| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 43 | | tagDensity | 0.302 | | leniency | 0.605 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1963 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 61.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1963 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "warmth" | | 1 | "weight" | | 2 | "race" | | 3 | "crystal" | | 4 | "silk" | | 5 | "calculating" | | 6 | "flicked" | | 7 | "stomach" | | 8 | "fractured" | | 9 | "silence" |
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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 | 143 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 143 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 173 | | 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 | 1961 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 76 | | wordCount | 1523 | | uniqueNames | 22 | | maxNameDensity | 2.04 | | worstName | "Rory" | | maxWindowNameDensity | 4 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 1 | | January | 1 | | Golden | 1 | | Empress | 1 | | Prague | 1 | | Silas | 6 | | Talisker | 1 | | Rory | 31 | | Cardiff | 1 | | Taff | 1 | | Canton | 1 | | Nia | 19 | | Law | 1 | | Inns | 1 | | Court | 1 | | Crown | 1 | | Brendan | 1 | | Carter | 2 | | Irish | 1 | | Jennifer | 1 | | Evan | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Rory" | | 4 | "Nia" | | 5 | "Brendan" | | 6 | "Carter" | | 7 | "Jennifer" | | 8 | "Evan" |
| | places | | 0 | "January" | | 1 | "Prague" | | 2 | "Cardiff" | | 3 | "Canton" | | 4 | "Law" |
| | globalScore | 0.482 | | windowScore | 0.333 | |
| 97.92% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 96 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite touching" | | 1 | "as if testing the ripeness of fruit" |
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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 | 1961 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 173 | | matches | | 0 | "undercut that Rory" | | 1 | "spoken that name" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 38.45 | | std | 34.83 | | cv | 0.906 | | sampleLengths | | 0 | 156 | | 1 | 107 | | 2 | 1 | | 3 | 124 | | 4 | 31 | | 5 | 24 | | 6 | 2 | | 7 | 18 | | 8 | 64 | | 9 | 2 | | 10 | 24 | | 11 | 63 | | 12 | 68 | | 13 | 13 | | 14 | 4 | | 15 | 22 | | 16 | 68 | | 17 | 3 | | 18 | 3 | | 19 | 53 | | 20 | 40 | | 21 | 6 | | 22 | 38 | | 23 | 2 | | 24 | 42 | | 25 | 56 | | 26 | 7 | | 27 | 3 | | 28 | 6 | | 29 | 49 | | 30 | 56 | | 31 | 65 | | 32 | 56 | | 33 | 11 | | 34 | 5 | | 35 | 48 | | 36 | 19 | | 37 | 3 | | 38 | 73 | | 39 | 23 | | 40 | 32 | | 41 | 84 | | 42 | 7 | | 43 | 4 | | 44 | 70 | | 45 | 25 | | 46 | 86 | | 47 | 12 | | 48 | 45 | | 49 | 54 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 143 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 257 | | matches | (empty) | |
| 76.80% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 3 | | flaggedSentences | 4 | | totalSentences | 173 | | ratio | 0.023 | | matches | | 0 | "The face beneath the makeup was older, sharper, the softness around the mouth carved away, but the eyes—green, calculating—were the same." | | 1 | "Her posture, too, had changed; she held her spine like a sword in its scabbard, straight and ready." | | 2 | "The jazz record clicked; the needle lifted from the groove." | | 3 | "Time had not merely passed; it had transmuted them into opposing elements, prosecutor and delivery girl, the one who stayed and fought within the system and the one who had fled it entirely." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 862 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.024361948955916472 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004640371229698376 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 173 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 173 | | mean | 11.34 | | std | 9.29 | | cv | 0.82 | | sampleLengths | | 0 | 20 | | 1 | 11 | | 2 | 16 | | 3 | 7 | | 4 | 10 | | 5 | 27 | | 6 | 23 | | 7 | 22 | | 8 | 4 | | 9 | 7 | | 10 | 9 | | 11 | 6 | | 12 | 8 | | 13 | 16 | | 14 | 4 | | 15 | 17 | | 16 | 20 | | 17 | 18 | | 18 | 18 | | 19 | 1 | | 20 | 10 | | 21 | 8 | | 22 | 10 | | 23 | 13 | | 24 | 19 | | 25 | 34 | | 26 | 9 | | 27 | 21 | | 28 | 5 | | 29 | 9 | | 30 | 17 | | 31 | 4 | | 32 | 12 | | 33 | 8 | | 34 | 2 | | 35 | 5 | | 36 | 8 | | 37 | 5 | | 38 | 42 | | 39 | 14 | | 40 | 8 | | 41 | 2 | | 42 | 2 | | 43 | 11 | | 44 | 11 | | 45 | 5 | | 46 | 8 | | 47 | 8 | | 48 | 9 | | 49 | 9 |
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| 41.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.2658959537572254 | | totalSentences | 173 | | uniqueOpeners | 46 | |
| 51.28% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 130 | | matches | | 0 | "Maybe it buoyed her." | | 1 | "Then she walked toward the" |
| | ratio | 0.015 | |
| 81.54% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 130 | | matches | | 0 | "He polished a tumbler with" | | 1 | "His left leg bore his" | | 2 | "He didn’t glance up." | | 3 | "He tilted his chin toward" | | 4 | "She headed for the far" | | 5 | "She unwound her scarf and" | | 6 | "Her left wrist itched." | | 7 | "She scratched the crescent scar" | | 8 | "Her hair, once a tangled," | | 9 | "She hadn’t spoken that name" | | 10 | "It tasted of Cardiff rain" | | 11 | "She pulled out the stool" | | 12 | "Her perfume smelled of bergamot" | | 13 | "Her manicured nails, ovals of" | | 14 | "She used to know every" | | 15 | "It had not existed in" | | 16 | "She looked up at the" | | 17 | "He’d stopped polishing." | | 18 | "His hazel gaze stayed fixed" | | 19 | "She took Nia in." |
| | ratio | 0.346 | |
| 6.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 118 | | totalSentences | 130 | | matches | | 0 | "The green neon above The" | | 1 | "Rory shouldered the door open," | | 2 | "The Golden Empress logo peeled" | | 3 | "The air held the resin" | | 4 | "Silas stood behind the bar," | | 5 | "He polished a tumbler with" | | 6 | "His left leg bore his" | | 7 | "He didn’t glance up." | | 8 | "He tilted his chin toward" | | 9 | "She headed for the far" | | 10 | "The leather exhaled beneath her" | | 11 | "She unwound her scarf and" | | 12 | "Her left wrist itched." | | 13 | "She scratched the crescent scar" | | 14 | "Rory stared at the backbar" | | 15 | "The voice came from the" | | 16 | "A woman rose, her hip" | | 17 | "Amber liquid sloshed against the" | | 18 | "Rory’s reflection in the mirror" | | 19 | "A tailored wool coat the" |
| | ratio | 0.908 | |
| 38.46% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 130 | | matches | | 0 | "Now she prosecuted for the" |
| | ratio | 0.008 | |
| 29.48% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 63 | | technicalSentenceCount | 10 | | matches | | 0 | "Silas stood behind the bar, his grey-streaked auburn hair catching the amber light, his neatly trimmed beard framing a jaw that had weathered worse winters than…" | | 1 | "Behind Silas, old maps papered the walls, borders drawn in languages that had since gone to war and redrawn themselves." | | 2 | "The girl who’d once worn combat boots to a moot court and spray-painted slogans on the side of the Law building now wore the armor of the establishment she had …" | | 3 | "The sound was short, joyless, a single note that died in the resin-thick air." | | 4 | "His hazel gaze stayed fixed on the glass in his hand, but his shoulders had gone still, the alert stillness of a man who had spent decades reading rooms for thr…" | | 5 | "In the quiet, Rory heard the hum of the green neon sign outside, the rattle of the pipes in the walls, the distant thrum of a city that had swallowed her whole …" | | 6 | "The maps behind Silas showed countries that had fractured and renamed themselves while the two women sat in their separate silences, becoming strangers." | | 7 | "She thought of Evan’s hand around her throat in a kitchen that smelled of gas and lilies, the way his thumb had pressed against her windpipe as if testing the r…" | | 8 | "The expensive coat that had replaced the paint-stained dungarees." | | 9 | "He limped back to his maps and his photographs, and the green neon buzzed on, painting the empty stool beside her a color that did not exist in nature." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 43 | | tagDensity | 0.163 | | leniency | 0.326 | | rawRatio | 0 | | effectiveRatio | 0 | |