| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.75 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.57% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1312 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "very" | | 1 | "suddenly" | | 2 | "carefully" |
| |
| 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) | |
| 77.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1312 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "shattered" | | 1 | "footfall" | | 2 | "streaming" | | 3 | "weight" | | 4 | "electric" |
| |
| 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 | 96 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 96 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 101 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 60 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 10 | | totalWords | 1318 | | ratio | 0.008 | | matches | | 0 | "Raven's Nest" | | 1 | "cardiac event" | | 2 | "administering unauthorised treatments" | | 3 | "SO" | | 4 | "RN" | | 5 | "Detective." |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1231 | | uniqueNames | 23 | | maxNameDensity | 1.22 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | High | 2 | | Street | 2 | | Tomás | 1 | | Herrera | 7 | | Kentish | 1 | | Town | 1 | | Road | 1 | | Tesco | 1 | | Express | 1 | | Hendon | 1 | | Christopher | 1 | | Quinn | 15 | | Tube | 1 | | Chalk | 1 | | Farm | 1 | | Deptford | 1 | | Tuesday | 1 | | November | 1 | | Nest | 2 | | English | 1 | | Curled | 1 | | Spanish | 1 |
| | persons | | 0 | "Tomás" | | 1 | "Herrera" | | 2 | "Christopher" | | 3 | "Quinn" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Kentish" | | 4 | "Town" | | 5 | "Road" | | 6 | "Chalk" | | 7 | "Farm" | | 8 | "Deptford" | | 9 | "November" | | 10 | "Nest" | | 11 | "English" | | 12 | "Spanish" |
| | globalScore | 0.891 | | windowScore | 0.5 | |
| 68.03% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 2 | | matches | | 0 | "Something like satisfaction settled in her c" | | 1 | "smelled like a Tube tunnel: dust, brake ir" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1318 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 101 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 33.79 | | std | 26.04 | | cv | 0.771 | | sampleLengths | | 0 | 56 | | 1 | 78 | | 2 | 15 | | 3 | 56 | | 4 | 1 | | 5 | 38 | | 6 | 30 | | 7 | 4 | | 8 | 51 | | 9 | 3 | | 10 | 49 | | 11 | 41 | | 12 | 12 | | 13 | 96 | | 14 | 9 | | 15 | 6 | | 16 | 77 | | 17 | 69 | | 18 | 6 | | 19 | 12 | | 20 | 48 | | 21 | 59 | | 22 | 4 | | 23 | 101 | | 24 | 21 | | 25 | 35 | | 26 | 23 | | 27 | 24 | | 28 | 39 | | 29 | 21 | | 30 | 8 | | 31 | 45 | | 32 | 52 | | 33 | 18 | | 34 | 39 | | 35 | 8 | | 36 | 24 | | 37 | 30 | | 38 | 10 |
| |
| 94.30% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 96 | | matches | | 0 | "been lifted" | | 1 | "been trained" | | 2 | "been floored" |
| |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 186 | | matches | | 0 | "was building" | | 1 | "was standing" | | 2 | "was laughing" | | 3 | "was singing" | | 4 | "was looking" | | 5 | "was already revising" | | 6 | "wasn't using" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 101 | | ratio | 0.059 | | matches | | 0 | "That was his mistake and she filed it away, because in that half-turn she saw his face clear under the streetlight — olive skin, water streaming off his jaw, and something around his neck catching the amber glow." | | 1 | "And there, in the corner where the wall met the terrace, a rectangle of deeper black where the paving had been lifted and set aside — a service hatch, iron, propped open at forty degrees against the brick." | | 2 | "No radio signal — she'd checked twice since Chalk Farm and got nothing but static, which was its own kind of information." | | 3 | "She got two of them: *SO*—something—*RN*." | | 4 | "Quinn's hand went to her hip and found nothing there worth finding — a warrant card, a phone with no signal, cuffs." | | 5 | "Then she laughed — a wet, delighted sound — and stepped aside, and the market opened up in front of Quinn like a throat." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 901 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.022197558268590455 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003329633740288568 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 101 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 101 | | mean | 13.05 | | std | 11.89 | | cv | 0.911 | | sampleLengths | | 0 | 21 | | 1 | 35 | | 2 | 3 | | 3 | 13 | | 4 | 33 | | 5 | 9 | | 6 | 20 | | 7 | 13 | | 8 | 2 | | 9 | 3 | | 10 | 38 | | 11 | 9 | | 12 | 2 | | 13 | 4 | | 14 | 1 | | 15 | 38 | | 16 | 5 | | 17 | 25 | | 18 | 4 | | 19 | 3 | | 20 | 9 | | 21 | 21 | | 22 | 3 | | 23 | 2 | | 24 | 13 | | 25 | 3 | | 26 | 7 | | 27 | 1 | | 28 | 3 | | 29 | 38 | | 30 | 2 | | 31 | 13 | | 32 | 11 | | 33 | 15 | | 34 | 3 | | 35 | 9 | | 36 | 14 | | 37 | 22 | | 38 | 60 | | 39 | 2 | | 40 | 1 | | 41 | 6 | | 42 | 6 | | 43 | 35 | | 44 | 8 | | 45 | 11 | | 46 | 23 | | 47 | 3 | | 48 | 15 | | 49 | 2 |
| |
| 74.26% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4752475247524752 | | totalSentences | 101 | | uniqueOpeners | 48 | |
| 81.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 82 | | matches | | 0 | "Somewhere down there a man" | | 1 | "Then she laughed — a" |
| | ratio | 0.024 | |
| 88.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 82 | | matches | | 0 | "He was fast." | | 1 | "He'd taken the corner off" | | 2 | "Her watch strap had gone" | | 3 | "Her lungs burned in that" | | 4 | "She shouted it into the" | | 5 | "He looked back." | | 6 | "He put his head down" | | 7 | "She allowed herself a breath." | | 8 | "She stopped dead." | | 9 | "She swept her torch across" | | 10 | "It smelled like a Tube" | | 11 | "Her partner's hands curled like" | | 12 | "She was certain of it" | | 13 | "He'd been in the Nest" | | 14 | "He carried a bag full" | | 15 | "She went down twelve of" | | 16 | "She was standing on a" | | 17 | "She got two of them:" | | 18 | "They lit stalls." | | 19 | "It felt suddenly like walking" |
| | ratio | 0.329 | |
| 94.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 82 | | matches | | 0 | "Rain came down in sheets" | | 1 | "Quinn ran through it with" | | 2 | "He was fast." | | 3 | "He'd taken the corner off" | | 4 | "Her watch strap had gone" | | 5 | "Her lungs burned in that" | | 6 | "She shouted it into the" | | 7 | "He looked back." | | 8 | "That was his mistake and" | | 9 | "A medallion on a chain," | | 10 | "Patron saint of travellers." | | 11 | "He put his head down" | | 12 | "She allowed herself a breath." | | 13 | "Something like satisfaction settled in" | | 14 | "The alley was empty." | | 15 | "She stopped dead." | | 16 | "Water hammered the bin lids," | | 17 | "The wall at the end" | | 18 | "A drainpipe too narrow and" | | 19 | "She swept her torch across" |
| | ratio | 0.732 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 6 | | matches | | 0 | "Rain came down in sheets across Camden High Street, turning the tarmac into a black mirror that shattered under every footfall." | | 1 | "That was his mistake and she filed it away, because in that half-turn she saw his face clear under the streetlight — olive skin, water streaming off his jaw, an…" | | 2 | "No radio signal — she'd checked twice since Chalk Farm and got nothing but static, which was its own kind of information." | | 3 | "Morris had gone into a basement in Deptford on a Tuesday night in November and come out on a coroner's table with a report that said *cardiac event* and photogr…" | | 4 | "Somewhere down there a man was laughing, and a woman was singing something with too many syllables in it, and a hundred quiet voices layered into the murmur of …" | | 5 | "Tall, in a butcher's apron, holding a curved knife she wasn't using on any meat Quinn could see." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 66.67% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 12 | | tagDensity | 0.417 | | leniency | 0.833 | | rawRatio | 0.2 | | effectiveRatio | 0.167 | |