| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 1 | | adverbTags | | 0 | "She turned back [back]" |
| | dialogueSentences | 60 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0.1 | | effectiveRatio | 0.033 | |
| 96.70% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1514 | | 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) | |
| 20.74% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1514 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "scanning" | | 1 | "measured" | | 2 | "traced" | | 3 | "footsteps" | | 4 | "echoed" | | 5 | "flicked" | | 6 | "etched" | | 7 | "shattered" | | 8 | "quivered" | | 9 | "etching" | | 10 | "pulsed" | | 11 | "echoing" | | 12 | "flickered" | | 13 | "silence" | | 14 | "jaw clenched" | | 15 | "pulse" | | 16 | "whisper" | | 17 | "charged" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "eyes widened" | | 1 | "jaw clenched" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 171 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 171 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 219 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1505 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 83 | | wordCount | 1084 | | uniqueNames | 11 | | maxNameDensity | 3.04 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Jacobs | 24 | | Footsteps | 2 | | Veil | 1 | | Compass | 1 | | Camden | 1 | | Kowalski | 1 | | Quinn | 33 | | Othala | 1 | | Morris | 1 | | Eva | 15 | | Dust | 3 |
| | persons | | 0 | "Jacobs" | | 1 | "Footsteps" | | 2 | "Compass" | | 3 | "Kowalski" | | 4 | "Quinn" | | 5 | "Othala" | | 6 | "Morris" | | 7 | "Eva" | | 8 | "Dust" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 84 | | 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 | 1505 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 219 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 83 | | mean | 18.13 | | std | 10.78 | | cv | 0.594 | | sampleLengths | | 0 | 29 | | 1 | 8 | | 2 | 29 | | 3 | 23 | | 4 | 23 | | 5 | 23 | | 6 | 8 | | 7 | 6 | | 8 | 22 | | 9 | 29 | | 10 | 8 | | 11 | 22 | | 12 | 6 | | 13 | 22 | | 14 | 21 | | 15 | 31 | | 16 | 8 | | 17 | 27 | | 18 | 40 | | 19 | 8 | | 20 | 19 | | 21 | 5 | | 22 | 14 | | 23 | 41 | | 24 | 10 | | 25 | 43 | | 26 | 19 | | 27 | 37 | | 28 | 10 | | 29 | 11 | | 30 | 14 | | 31 | 4 | | 32 | 32 | | 33 | 24 | | 34 | 8 | | 35 | 21 | | 36 | 6 | | 37 | 17 | | 38 | 35 | | 39 | 10 | | 40 | 20 | | 41 | 26 | | 42 | 8 | | 43 | 19 | | 44 | 17 | | 45 | 5 | | 46 | 29 | | 47 | 19 | | 48 | 12 | | 49 | 12 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 171 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 221 | | matches | (empty) | |
| 90.67% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 219 | | ratio | 0.018 | | matches | | 0 | "From her satchel she withdrew the Veil Compass—a small brass instrument etched with protective sigils." | | 1 | "A low hum pulsed through the tunnel—like the rumble of millions of hooves." | | 2 | "Shadows receded, then reformed into silhouettes—three figures wearing hooded cloaks." | | 3 | "Quinn closed her eyes for a beat, centred her aim—and then charged after them." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1091 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.02016498625114574 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.00458295142071494 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 219 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 219 | | mean | 6.87 | | std | 4.75 | | cv | 0.691 | | sampleLengths | | 0 | 9 | | 1 | 10 | | 2 | 10 | | 3 | 8 | | 4 | 13 | | 5 | 16 | | 6 | 11 | | 7 | 12 | | 8 | 4 | | 9 | 19 | | 10 | 7 | | 11 | 12 | | 12 | 2 | | 13 | 2 | | 14 | 4 | | 15 | 4 | | 16 | 3 | | 17 | 3 | | 18 | 8 | | 19 | 14 | | 20 | 13 | | 21 | 4 | | 22 | 4 | | 23 | 5 | | 24 | 3 | | 25 | 8 | | 26 | 6 | | 27 | 7 | | 28 | 6 | | 29 | 3 | | 30 | 2 | | 31 | 4 | | 32 | 4 | | 33 | 9 | | 34 | 9 | | 35 | 2 | | 36 | 14 | | 37 | 5 | | 38 | 2 | | 39 | 15 | | 40 | 6 | | 41 | 8 | | 42 | 4 | | 43 | 4 | | 44 | 9 | | 45 | 6 | | 46 | 2 | | 47 | 7 | | 48 | 3 | | 49 | 3 |
| |
| 54.19% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.3333333333333333 | | totalSentences | 219 | | uniqueOpeners | 73 | |
| 68.49% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 146 | | matches | | 0 | "Exactly five centimetres across." | | 1 | "Then traced the lines." | | 2 | "Then the sound of steel" |
| | ratio | 0.021 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 146 | | matches | | 0 | "She crouched low, eyes scanning" | | 1 | "She stood, brushing dust from" | | 2 | "He frowned, gloved hand hovering" | | 3 | "She unfurled a small ruler" | | 4 | "She turned back to the" | | 5 | "He lowered his shoulder-length build" | | 6 | "Its patina glinted under her" | | 7 | "She ignored him and held" | | 8 | "She pulled a leather-bound notebook" | | 9 | "She tapped the sketch" | | 10 | "She traced a line with" | | 11 | "He studied her." | | 12 | "She wiped a smear of" | | 13 | "It pointed toward a bricked-up" | | 14 | "It fell away with a" | | 15 | "She shone its face onto" | | 16 | "She crouched to examine the" | | 17 | "She picked one up." | | 18 | "It had etching." | | 19 | "She thought of DS Morris." |
| | ratio | 0.205 | |
| 35.34% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 124 | | totalSentences | 146 | | matches | | 0 | "Quinn pressed a gloved finger" | | 1 | "The blood had begun to" | | 2 | "She crouched low, eyes scanning" | | 3 | "DC Jacobs stepped closer, the" | | 4 | "Quinn’s nostrils flared as the" | | 5 | "Jacobs cleared his throat." | | 6 | "She stood, brushing dust from" | | 7 | "Blood crusted beneath the victim’s" | | 8 | "Jacobs studied the mark." | | 9 | "Quinn’s gaze sharpened." | | 10 | "He frowned, gloved hand hovering" | | 11 | "She unfurled a small ruler" | | 12 | "A reversed rune, she realised." | | 13 | "Footsteps echoed from the platform" | | 14 | "Quinn flicked her torch toward" | | 15 | "A shadow receded around a" | | 16 | "Quinn raised a hand." | | 17 | "She turned back to the" | | 18 | "He lowered his shoulder-length build" | | 19 | "Its patina glinted under her" |
| | ratio | 0.849 | |
| 34.25% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 146 | | matches | | 0 | "Now distinct words, guttural and" |
| | ratio | 0.007 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 1 | | matches | | 0 | "Quinn recognised the victim’s uniform: a security guard who reported strange noises down here last week." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 83.33% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 4 | | fancyTags | | 0 | "she murmured (murmur)" | | 1 | "Eva whispered (whisper)" | | 2 | "Quinn whispered (whisper)" | | 3 | "She murmured (murmur)" |
| | dialogueSentences | 60 | | tagDensity | 0.1 | | leniency | 0.2 | | rawRatio | 0.667 | | effectiveRatio | 0.133 | |