| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 31 | | adverbTagCount | 3 | | adverbTags | | 0 | "Quinn circled again [again]" | | 1 | "More shuffling [More]" | | 2 | "She walked around [around]" |
| | dialogueSentences | 79 | | tagDensity | 0.392 | | leniency | 0.785 | | rawRatio | 0.097 | | effectiveRatio | 0.076 | |
| 93.34% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1501 | | totalAiIsmAdverbs | 2 | | 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) | |
| 70.02% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1501 | | totalAiIsms | 9 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | word | "the last thing" | | count | 1 |
| | 8 | |
| | highlights | | 0 | "sense of" | | 1 | "determined" | | 2 | "flickered" | | 3 | "traced" | | 4 | "tracing" | | 5 | "silence" | | 6 | "weight" | | 7 | "the last thing" | | 8 | "footsteps" |
| |
| 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 | 120 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 120 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 165 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1494 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 928 | | uniqueNames | 14 | | maxNameDensity | 1.51 | | worstName | "Miller" | | maxWindowNameDensity | 3 | | worstWindowName | "Miller" | | discoveredNames | | Tottenham | 1 | | Court | 1 | | Road | 1 | | Miller | 14 | | Harlow | 2 | | Quinn | 10 | | Cold | 1 | | Morris | 3 | | British | 1 | | Museum | 1 | | Three | 1 | | Eva | 1 | | Solid | 1 | | Tube | 1 |
| | persons | | 0 | "Miller" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Morris" | | 4 | "Museum" | | 5 | "Eva" |
| | places | | 0 | "Tottenham" | | 1 | "Court" | | 2 | "Road" | | 3 | "British" | | 4 | "Three" |
| | globalScore | 0.746 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1494 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 165 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 79 | | mean | 18.91 | | std | 15.03 | | cv | 0.795 | | sampleLengths | | 0 | 23 | | 1 | 15 | | 2 | 30 | | 3 | 15 | | 4 | 40 | | 5 | 12 | | 6 | 47 | | 7 | 6 | | 8 | 3 | | 9 | 33 | | 10 | 11 | | 11 | 42 | | 12 | 3 | | 13 | 7 | | 14 | 36 | | 15 | 6 | | 16 | 30 | | 17 | 15 | | 18 | 41 | | 19 | 22 | | 20 | 34 | | 21 | 10 | | 22 | 6 | | 23 | 40 | | 24 | 19 | | 25 | 8 | | 26 | 4 | | 27 | 2 | | 28 | 18 | | 29 | 10 | | 30 | 47 | | 31 | 7 | | 32 | 8 | | 33 | 19 | | 34 | 5 | | 35 | 26 | | 36 | 5 | | 37 | 8 | | 38 | 43 | | 39 | 6 | | 40 | 17 | | 41 | 39 | | 42 | 28 | | 43 | 20 | | 44 | 14 | | 45 | 13 | | 46 | 3 | | 47 | 41 | | 48 | 1 | | 49 | 50 |
| |
| 96.49% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 120 | | matches | | 0 | "been closed" | | 1 | "being rearranged" | | 2 | "been sealed" |
| |
| 36.40% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 163 | | matches | | 0 | "wasn't pointing" | | 1 | "was pointing" | | 2 | "was beginning" | | 3 | "was backing" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 165 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 934 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.034261241970021415 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.009635974304068522 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 165 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 165 | | mean | 9.05 | | std | 7.1 | | cv | 0.784 | | sampleLengths | | 0 | 23 | | 1 | 9 | | 2 | 6 | | 3 | 14 | | 4 | 6 | | 5 | 2 | | 6 | 8 | | 7 | 10 | | 8 | 5 | | 9 | 15 | | 10 | 1 | | 11 | 2 | | 12 | 22 | | 13 | 6 | | 14 | 6 | | 15 | 13 | | 16 | 2 | | 17 | 1 | | 18 | 12 | | 19 | 3 | | 20 | 11 | | 21 | 4 | | 22 | 1 | | 23 | 6 | | 24 | 3 | | 25 | 8 | | 26 | 25 | | 27 | 3 | | 28 | 8 | | 29 | 19 | | 30 | 23 | | 31 | 3 | | 32 | 7 | | 33 | 9 | | 34 | 4 | | 35 | 23 | | 36 | 5 | | 37 | 1 | | 38 | 16 | | 39 | 14 | | 40 | 6 | | 41 | 9 | | 42 | 17 | | 43 | 2 | | 44 | 2 | | 45 | 13 | | 46 | 7 | | 47 | 11 | | 48 | 11 | | 49 | 29 |
| |
| 79.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.5212121212121212 | | totalSentences | 165 | | uniqueOpeners | 86 | |
| 75.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 88 | | matches | | 0 | "Just enough to dislodge a" | | 1 | "Faintly at first, then brighter," |
| | ratio | 0.023 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 88 | | matches | | 0 | "She stood, knees protesting, and" | | 1 | "She tilted her head" | | 2 | "She approached the body, close" | | 3 | "She stepped closer." | | 4 | "It pointed toward the wall" | | 5 | "She turned her attention to" | | 6 | "She pulled out her phone" | | 7 | "She'd sent the photos" | | 8 | "She'd dismissed his theories as" | | 9 | "She pointed to the fingers," | | 10 | "She walked around the body" | | 11 | "She looked at the brickwork" | | 12 | "She ignored him, crossing to" | | 13 | "It cared about something else" | | 14 | "She pressed her palm flat" | | 15 | "It was pointing directly at" | | 16 | "His journal, never recovered, had" | | 17 | "She pulled a small plastic" | | 18 | "Her eyes were on the" |
| | ratio | 0.216 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 88 | | matches | | 0 | "The body hung upside down" | | 1 | "DC Miller ducked under the" | | 2 | "Harlow Quinn crouched near the" | | 3 | "Ground bone, if the copper" | | 4 | "Miller peered up at the" | | 5 | "Quinn touched the powdery residue" | | 6 | "She stood, knees protesting, and" | | 7 | "The metal links simply..." | | 8 | "She tilted her head" | | 9 | "Miller squinted upward." | | 10 | "Quinn circled again" | | 11 | "She approached the body, close" | | 12 | "Copper and something else." | | 13 | "Something that reminded her of" | | 14 | "The memory flickered and died." | | 15 | "Miller made a note" | | 16 | "Quinn examined the chains attached" | | 17 | "The metal emerged from the" | | 18 | "Miller consulted his phone" | | 19 | "Quinn traced the chain with" |
| | ratio | 0.705 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 5 | | matches | | 0 | "Something that reminded her of Morris, three years ago, standing in a room just like this one, staring at symbols he didn't understand." | | 1 | "Something about the object pulled at her, the same way certain cases pulled, the ones that didn't make sense on paper but kept her awake at three in the morning…" | | 2 | "In a sealed underground station that had been closed for six years, the bricks were warm." | | 3 | "Faintly at first, then brighter, casting an amber light that had no business existing in an abandoned Tube station at half past midnight." | | 4 | "And from somewhere beyond it, Harlow Quinn heard the last thing she expected to hear in an abandoned station that had been sealed for six years." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 31 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 2 | | fancyTags | | 0 | "Miller warned (warn)" | | 1 | "She pressed (press)" |
| | dialogueSentences | 79 | | tagDensity | 0.089 | | leniency | 0.177 | | rawRatio | 0.286 | | effectiveRatio | 0.051 | |