| 88.89% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 2 | | adverbTags | | 0 | "red hair twisted around [around]" | | 1 | "Quinn said quietly [quietly]" |
| | dialogueSentences | 36 | | tagDensity | 0.417 | | leniency | 0.833 | | rawRatio | 0.133 | | effectiveRatio | 0.111 | |
| 96.12% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1289 | | 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) | |
| 72.85% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1289 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "weight" | | 1 | "etched" | | 2 | "mechanical" | | 3 | "chill" | | 4 | "warmth" |
| |
| 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 | 60 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 60 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1304 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 73.53% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 850 | | uniqueNames | 6 | | maxNameDensity | 1.53 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 13 | | Tube | 2 | | Camden | 1 | | Osei | 4 | | Kowalski | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Osei" | | 3 | "Kowalski" |
| | places | (empty) | | globalScore | 0.735 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | 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 | 1304 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 40.75 | | std | 34.94 | | cv | 0.857 | | sampleLengths | | 0 | 10 | | 1 | 94 | | 2 | 63 | | 3 | 19 | | 4 | 11 | | 5 | 13 | | 6 | 74 | | 7 | 41 | | 8 | 4 | | 9 | 33 | | 10 | 7 | | 11 | 53 | | 12 | 111 | | 13 | 44 | | 14 | 17 | | 15 | 43 | | 16 | 10 | | 17 | 10 | | 18 | 15 | | 19 | 140 | | 20 | 3 | | 21 | 26 | | 22 | 68 | | 23 | 28 | | 24 | 31 | | 25 | 112 | | 26 | 71 | | 27 | 58 | | 28 | 23 | | 29 | 25 | | 30 | 3 | | 31 | 44 |
| |
| 87.72% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 60 | | matches | | 0 | "been sealed" | | 1 | "was buttoned" | | 2 | "been placed" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 138 | | matches | | 0 | "was building" | | 1 | "was watching" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 1 | | flaggedSentences | 9 | | totalSentences | 82 | | ratio | 0.11 | | matches | | 0 | "Eighteen years on the job had taught her that murder scenes gave off a texture — a weight in the air." | | 1 | "Freckles, round glasses, a tail of red hair twisted around one finger and tucked behind her left ear in what Quinn recognized — from a hundred witnesses' worth of tells — as anxiety rather than guilt." | | 2 | "A clean nick on his jaw suggested a recent shave, which meant he'd groomed for something — a meeting, perhaps." | | 3 | "But it had been placed on his chest after death; lividity hadn't formed beneath it." | | 4 | "She checked the watch — an expensive mechanical piece, still ticking, stopped nowhere in particular because mechanical watches don't stop when their owners do." | | 5 | "The dead man had no visible wounds — she'd noted that immediately — and no wound meant no blood, and no blood meant the cause of death was something quiet." | | 6 | "One set of tracks led in — small shoes, she noted, or careful feet — but none led out along the same path." | | 7 | "Kowalski hesitated, and Quinn watched the tell — the hair tucked behind the ear — repeat itself twice in ten seconds." | | 8 | "Quinn looked down at the compass, at the sigils etched into the brass, and her partner's face — the partner she'd lost to a case that had closed itself like a wound sealing over — rose unbidden." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 595 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.02689075630252101 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.008403361344537815 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 15.9 | | std | 11.74 | | cv | 0.738 | | sampleLengths | | 0 | 10 | | 1 | 34 | | 2 | 21 | | 3 | 11 | | 4 | 28 | | 5 | 21 | | 6 | 11 | | 7 | 31 | | 8 | 14 | | 9 | 5 | | 10 | 6 | | 11 | 5 | | 12 | 13 | | 13 | 38 | | 14 | 36 | | 15 | 12 | | 16 | 29 | | 17 | 4 | | 18 | 24 | | 19 | 9 | | 20 | 7 | | 21 | 17 | | 22 | 36 | | 23 | 22 | | 24 | 7 | | 25 | 4 | | 26 | 20 | | 27 | 22 | | 28 | 4 | | 29 | 15 | | 30 | 17 | | 31 | 24 | | 32 | 10 | | 33 | 8 | | 34 | 2 | | 35 | 12 | | 36 | 5 | | 37 | 14 | | 38 | 26 | | 39 | 3 | | 40 | 10 | | 41 | 10 | | 42 | 8 | | 43 | 2 | | 44 | 5 | | 45 | 9 | | 46 | 30 | | 47 | 9 | | 48 | 6 | | 49 | 38 |
| |
| 79.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5 | | totalSentences | 82 | | uniqueOpeners | 41 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 55 | | matches | | 0 | "Just a single object resting" | | 1 | "Impossibly warm, in a cold" | | 2 | "Then she turned to Kowalski," |
| | ratio | 0.055 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 55 | | matches | | 0 | "She pushed her glasses up" | | 1 | "She nodded toward the body" | | 2 | "His shoes were tied." | | 3 | "His fingernails were clean but" | | 4 | "He'd held it recently." | | 5 | "She checked the watch —" | | 6 | "His left wrist had a" | | 7 | "She stood, her knees cracking" | | 8 | "Her voice dropped" | | 9 | "She kept her face still," | | 10 | "She reached out and, photo" | | 11 | "It was warm." | | 12 | "It spun once, twice, and" | | 13 | "She turned to Osei." |
| | ratio | 0.255 | |
| 60.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 55 | | matches | | 0 | "The dead man had picked" | | 1 | "Detective Harlow Quinn ducked under" | | 2 | "This one felt wrong in" | | 3 | "The station had been sealed" | | 4 | "The body lay at the" | | 5 | "Quinn followed the glow of" | | 6 | "Freckles, round glasses, a tail" | | 7 | "the woman said, extending a" | | 8 | "She pushed her glasses up" | | 9 | "She nodded toward the body" | | 10 | "Quinn crouched by the body," | | 11 | "The dead man's coat was" | | 12 | "His shoes were tied." | | 13 | "A clean nick on his" | | 14 | "His fingernails were clean but" | | 15 | "He'd held it recently." | | 16 | "Someone had handled the body" | | 17 | "She checked the watch —" | | 18 | "His left wrist had a" | | 19 | "The watch he wore now" |
| | ratio | 0.8 | |
| 90.91% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 55 | | matches | | 0 | "Whoever had come in had" |
| | ratio | 0.018 | |
| 44.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 4 | | matches | | 0 | "Detective Harlow Quinn ducked under the police tape and descended the rusted service stairs into the abandoned Tube station beneath Camden, her torch beam cutti…" | | 1 | "The station had been sealed since the eighties, its tiled walls furred with damp, its platform edge yawning black over tracks that hadn't carried a train in dec…" | | 2 | "A clean nick on his jaw suggested a recent shave, which meant he'd groomed for something — a meeting, perhaps." | | 3 | "The corridor ended at the sealed tunnel door, its rusted handle clean and bright, as if freshly turned." |
| |
| 91.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 1 | | matches | | 0 | "She stood, her knees cracking in the cold" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 36 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |