 | 10 | | 48 | 16 | | 49 | 4 |
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| 64.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.41420118343195267 | | totalSentences | 169 | | uniqueOpeners | 70 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 84 | | matches | | 0 | "Only his eyes were the" | | 1 | "Then he nodded." | | 2 | "Just a tiny fracture in" |
| | ratio | 0.036 | |
| 72.38% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 84 | | matches | | 0 | "She nodded at Silas behind" | | 1 | "He raised a glass in" | | 2 | "His signet ring caught the" | | 3 | "She stared at the crescent" | | 4 | "She didn't turn." | | 5 | "She heard footsteps, a pause," | | 6 | "She hadn't heard anyone say" | | 7 | "He'd been her course-mate at" | | 8 | "His cheekbones cut sharp beneath" | | 9 | "His hair, once thick and" | | 10 | "He wore a coat that" | | 11 | "He stared at her." | | 12 | "She stared back." | | 13 | "He rubbed the back of" | | 14 | "He set a fresh ale" | | 15 | "She studied his hands wrapped" | | 16 | "He used to play guitar" | | 17 | "She remembered Tommy at twenty-two," | | 18 | "He'd been the kind of" | | 19 | "She wondered when he'd stopped" |
| | ratio | 0.369 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 84 | | matches | | 0 | "The rain had been falling" | | 1 | "Aurora pushed through the door" | | 2 | "The warmth hit her face." | | 3 | "The smell of aged whiskey" | | 4 | "She nodded at Silas behind" | | 5 | "He raised a glass in" | | 6 | "His signet ring caught the" | | 7 | "Silas let out a short" | | 8 | "Rory wrapped both hands around" | | 9 | "The condensation seeped into the" | | 10 | "She stared at the crescent" | | 11 | "The door opened behind her." | | 12 | "She didn't turn." | | 13 | "The Raven's Nest had its" | | 14 | "She heard footsteps, a pause," | | 15 | "The voice hit her like" | | 16 | "That particular Cardiff lilt on" | | 17 | "She hadn't heard anyone say" | | 18 | "Thomas Vaughan sat two stools" | | 19 | "The Tommy she remembered was" |
| | ratio | 0.833 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 35.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 6 | | matches | | 0 | "The Tommy she remembered was soft-edged, round-faced, the kind of boy who laughed too easily and ate chips with curry sauce at three in the morning after too ma…" | | 1 | "His cheekbones cut sharp beneath skin that had the grey-yellow tinge of someone who either hadn't seen the sun in months or had seen too much of it through the …" | | 2 | "His hair, once thick and sandy-brown, had thinned at the temples and was cropped short in a way that made his ears stick out." | | 3 | "He wore a coat that was too large for him now, the shoulders bunching where his own had narrowed." | | 4 | "Silas appeared at the edge of her vision, polishing a glass with the practiced ease of someone who'd learned to read a room decades ago." | | 5 | "Not the awkward silence of strangers, but the heavy, textured silence of two people who remembered the same things and couldn't figure out how to talk about the…" |
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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 | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 73 | | tagDensity | 0.055 | | leniency | 0.11 | | rawRatio | 0 | | effectiveRatio | 0 | |