| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 26 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 83 | | tagDensity | 0.313 | | leniency | 0.627 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 83.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1502 | | totalAiIsmAdverbs | 5 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
| | 2 | | | 3 | | | 4 | |
| | highlights | | 0 | "slightly" | | 1 | "deliberately" | | 2 | "softly" | | 3 | "really" | | 4 | "perfectly" |
| |
| 60.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 56.72% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1502 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "stomach" | | 1 | "scanning" | | 2 | "methodical" | | 3 | "calculated" | | 4 | "eyebrow" | | 5 | "silence" | | 6 | "familiar" | | 7 | "flickered" | | 8 | "weight" | | 9 | "potential" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 98 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 98 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 156 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1502 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 834 | | uniqueNames | 14 | | maxNameDensity | 0.72 | | worstName | "Silas" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Silas" | | discoveredNames | | November | 1 | | Chen | 1 | | Marcus | 5 | | Aurora | 3 | | Silas | 6 | | Scotch | 1 | | Calculated | 1 | | Raven | 1 | | Nest | 1 | | Practicality | 1 | | Evan | 2 | | Eva | 1 | | Cold | 1 | | Swallowed | 1 |
| | persons | | 0 | "Chen" | | 1 | "Marcus" | | 2 | "Aurora" | | 3 | "Silas" | | 4 | "Raven" | | 5 | "Evan" | | 6 | "Eva" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 63.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 2 | | matches | | 0 | "quite name" | | 1 | "looked like he hadn't had a proper meal i" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1502 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 156 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 81 | | mean | 18.54 | | std | 17.09 | | cv | 0.922 | | sampleLengths | | 0 | 17 | | 1 | 1 | | 2 | 12 | | 3 | 12 | | 4 | 15 | | 5 | 40 | | 6 | 20 | | 7 | 44 | | 8 | 38 | | 9 | 3 | | 10 | 1 | | 11 | 33 | | 12 | 1 | | 13 | 22 | | 14 | 2 | | 15 | 21 | | 16 | 1 | | 17 | 30 | | 18 | 6 | | 19 | 7 | | 20 | 61 | | 21 | 15 | | 22 | 17 | | 23 | 5 | | 24 | 20 | | 25 | 3 | | 26 | 12 | | 27 | 60 | | 28 | 4 | | 29 | 53 | | 30 | 1 | | 31 | 12 | | 32 | 10 | | 33 | 18 | | 34 | 6 | | 35 | 4 | | 36 | 3 | | 37 | 47 | | 38 | 5 | | 39 | 3 | | 40 | 15 | | 41 | 53 | | 42 | 2 | | 43 | 40 | | 44 | 4 | | 45 | 22 | | 46 | 15 | | 47 | 31 | | 48 | 5 | | 49 | 9 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 149 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 156 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 836 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.02631578947368421 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007177033492822967 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 156 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 156 | | mean | 9.63 | | std | 8.14 | | cv | 0.845 | | sampleLengths | | 0 | 17 | | 1 | 1 | | 2 | 9 | | 3 | 3 | | 4 | 12 | | 5 | 3 | | 6 | 12 | | 7 | 6 | | 8 | 22 | | 9 | 12 | | 10 | 20 | | 11 | 18 | | 12 | 7 | | 13 | 10 | | 14 | 9 | | 15 | 23 | | 16 | 15 | | 17 | 3 | | 18 | 1 | | 19 | 6 | | 20 | 27 | | 21 | 1 | | 22 | 8 | | 23 | 2 | | 24 | 5 | | 25 | 7 | | 26 | 2 | | 27 | 7 | | 28 | 12 | | 29 | 2 | | 30 | 1 | | 31 | 20 | | 32 | 1 | | 33 | 9 | | 34 | 6 | | 35 | 6 | | 36 | 1 | | 37 | 4 | | 38 | 12 | | 39 | 16 | | 40 | 7 | | 41 | 7 | | 42 | 15 | | 43 | 15 | | 44 | 11 | | 45 | 6 | | 46 | 5 | | 47 | 5 | | 48 | 6 | | 49 | 9 |
| |
| 80.98% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.5128205128205128 | | totalSentences | 156 | | uniqueOpeners | 80 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 31.76% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 85 | | matches | | 0 | "He poured anyway." | | 1 | "She turned her arm over," | | 2 | "He stood in the entrance," | | 3 | "Their eyes met." | | 4 | "She hadn't been Aurora to" | | 5 | "He crossed to the bar," | | 6 | "He signalled Silas with two" | | 7 | "He settled onto the stool" | | 8 | "They drank in silence." | | 9 | "He swirled his drink" | | 10 | "He set down the glass" | | 11 | "She'd been the pragmatic one," | | 12 | "He turned to face her" | | 13 | "He'd lost weight too, or" | | 14 | "He retreated without a word." | | 15 | "She laughed, the sound jagged" | | 16 | "She drained her glass" | | 17 | "He absorbed this like a" | | 18 | "His hand found hers on" | | 19 | "She pulled away." |
| | ratio | 0.471 | |
| 24.71% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 85 | | matches | | 0 | "The whiskey glass hit the" | | 1 | "Silas didn't look up from" | | 2 | "He poured anyway." | | 3 | "Aurora stared at the amber" | | 4 | "The scar on her wrist" | | 5 | "She turned her arm over," | | 6 | "The door swung open, bringing" | | 7 | "He stood in the entrance," | | 8 | "Marcus Chen, but not as" | | 9 | "This Marcus carried himself like" | | 10 | "Their eyes met." | | 11 | "The name landed like a" | | 12 | "She hadn't been Aurora to" | | 13 | "He crossed to the bar," | | 14 | "Everything about him calculated now." | | 15 | "He signalled Silas with two" | | 16 | "The old man raised an" | | 17 | "He settled onto the stool" | | 18 | "A muscle twitched in his" | | 19 | "They drank in silence." |
| | ratio | 0.871 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 28.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 4 | | matches | | 0 | "The door swung open, bringing with it a gust of November air and a figure that made her stomach drop." | | 1 | "Silas moving behind the bar with his slight limp, polishing glasses that didn't need polishing." | | 2 | "The confident barrister had fled, leaving behind the awkward boy who'd once knocked over an entire display of legal textbooks because she'd smiled at him across…" | | 3 | "She studied him properly now, the expensive suit, the perfectly knotted tie, the watch that cost more than her annual rent." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 26 | | uselessAdditionCount | 1 | | matches | | 0 | "He gestured, the maps, the shadows" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 83 | | tagDensity | 0.024 | | leniency | 0.048 | | rawRatio | 0.5 | | effectiveRatio | 0.024 | |