| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 53 | | tagDensity | 0.396 | | leniency | 0.792 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.97% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1242 | | 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) | |
| 83.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1242 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "traced" | | 1 | "etched" | | 2 | "magnetic" | | 3 | "footsteps" |
| |
| 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 | 61 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 61 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 93 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 61 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1245 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 48.55% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 690 | | uniqueNames | 9 | | maxNameDensity | 2.03 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 14 | | Camden | 1 | | High | 1 | | Street | 1 | | Pike | 9 | | Ashcombe | 1 | | Grey | 1 | | Footsteps | 1 | | Eva | 2 |
| | persons | | 0 | "Quinn" | | 1 | "Pike" | | 2 | "Footsteps" | | 3 | "Eva" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Ashcombe" |
| | globalScore | 0.486 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 31 | | 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 | 1245 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 93 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 23.94 | | std | 21.34 | | cv | 0.891 | | sampleLengths | | 0 | 25 | | 1 | 44 | | 2 | 21 | | 3 | 24 | | 4 | 27 | | 5 | 50 | | 6 | 1 | | 7 | 62 | | 8 | 24 | | 9 | 1 | | 10 | 44 | | 11 | 9 | | 12 | 93 | | 13 | 7 | | 14 | 27 | | 15 | 19 | | 16 | 22 | | 17 | 13 | | 18 | 7 | | 19 | 23 | | 20 | 10 | | 21 | 8 | | 22 | 7 | | 23 | 50 | | 24 | 34 | | 25 | 5 | | 26 | 95 | | 27 | 9 | | 28 | 35 | | 29 | 55 | | 30 | 28 | | 31 | 20 | | 32 | 3 | | 33 | 3 | | 34 | 6 | | 35 | 24 | | 36 | 21 | | 37 | 10 | | 38 | 51 | | 39 | 15 | | 40 | 1 | | 41 | 28 | | 42 | 5 | | 43 | 5 | | 44 | 37 | | 45 | 1 | | 46 | 5 | | 47 | 41 | | 48 | 44 | | 49 | 5 |
| |
| 93.76% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 61 | | matches | | 0 | "was rucked" | | 1 | "been made" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 123 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 93 | | ratio | 0.011 | | matches | | 0 | "Cold, and stiffening, and they gave up their contents in pieces: a small brass compass, the casing furred with verdigris, its face crowded with tiny etched figures — spirals, eyes, a ring of marks that were not letters in any alphabet she'd been made to learn." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 478 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.02510460251046025 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 93 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 93 | | mean | 13.39 | | std | 12.39 | | cv | 0.926 | | sampleLengths | | 0 | 25 | | 1 | 17 | | 2 | 15 | | 3 | 12 | | 4 | 11 | | 5 | 10 | | 6 | 24 | | 7 | 27 | | 8 | 23 | | 9 | 9 | | 10 | 18 | | 11 | 1 | | 12 | 38 | | 13 | 24 | | 14 | 16 | | 15 | 8 | | 16 | 1 | | 17 | 23 | | 18 | 18 | | 19 | 3 | | 20 | 2 | | 21 | 3 | | 22 | 4 | | 23 | 32 | | 24 | 61 | | 25 | 7 | | 26 | 27 | | 27 | 5 | | 28 | 14 | | 29 | 8 | | 30 | 14 | | 31 | 4 | | 32 | 3 | | 33 | 6 | | 34 | 7 | | 35 | 19 | | 36 | 4 | | 37 | 10 | | 38 | 8 | | 39 | 5 | | 40 | 2 | | 41 | 35 | | 42 | 15 | | 43 | 1 | | 44 | 33 | | 45 | 5 | | 46 | 14 | | 47 | 51 | | 48 | 30 | | 49 | 9 |
| |
| 97.85% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.6559139784946236 | | totalSentences | 93 | | uniqueOpeners | 61 | |
| 64.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 52 | | matches | | 0 | "Somewhere above, Camden High Street" |
| | ratio | 0.019 | |
| 58.46% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 52 | | matches | | 0 | "She came down the spiral" | | 1 | "She swung the torch low" | | 2 | "His mouth moved." | | 3 | "She pointed the torch down" | | 4 | "She held the torch out" | | 5 | "He looked at her." | | 6 | "He got down." | | 7 | "She watched his shoulders go" | | 8 | "She crossed to the body" | | 9 | "She lifted the hem of" | | 10 | "She nodded down the platform" | | 11 | "Her torch had caught something" | | 12 | "She worked the fingers open." | | 13 | "It ignored her." | | 14 | "It ignored the tunnel, the" | | 15 | "She turned it again." | | 16 | "She stood, and the needle" | | 17 | "She stopped four steps up," | | 18 | "She tucked a curl behind" | | 19 | "She looked at the satchel" |
| | ratio | 0.404 | |
| 27.31% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 52 | | matches | | 0 | "The stairwell smelled of iron" | | 1 | "She came down the spiral" | | 2 | "DC Pike called up" | | 3 | "Quinn stopped six steps short" | | 4 | "The body lay on the" | | 5 | "Blood had pooled and then" | | 6 | "Pike thumbed his notebook" | | 7 | "Quinn came down the last" | | 8 | "She swung the torch low" | | 9 | "The beam raked the floor" | | 10 | "His mouth moved." | | 11 | "Quinn traced the air above" | | 12 | "She pointed the torch down" | | 13 | "Pike stood, brushing his knees." | | 14 | "She held the torch out" | | 15 | "He looked at her." | | 16 | "He got down." | | 17 | "She watched his shoulders go" | | 18 | "Quinn took the torch back" | | 19 | "She crossed to the body" |
| | ratio | 0.865 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 18 | | technicalSentenceCount | 2 | | matches | | 0 | "Cold, and stiffening, and they gave up their contents in pieces: a small brass compass, the casing furred with verdigris, its face crowded with tiny etched figu…" | | 1 | "The woman who came down was small and red-haired and wearing entirely the wrong shoes, and she had a leather satchel clamped under one arm with the strap wrappe…" |
| |
| 77.38% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 2 | | matches | | 0 | "She pointed, an advert ghost still legible on it: DRINK MAZAWATTEE" | | 1 | "She stood, and the needle stayed with the wall like a dog watching a door" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 53 | | tagDensity | 0.094 | | leniency | 0.189 | | rawRatio | 0 | | effectiveRatio | 0 | |