| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.407 | | leniency | 0.815 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1154 | | totalAiIsmAdverbs | 3 | | found | | 0 | | adverb | "deliberately" | | count | 1 |
| | 1 | | | 2 | |
| | highlights | | 0 | "deliberately" | | 1 | "slowly" | | 2 | "slightly" |
| |
| 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) | |
| 65.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1154 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "traced" | | 1 | "shattered" | | 2 | "echoed" | | 3 | "standard" | | 4 | "etched" | | 5 | "crystal" | | 6 | "familiar" | | 7 | "silence" |
| |
| 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 | 111 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 111 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 127 | | 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 | 1154 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 58.20% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 817 | | uniqueNames | 14 | | maxNameDensity | 1.84 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 15 | | London | 1 | | Underground | 1 | | Featherstone | 10 | | Water | 1 | | Ellman | 5 | | Camden | 1 | | Warren | 2 | | Street | 2 | | Tottenham | 1 | | Court | 1 | | Road | 1 | | Veil | 1 | | One | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Underground" | | 2 | "Featherstone" | | 3 | "Water" | | 4 | "Ellman" |
| | places | | 0 | "London" | | 1 | "Warren" | | 2 | "Street" | | 3 | "Tottenham" | | 4 | "Court" | | 5 | "Road" | | 6 | "One" |
| | globalScore | 0.582 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 1 | | matches | | 0 | "as if holding something she couldn't see" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1154 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 127 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 32.97 | | std | 18.27 | | cv | 0.554 | | sampleLengths | | 0 | 57 | | 1 | 18 | | 2 | 65 | | 3 | 36 | | 4 | 44 | | 5 | 3 | | 6 | 42 | | 7 | 20 | | 8 | 20 | | 9 | 65 | | 10 | 18 | | 11 | 63 | | 12 | 38 | | 13 | 61 | | 14 | 50 | | 15 | 20 | | 16 | 56 | | 17 | 30 | | 18 | 15 | | 19 | 46 | | 20 | 27 | | 21 | 24 | | 22 | 19 | | 23 | 26 | | 24 | 60 | | 25 | 29 | | 26 | 47 | | 27 | 35 | | 28 | 13 | | 29 | 1 | | 30 | 35 | | 31 | 24 | | 32 | 21 | | 33 | 23 | | 34 | 3 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 111 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 148 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 127 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 821 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.037758830694275276 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0060901339829476245 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 127 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 127 | | mean | 9.09 | | std | 6.89 | | cv | 0.758 | | sampleLengths | | 0 | 20 | | 1 | 26 | | 2 | 11 | | 3 | 14 | | 4 | 4 | | 5 | 22 | | 6 | 18 | | 7 | 2 | | 8 | 2 | | 9 | 1 | | 10 | 20 | | 11 | 18 | | 12 | 4 | | 13 | 14 | | 14 | 7 | | 15 | 4 | | 16 | 6 | | 17 | 9 | | 18 | 8 | | 19 | 5 | | 20 | 5 | | 21 | 3 | | 22 | 8 | | 23 | 2 | | 24 | 6 | | 25 | 2 | | 26 | 4 | | 27 | 20 | | 28 | 9 | | 29 | 5 | | 30 | 5 | | 31 | 1 | | 32 | 20 | | 33 | 13 | | 34 | 20 | | 35 | 5 | | 36 | 10 | | 37 | 8 | | 38 | 9 | | 39 | 15 | | 40 | 3 | | 41 | 12 | | 42 | 7 | | 43 | 3 | | 44 | 4 | | 45 | 18 | | 46 | 6 | | 47 | 13 | | 48 | 4 | | 49 | 34 |
| |
| 79.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4881889763779528 | | totalSentences | 127 | | uniqueOpeners | 62 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 92 | | matches | | 0 | "Too round for a cigarette." | | 1 | "Too clean for an accident." | | 2 | "Then a single word, distorted." |
| | ratio | 0.033 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 92 | | matches | | 0 | "She advanced past the cordon" | | 1 | "She stopped beside the edge" | | 2 | "His boots scuffed closer." | | 3 | "She traced the edge with" | | 4 | "She thumbed the home button" | | 5 | "She moved along the body" | | 6 | "She bent, lifted it with" | | 7 | "She clicked it shut and" | | 8 | "She tapped a clean square" | | 9 | "She swept the torch across" | | 10 | "She ignored it for the" | | 11 | "She tugged it free." | | 12 | "She pocketed the token." | | 13 | "She crossed back to Ellman." | | 14 | "His eyes stared at nothing." | | 15 | "She closed the other with" | | 16 | "she told Featherstone" | | 17 | "He nodded, already turning away" | | 18 | "She drew it out and" | | 19 | "She reached for her radio." |
| | ratio | 0.261 | |
| 41.52% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 92 | | matches | | 0 | "The rotten reek of something" | | 1 | "She advanced past the cordon" | | 2 | "Bones crunched somewhere to her" | | 3 | "Featherstone's voice caught up with" | | 4 | "She stopped beside the edge" | | 5 | "The body lay half-sprawled across" | | 6 | "Entry wound neat enough to" | | 7 | "His boots scuffed closer." | | 8 | "Quinn lifted the dead man's" | | 9 | "Calluses on the fingertips." | | 10 | "She traced the edge with" | | 11 | "Featherstone handed it over in" | | 12 | "She thumbed the home button" | | 13 | "Quinn stood, torch beam climbing" | | 14 | "Water seeped in steady drips." | | 15 | "Every sound echoed too far." | | 16 | "She moved along the body" | | 17 | "A single shoe print near" | | 18 | "Quinn shifted the torch lower." | | 19 | "Someone had moved something heavy" |
| | ratio | 0.837 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 92 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "Featherstone's voice caught up, lantern swinging from one careful hand" |
| |
| 75.93% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "he added (add)" | | 1 | "Featherstone continued (continue)" |
| | dialogueSentences | 27 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0.333 | | effectiveRatio | 0.148 | |