| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 57 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 193 | | tagDensity | 0.295 | | leniency | 0.591 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.78% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 3552 | | totalAiIsmAdverbs | 3 | | found | | 0 | | adverb | "deliberately" | | count | 1 |
| | 1 | | | 2 | |
| | highlights | | 0 | "deliberately" | | 1 | "slightly" | | 2 | "slowly" |
| |
| 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) | |
| 56.36% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 3552 | | totalAiIsms | 31 | | found | | | highlights | | 0 | "echoed" | | 1 | "gloom" | | 2 | "silence" | | 3 | "shimmered" | | 4 | "weight" | | 5 | "etched" | | 6 | "vibrated" | | 7 | "pristine" | | 8 | "etch" | | 9 | "could feel" | | 10 | "perfect" | | 11 | "pulse" | | 12 | "pulsed" | | 13 | "flickered" | | 14 | "shattered" | | 15 | "trembled" | | 16 | "echo" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 589 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 3 | | narrationSentences | 589 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 725 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 3552 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 51 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 173 | | wordCount | 2748 | | uniqueNames | 9 | | maxNameDensity | 3.42 | | worstName | "Quinn" | | maxWindowNameDensity | 7 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 94 | | Miller | 58 | | Morris | 2 | | Camden | 1 | | Three | 5 | | Like | 4 | | Two | 3 | | Waiting | 3 | | Click | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Miller" | | 2 | "Morris" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 94.13% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 179 | | glossingSentenceCount | 4 | | matches | | 0 | "felt like standing next to a large gene" | | 1 | "felt like the night Morris died" | | 2 | "appeared behind the wall" | | 3 | "sounded like two stones grinding together" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 3552 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 725 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 285 | | mean | 12.46 | | std | 13.75 | | cv | 1.103 | | sampleLengths | | 0 | 71 | | 1 | 34 | | 2 | 19 | | 3 | 34 | | 4 | 3 | | 5 | 20 | | 6 | 56 | | 7 | 24 | | 8 | 10 | | 9 | 12 | | 10 | 17 | | 11 | 64 | | 12 | 4 | | 13 | 37 | | 14 | 10 | | 15 | 4 | | 16 | 7 | | 17 | 43 | | 18 | 2 | | 19 | 9 | | 20 | 7 | | 21 | 44 | | 22 | 4 | | 23 | 18 | | 24 | 13 | | 25 | 11 | | 26 | 17 | | 27 | 44 | | 28 | 14 | | 29 | 8 | | 30 | 10 | | 31 | 4 | | 32 | 6 | | 33 | 4 | | 34 | 26 | | 35 | 4 | | 36 | 5 | | 37 | 10 | | 38 | 48 | | 39 | 4 | | 40 | 2 | | 41 | 15 | | 42 | 14 | | 43 | 8 | | 44 | 7 | | 45 | 36 | | 46 | 9 | | 47 | 3 | | 48 | 8 | | 49 | 29 |
| |
| 99.90% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 9 | | totalSentences | 589 | | matches | | 0 | "been sealed" | | 1 | "were etched" | | 2 | "was gone" | | 3 | "were gone" | | 4 | "was gone" | | 5 | "was rusted" | | 6 | "was gone" | | 7 | "was gone" | | 8 | "was gone" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 550 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 725 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2748 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 72 | | adverbRatio | 0.026200873362445413 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.005094614264919942 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 725 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 725 | | mean | 4.9 | | std | 3.16 | | cv | 0.645 | | sampleLengths | | 0 | 17 | | 1 | 11 | | 2 | 17 | | 3 | 10 | | 4 | 1 | | 5 | 15 | | 6 | 23 | | 7 | 11 | | 8 | 19 | | 9 | 10 | | 10 | 16 | | 11 | 3 | | 12 | 5 | | 13 | 3 | | 14 | 20 | | 15 | 2 | | 16 | 6 | | 17 | 9 | | 18 | 19 | | 19 | 9 | | 20 | 11 | | 21 | 8 | | 22 | 7 | | 23 | 9 | | 24 | 4 | | 25 | 6 | | 26 | 12 | | 27 | 17 | | 28 | 9 | | 29 | 11 | | 30 | 3 | | 31 | 12 | | 32 | 11 | | 33 | 18 | | 34 | 4 | | 35 | 9 | | 36 | 10 | | 37 | 18 | | 38 | 10 | | 39 | 4 | | 40 | 7 | | 41 | 6 | | 42 | 9 | | 43 | 4 | | 44 | 10 | | 45 | 14 | | 46 | 2 | | 47 | 3 | | 48 | 6 | | 49 | 7 |
| |
| 37.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 93 | | diversityRatio | 0.26629680998613037 | | totalSentences | 721 | | uniqueOpeners | 192 | |
| 91.53% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 12 | | totalSentences | 437 | | matches | | 0 | "Just the compass." | | 1 | "Just an outline of ice" | | 2 | "Too many joints." | | 3 | "Only more violet light." | | 4 | "Only the grey powder remained" | | 5 | "Then it stayed still." | | 6 | "Away from north." | | 7 | "Too low for a bridge." | | 8 | "Too solid for a cloud." | | 9 | "Just the night sky." | | 10 | "Just the hum of the" | | 11 | "Only the compass remained." |
| | ratio | 0.027 | |
| 83.62% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 149 | | totalSentences | 437 | | matches | | 0 | "Her boots struck the concrete" | | 1 | "She checked the worn leather" | | 2 | "He turned as Quinn approached," | | 3 | "Her knees cracked in the" | | 4 | "She ran a gloved hand" | | 5 | "She rubbed the substance between" | | 6 | "It shimmered with a faint" | | 7 | "She pointed to the ladder" | | 8 | "She knelt again." | | 9 | "She slipped the compass inside" | | 10 | "She stopped and listened." | | 11 | "It felt like standing next" | | 12 | "He frowned and rubbed his" | | 13 | "Her sharp jaw tightened." | | 14 | "She pushed the memory down." | | 15 | "She inspected the man's pockets." | | 16 | "She looked at the wall" | | 17 | "He wrinkled his nose and" | | 18 | "It wasn't pointing down the" | | 19 | "It pointed at the wall" |
| | ratio | 0.341 | |
| 26.36% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 379 | | totalSentences | 437 | | matches | | 0 | "Harlow Quinn ducked under the" | | 1 | "The air down here tasted" | | 2 | "Her boots struck the concrete" | | 3 | "She checked the worn leather" | | 4 | "The station had been sealed" | | 5 | "DS Miller stood near the" | | 6 | "He turned as Quinn approached," | | 7 | "Quinn stopped beside him and" | | 8 | "A man in his thirties," | | 9 | "Her knees cracked in the" | | 10 | "She ran a gloved hand" | | 11 | "The fabric of his jacket" | | 12 | "She rubbed the substance between" | | 13 | "It shimmered with a faint" | | 14 | "She pointed to the ladder" | | 15 | "Miller shifted his weight." | | 16 | "The gravel crunched under his" | | 17 | "Quinn stood and swept her" | | 18 | "The light caught something metallic" | | 19 | "She knelt again." |
| | ratio | 0.867 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 437 | | matches | (empty) | | ratio | 0 | |
| 89.29% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 3 | | matches | | 0 | "The fabric of his jacket felt stiff, coated in a fine grey powder that didn't match the station dust." | | 1 | "The casing bore a patina of verdigris that looked centuries old." | | 2 | "The lines intersected at angles that made her head ache." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 57 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 98.19% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 56 | | fancyCount | 10 | | fancyTags | | 0 | "Miller suggested (suggest)" | | 1 | "Quinn ordered (order)" | | 2 | "Miller whispered (whisper)" | | 3 | "Quinn confirmed (confirm)" | | 4 | "Quinn corrected (correct)" | | 5 | "Miller shouted (shout)" | | 6 | "Quinn ordered (order)" | | 7 | "Miller whispered (whisper)" | | 8 | "Miller confirmed (confirm)" | | 9 | "Quinn corrected (correct)" |
| | dialogueSentences | 193 | | tagDensity | 0.29 | | leniency | 0.58 | | rawRatio | 0.179 | | effectiveRatio | 0.104 | |