| 96.55% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 3 | | adverbTags | | 0 | "She handed back [back]" | | 1 | "She crouched again [again]" | | 2 | "She turned back [back]" |
| | dialogueSentences | 58 | | tagDensity | 0.293 | | leniency | 0.586 | | rawRatio | 0.176 | | effectiveRatio | 0.103 | |
| 96.77% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1548 | | 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) | |
| 80.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1548 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "footsteps" | | 1 | "perfect" | | 2 | "weight" | | 3 | "charm" | | 4 | "etched" | | 5 | "quivered" |
| |
| 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 | 103 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 103 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 144 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1550 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 1040 | | uniqueNames | 19 | | maxNameDensity | 0.77 | | worstName | "Batra" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Batra" | | discoveredNames | | Chalk | 2 | | Farm | 2 | | Road | 2 | | Millennium | 1 | | Nikhil | 1 | | Batra | 8 | | Odile | 1 | | Fenn | 1 | | Arabic | 1 | | Pret | 1 | | Court | 1 | | British | 1 | | Museum | 1 | | Restricted | 1 | | Collection | 1 | | Item | 1 | | Retrieval | 1 | | Authorised | 1 | | Quinn | 7 |
| | persons | | 0 | "Nikhil" | | 1 | "Batra" | | 2 | "Fenn" | | 3 | "Quinn" |
| | places | | 0 | "Chalk" | | 1 | "Farm" | | 2 | "Road" | | 3 | "Court" | | 4 | "British" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 1 | | matches | | 0 | "something like the air after lightning" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.645 | | wordCount | 1550 | | matches | | 0 | "not with the usual cardinal points but with a ring of looping symbols, angular" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 144 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 69 | | mean | 22.46 | | std | 21.53 | | cv | 0.959 | | sampleLengths | | 0 | 46 | | 1 | 13 | | 2 | 74 | | 3 | 20 | | 4 | 8 | | 5 | 3 | | 6 | 65 | | 7 | 5 | | 8 | 6 | | 9 | 17 | | 10 | 29 | | 11 | 33 | | 12 | 9 | | 13 | 3 | | 14 | 4 | | 15 | 57 | | 16 | 9 | | 17 | 25 | | 18 | 4 | | 19 | 27 | | 20 | 22 | | 21 | 12 | | 22 | 4 | | 23 | 8 | | 24 | 54 | | 25 | 4 | | 26 | 9 | | 27 | 41 | | 28 | 18 | | 29 | 4 | | 30 | 31 | | 31 | 5 | | 32 | 19 | | 33 | 36 | | 34 | 82 | | 35 | 3 | | 36 | 4 | | 37 | 53 | | 38 | 6 | | 39 | 6 | | 40 | 6 | | 41 | 53 | | 42 | 6 | | 43 | 54 | | 44 | 1 | | 45 | 2 | | 46 | 5 | | 47 | 28 | | 48 | 37 | | 49 | 59 |
| |
| 95.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 103 | | matches | | 0 | "been painted" | | 1 | "was scoured" | | 2 | "been torn" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 155 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 144 | | ratio | 0.007 | | matches | | 0 | "The body read: Restricted Collection — Item Retrieval — Authorised." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 515 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.021359223300970873 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 144 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 144 | | mean | 10.76 | | std | 8.93 | | cv | 0.83 | | sampleLengths | | 0 | 15 | | 1 | 31 | | 2 | 13 | | 3 | 3 | | 4 | 10 | | 5 | 40 | | 6 | 2 | | 7 | 11 | | 8 | 8 | | 9 | 20 | | 10 | 8 | | 11 | 3 | | 12 | 29 | | 13 | 36 | | 14 | 5 | | 15 | 6 | | 16 | 8 | | 17 | 9 | | 18 | 6 | | 19 | 23 | | 20 | 14 | | 21 | 9 | | 22 | 10 | | 23 | 9 | | 24 | 3 | | 25 | 4 | | 26 | 2 | | 27 | 4 | | 28 | 32 | | 29 | 2 | | 30 | 17 | | 31 | 9 | | 32 | 20 | | 33 | 5 | | 34 | 4 | | 35 | 10 | | 36 | 17 | | 37 | 18 | | 38 | 4 | | 39 | 12 | | 40 | 4 | | 41 | 8 | | 42 | 4 | | 43 | 5 | | 44 | 5 | | 45 | 10 | | 46 | 4 | | 47 | 8 | | 48 | 18 | | 49 | 4 |
| |
| 92.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5763888888888888 | | totalSentences | 144 | | uniqueOpeners | 83 | |
| 78.43% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 85 | | matches | | 0 | "Somewhere down the tunnel, water" | | 1 | "Too soft for brick powder." |
| | ratio | 0.024 | |
| 92.94% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 85 | | matches | | 0 | "He nodded towards the far" | | 1 | "She handed back the coffee" | | 2 | "Their footsteps rang off the" | | 3 | "Their own prints punched through" | | 4 | "She watched him look." | | 5 | "Their tracks, the" | | 6 | "She pressed a gloved fingertip" | | 7 | "She rose, knees cracking" | | 8 | "She didn't look up." | | 9 | "She pointed without touching" | | 10 | "He gestured at the platform." | | 11 | "She had noticed it on" | | 12 | "She crouched again and ran" | | 13 | "He opened his mouth." | | 14 | "She rubbed a pinch of" | | 15 | "It carried a smell she" | | 16 | "She stood and wiped her" | | 17 | "She could tell by the" | | 18 | "She turned it to the" | | 19 | "She set it down and" |
| | ratio | 0.318 | |
| 65.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 85 | | matches | | 0 | "The service hatch on Chalk" | | 1 | "Someone had since cut through" | | 2 | "Quinn counted them." | | 3 | "The twenty-third shifted under her" | | 4 | "A roundel with the station" | | 5 | "DS Nikhil Batra waited beside" | | 6 | "He nodded towards the far" | | 7 | "She handed back the coffee" | | 8 | "Batra shrugged and walked beside" | | 9 | "Their footsteps rang off the" | | 10 | "The platform floor held a" | | 11 | "Their own prints punched through" | | 12 | "Quinn stopped a metre short" | | 13 | "She watched him look." | | 14 | "Their tracks, the" | | 15 | "She pressed a gloved fingertip" | | 16 | "She rose, knees cracking" | | 17 | "She didn't look up." | | 18 | "Quinn studied the man." | | 19 | "Trousers with a knife-edge crease." |
| | ratio | 0.788 | |
| 58.82% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 85 | | matches | | 0 | "Now she walked the platform" |
| | ratio | 0.012 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 1 | | matches | | 0 | "A disc of pale material the width of a ten-pence piece, drilled through the centre and carved on one face with a spiral that tightened into a point." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 58 | | tagDensity | 0.086 | | leniency | 0.172 | | rawRatio | 0.2 | | effectiveRatio | 0.034 | |