| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 2 | | adverbTags | | 0 | "Tomás said quietly [quietly]" | | 1 | "He gestured subtly [subtly]" |
| | dialogueSentences | 12 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.5 | | effectiveRatio | 0.333 | |
| 76.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1296 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "sharply" | | 1 | "quickly" | | 2 | "very" | | 3 | "softly" | | 4 | "slowly" |
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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) | |
| 7.41% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1296 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | |
| | highlights | | 0 | "echo" | | 1 | "footsteps" | | 2 | "flicker" | | 3 | "uncanny" | | 4 | "pulse" | | 5 | "clandestine" | | 6 | "mechanical" | | 7 | "whisper" | | 8 | "silence" | | 9 | "peril" | | 10 | "echoed" | | 11 | "flicked" | | 12 | "navigate" | | 13 | "scanning" | | 14 | "etched" | | 15 | "throbbed" | | 16 | "silk" | | 17 | "calculating" | | 18 | "velvet" | | 19 | "charged" | | 20 | "electric" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 87 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 87 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1286 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 90.17% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1170 | | uniqueNames | 15 | | maxNameDensity | 1.2 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Market" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 14 | | Raven | 3 | | Nest | 3 | | Veil | 4 | | Market | 9 | | London | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 1 | | Metropolitan | 1 | | Tomás | 7 | | Tube | 1 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Herrera" | | 6 | "Tomás" | | 7 | "Morris" |
| | places | | 0 | "Soho" | | 1 | "Veil" | | 2 | "Market" | | 3 | "London" | | 4 | "Metropolitan" |
| | globalScore | 0.902 | | windowScore | 1 | |
| 80.56% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like it belonged to someone temper" | | 1 | "something like burnt jasmine laced with iron" |
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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 | 1286 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 30.62 | | std | 19.27 | | cv | 0.629 | | sampleLengths | | 0 | 63 | | 1 | 62 | | 2 | 58 | | 3 | 25 | | 4 | 66 | | 5 | 7 | | 6 | 51 | | 7 | 40 | | 8 | 57 | | 9 | 52 | | 10 | 19 | | 11 | 58 | | 12 | 10 | | 13 | 49 | | 14 | 24 | | 15 | 13 | | 16 | 40 | | 17 | 61 | | 18 | 2 | | 19 | 39 | | 20 | 31 | | 21 | 18 | | 22 | 43 | | 23 | 9 | | 24 | 37 | | 25 | 32 | | 26 | 5 | | 27 | 23 | | 28 | 62 | | 29 | 16 | | 30 | 18 | | 31 | 32 | | 32 | 20 | | 33 | 23 | | 34 | 22 | | 35 | 11 | | 36 | 16 | | 37 | 20 | | 38 | 5 | | 39 | 27 | | 40 | 6 | | 41 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 87 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 203 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 5 | | flaggedSentences | 14 | | totalSentences | 95 | | ratio | 0.147 | | matches | | 0 | "She adjusted the collar of her trench coat and checked the weighted watch strapped to her left wrist—leather worn thin from years of use—a small talisman grounding her when chaos threatened." | | 1 | "The uncanny thing was the faint glow from an old, green neon sign barely illuminating the entrance — the distinctive green light spelling out a name: The Raven’s Nest." | | 2 | "Then, a soft mechanical click, almost inaudible beneath the ambient noise—a hidden door sliding open somewhere to her right." | | 3 | "The space gave off a harsh whisper of friction—a threshold into the unknown." | | 4 | "The Raven’s Nest was more than just a bar; it was a gateway." | | 5 | "And now, a lead tip she couldn’t ignore had pointed her towards this very place—a suspect intertwined with the Market’s dark corridors." | | 6 | "The muted hum of the bar faded into a low, eerie silence broken only by occasional muffled voices speaking in clipped tones—barter in this subterranean world came with peril." | | 7 | "Ever since the rumors surfaced of those tokens being the only legal entry, she considered how the Market’s gatekeepers might react to an outsider like herself—especially one marked by determination and a badge." | | 8 | "The man’s olive skin caught faint light; his short curly hair looked like it belonged to someone tempered by the streets rather than this hidden world." | | 9 | "She’d heard of him—former paramedic who’d lost his NHS license for helping the supernatural, a healer who operated in the grey spaces, tending wounds no hospital dared touch." | | 10 | "The abandoned Tube station—normally deserted and a relic of forgotten commutes—throbbed now with an unsettling vitality." | | 11 | "Stalls lined the curved platforms, piled high with forbidden objects: shimmering potions sealed in cracked glass; threads of luminous spider silk; talismans pulsating with energy." | | 12 | "She recognized no faces save for Tomás, but she felt eyes on her—hidden, calculating." | | 13 | "The rain above was distant now; here, time slowed, coiling into the unknown." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1184 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 47 | | adverbRatio | 0.03969594594594594 | | lyAdverbCount | 22 | | lyAdverbRatio | 0.018581081081081082 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 13.54 | | std | 7.68 | | cv | 0.568 | | sampleLengths | | 0 | 15 | | 1 | 23 | | 2 | 25 | | 3 | 8 | | 4 | 11 | | 5 | 12 | | 6 | 31 | | 7 | 17 | | 8 | 12 | | 9 | 29 | | 10 | 7 | | 11 | 18 | | 12 | 24 | | 13 | 12 | | 14 | 16 | | 15 | 14 | | 16 | 7 | | 17 | 19 | | 18 | 17 | | 19 | 15 | | 20 | 10 | | 21 | 13 | | 22 | 4 | | 23 | 13 | | 24 | 8 | | 25 | 28 | | 26 | 11 | | 27 | 10 | | 28 | 30 | | 29 | 22 | | 30 | 4 | | 31 | 15 | | 32 | 29 | | 33 | 29 | | 34 | 10 | | 35 | 13 | | 36 | 3 | | 37 | 33 | | 38 | 4 | | 39 | 20 | | 40 | 6 | | 41 | 7 | | 42 | 16 | | 43 | 24 | | 44 | 9 | | 45 | 26 | | 46 | 17 | | 47 | 9 | | 48 | 2 | | 49 | 28 |
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| 69.47% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4421052631578947 | | totalSentences | 95 | | uniqueOpeners | 42 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 83 | | matches | | 0 | "Then, a soft mechanical click," | | 1 | "Sometimes, that uncertainty was the" | | 2 | "Ever since the rumors surfaced" |
| | ratio | 0.036 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 83 | | matches | | 0 | "She adjusted the collar of" | | 1 | "Her pulse accelerated, but she" | | 2 | "She paused, hand hovering at" | | 3 | "She knew the stories." | | 4 | "Her mind ticked through the" | | 5 | "She reached into her coat" | | 6 | "Her gut screamed caution." | | 7 | "She’d heard of him—former paramedic" | | 8 | "His voice was low but" | | 9 | "He gestured subtly toward a" | | 10 | "Her fingers twitched with frustration." | | 11 | "He studied her a beat" | | 12 | "It was an archaic token," | | 13 | "She recognized no faces save" | | 14 | "They moved silently past a" | | 15 | "She swallowed hard and nodded," | | 16 | "They stopped at a niche" | | 17 | "Her brown eyes burned through" | | 18 | "She slipped past the curtain." |
| | ratio | 0.229 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 83 | | matches | | 0 | "Detective Harlow Quinn’s breath puffed" | | 1 | "The city's usual haze had" | | 2 | "A figure darted between shadowed" | | 3 | "Quinn’s boot met the slick" | | 4 | "She adjusted the collar of" | | 5 | "The suspect turned sharply, disappearing" | | 6 | "The worn stone stairs led" | | 7 | "The uncanny thing was the" | | 8 | "Her pulse accelerated, but she" | | 9 | "The neon buzz hummed overhead," | | 10 | "Quinn’s eyes adjusted quickly to" | | 11 | "Walls lined with yellowed maps" | | 12 | "Shadows gathered thickly here, pooling" | | 13 | "Quinn’s gaze snapped to a" | | 14 | "The scent of damp wood" | | 15 | "She paused, hand hovering at" | | 16 | "The space gave off a" | | 17 | "She knew the stories." | | 18 | "The Raven’s Nest was more" | | 19 | "Tonight wasn’t scheduled for the" |
| | ratio | 0.675 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 83 | | matches | | 0 | "To follow blindly might mean" | | 1 | "Even with her military precision" | | 2 | "If anyone could navigate the" |
| | ratio | 0.036 | |
| 76.72% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 5 | | matches | | 0 | "The neon buzz hummed overhead, weaving itself into the low murmur of clandestine voices and clinking glasses that came from deeper within the bar." | | 1 | "But deeper still lay the entrance to the Veil Market, the underground supernatural bazaar that emerged only under a full moon, shifting locations in abandoned s…" | | 2 | "Without a whisper more, Quinn slipped through the hidden door and descended a narrower set of stone stairs that led down to a space thick with shadow and expect…" | | 3 | "She’d heard of him—former paramedic who’d lost his NHS license for helping the supernatural, a healer who operated in the grey spaces, tending wounds no hospita…" | | 4 | "His voice was low but steady, a pragmatic timbre that hadn’t yet betrayed surprise at her presence." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 66.67% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Tomás whispered (whisper)" |
| | dialogueSentences | 12 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.333 | | effectiveRatio | 0.167 | |