| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 95.34% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1073 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1073 | | totalAiIsms | 23 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | word | "moths to flame" | | count | 1 |
| | 16 | | | 17 | | | 18 | | | 19 | | | 20 | |
| | highlights | | 0 | "rhythmic" | | 1 | "cacophony" | | 2 | "whisper" | | 3 | "macabre" | | 4 | "absolutely" | | 5 | "raced" | | 6 | "navigating" | | 7 | "loomed" | | 8 | "reminder" | | 9 | "electric" | | 10 | "pulse" | | 11 | "familiar" | | 12 | "amidst" | | 13 | "potential" | | 14 | "aligned" | | 15 | "moths to flame" | | 16 | "quickened" | | 17 | "unwavering" | | 18 | "determined" | | 19 | "unspoken" | | 20 | "depths" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "eyes widened" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 64 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 64 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 64 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1079 | | ratio | 0 | | matches | (empty) | |
| 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 | 33 | | wordCount | 1079 | | uniqueNames | 15 | | maxNameDensity | 0.74 | | worstName | "Tomás" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Tomás" | | discoveredNames | | Harlow | 3 | | Quinn | 1 | | Soho | 1 | | Herrera | 1 | | Tomás | 8 | | Raven | 2 | | Nest | 2 | | London | 2 | | Charlotte | 1 | | Street | 1 | | Veil | 2 | | Market | 6 | | Camden | 1 | | Tube | 1 | | Metropolitan | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Tomás" | | 4 | "Raven" | | 5 | "Market" | | 6 | "Metropolitan" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Charlotte" | | 3 | "Street" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1079 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 64 | | matches | (empty) | |
| 40.81% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 19 | | mean | 56.79 | | std | 16.63 | | cv | 0.293 | | sampleLengths | | 0 | 97 | | 1 | 84 | | 2 | 49 | | 3 | 70 | | 4 | 47 | | 5 | 61 | | 6 | 48 | | 7 | 55 | | 8 | 86 | | 9 | 43 | | 10 | 60 | | 11 | 36 | | 12 | 43 | | 13 | 55 | | 14 | 47 | | 15 | 37 | | 16 | 56 | | 17 | 64 | | 18 | 41 |
| |
| 99.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 64 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 172 | | matches | | 0 | "was heading" | | 1 | "was weaving" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 6 | | flaggedSentences | 15 | | totalSentences | 64 | | ratio | 0.234 | | matches | | 0 | "The alleyways shrouded in shadow posed little threat to someone like her — not when her quarry, the one with secrets tied to the recent spate of bizarre occurrences, had just darted into the mazelike darkness." | | 1 | "Harlow knew Tomás in passing — a former paramedic fallen from grace, now mingling with those who dealt in shadows and whispers." | | 2 | "A hurried transaction outside The Raven's Nest, his back to her as he exchanged words — and likely something more — with a figure she couldn't place." | | 3 | "But The Raven's Nest wasn't her target tonight; she was after something more elusive, more cunning." | | 4 | "A smirk tugged at her lips—he was heading underground." | | 5 | "The Veil Market lay beneath, its entry hidden in the abandoned passageways of the old Camden Tube station—a concealed city beneath her city." | | 6 | "She heard them then — the distant murmur of many voices mingling with the scent of spices and smoke." | | 7 | "Her hesitation wasn't born of fear, but caution; the Market was legendary for its danger as much as its wares." | | 8 | "But so too was she, albeit in different circles — the Metropolitan's own legend in investigation." | | 9 | "No words were necessary; she handed him the token, received only an inscrutable look before the gate groaned open." | | 10 | "Tomás was here amidst the chaos; she felt it more than saw it, an instinct honed from years in the field." | | 11 | "The press of bodies finally yielded — a figure, familiar and brisk, was weaving through the crowd." | | 12 | "Such blundering on her part was rare; she wouldn’t allow it again." | | 13 | "The chase wasn't over — not here, not now, and certainly not while so much lay unspoken between Tomás and the secrets that she relentlessly pursued through London’s depths." | | 14 | "The stage was set; only the players and their choices would decide its denouement." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1079 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.028730305838739572 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.012974976830398516 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 64 | | echoCount | 0 | | echoWords | (empty) | |
| 88.16% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 64 | | mean | 16.86 | | std | 6.24 | | cv | 0.37 | | sampleLengths | | 0 | 20 | | 1 | 23 | | 2 | 18 | | 3 | 36 | | 4 | 10 | | 5 | 27 | | 6 | 22 | | 7 | 25 | | 8 | 10 | | 9 | 27 | | 10 | 12 | | 11 | 12 | | 12 | 29 | | 13 | 13 | | 14 | 16 | | 15 | 15 | | 16 | 9 | | 17 | 23 | | 18 | 16 | | 19 | 16 | | 20 | 19 | | 21 | 10 | | 22 | 15 | | 23 | 20 | | 24 | 13 | | 25 | 16 | | 26 | 19 | | 27 | 20 | | 28 | 15 | | 29 | 13 | | 30 | 22 | | 31 | 20 | | 32 | 16 | | 33 | 9 | | 34 | 15 | | 35 | 19 | | 36 | 4 | | 37 | 15 | | 38 | 20 | | 39 | 21 | | 40 | 6 | | 41 | 21 | | 42 | 9 | | 43 | 16 | | 44 | 14 | | 45 | 13 | | 46 | 17 | | 47 | 6 | | 48 | 20 | | 49 | 12 |
| |
| 71.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.4375 | | totalSentences | 64 | | uniqueOpeners | 28 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 64 | | matches | | 0 | "Suddenly, a stall burst in" | | 1 | "Such blundering on her part" |
| | ratio | 0.031 | |
| 88.75% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 64 | | matches | | 0 | "She moved with purpose, brown" | | 1 | "She caught a glimpse of" | | 2 | "His olive skin would blend" | | 3 | "She hadn't had enough to" | | 4 | "Her feet splashed through puddles," | | 5 | "She didn’t pause to care" | | 6 | "She caught another glimpse of" | | 7 | "She knew better than to" | | 8 | "She’d promised herself never to" | | 9 | "She heard them then —" | | 10 | "She hesitated, the worn leather" | | 11 | "Her hesitation wasn't born of" | | 12 | "Her attention tunneled to the" | | 13 | "Her quarry wouldn’t vanish without" | | 14 | "She kept to the fringes," | | 15 | "She ignored them, probing deeper" | | 16 | "He was careful, but not" | | 17 | "Her bearing remained military, an" | | 18 | "Her heart leaped in time" | | 19 | "They locked on hers, recognition" |
| | ratio | 0.328 | |
| 53.75% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 64 | | matches | | 0 | "Detective Harlow Quinn tightened her" | | 1 | "The rhythmic pattering drowned out" | | 2 | "She moved with purpose, brown" | | 3 | "The alleyways shrouded in shadow" | | 4 | "Tomás Herrera, always one step" | | 5 | "She caught a glimpse of" | | 6 | "Harlow knew Tomás in passing" | | 7 | "His olive skin would blend" | | 8 | "The thought of their last" | | 9 | "A hurried transaction outside The" | | 10 | "She hadn't had enough to" | | 11 | "Her feet splashed through puddles," | | 12 | "She didn’t pause to care" | | 13 | "She caught another glimpse of" | | 14 | "A smirk tugged at her" | | 15 | "The Veil Market lay beneath," | | 16 | "Breath rasped through her teeth," | | 17 | "She knew better than to" | | 18 | "The bone token, a macabre" | | 19 | "She’d promised herself never to" |
| | ratio | 0.813 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 64 | | matches | (empty) | | ratio | 0 | |
| 68.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 6 | | matches | | 0 | "Sheltered now from the rain, the tap-drip-run of water off her coat continued, forming small rivulets that raced toward grates." | | 1 | "She hesitated, the worn leather of her watch catching beneath the cuff of her coat, reminding her of her instinct and duty." | | 2 | "A bone-thin figure in a tattered greatcoat stood guard, as if conjured by her presence." | | 3 | "Faces of all kinds, some familiar from dossiers, others that might’ve only existed in storybooks, wandered amidst the aisle of curiosities." | | 4 | "Voices battered against her awareness, snippets of conversation that promised everything for a price." | | 5 | "They locked on hers, recognition flashing through, before he gathered himself and darted anew, pushing through the throng with singular determination." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |