| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1564 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 80.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1564 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "footsteps" | | 1 | "weight" | | 2 | "mechanical" | | 3 | "loomed" | | 4 | "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 | 122 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 122 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 122 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1582 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1580 | | uniqueNames | 17 | | maxNameDensity | 0.95 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 2 | | Quinn | 15 | | Raven | 2 | | Nest | 2 | | Wednesdays | 1 | | Herrera | 10 | | Google | 1 | | Dean | 1 | | Street | 1 | | Fitzrovia | 1 | | Underground | 1 | | Art | 1 | | Deco | 1 | | Morris | 3 | | Tomás | 3 | | Tube | 1 | | Met | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Herrera" | | 4 | "Art" | | 5 | "Deco" | | 6 | "Morris" | | 7 | "Tomás" | | 8 | "Met" |
| | places | | 0 | "Soho" | | 1 | "Google" | | 2 | "Dean" | | 3 | "Street" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 85.90% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 2 | | matches | | 0 | "quite make out" | | 1 | "sounded like Morris telling her to wait, t" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1582 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 122 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 49.44 | | std | 34.54 | | cv | 0.699 | | sampleLengths | | 0 | 86 | | 1 | 57 | | 2 | 7 | | 3 | 77 | | 4 | 51 | | 5 | 6 | | 6 | 73 | | 7 | 44 | | 8 | 50 | | 9 | 5 | | 10 | 107 | | 11 | 3 | | 12 | 76 | | 13 | 72 | | 14 | 8 | | 15 | 47 | | 16 | 10 | | 17 | 87 | | 18 | 35 | | 19 | 145 | | 20 | 46 | | 21 | 54 | | 22 | 79 | | 23 | 25 | | 24 | 101 | | 25 | 4 | | 26 | 47 | | 27 | 6 | | 28 | 44 | | 29 | 36 | | 30 | 66 | | 31 | 28 |
| |
| 93.76% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 122 | | matches | | 0 | "been closed" | | 1 | "been taught" | | 2 | "been issued" | | 3 | "been built" |
| |
| 71.79% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 260 | | matches | | 0 | "was going" | | 1 | "was wasting" | | 2 | "was going" | | 3 | "was building" | | 4 | "was meeting" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 0 | | flaggedSentences | 14 | | totalSentences | 122 | | ratio | 0.115 | | matches | | 0 | "She checked her watch — the worn leather band dark with moisture against her wrist — and noted the time." | | 1 | "He was average height — maybe five-ten — with a compact build visible even beneath a dark jacket." | | 2 | "She adjusted, cutting through a narrow alley she knew from a case four years ago — a body in a skip, a jealous husband, the kind of clean human ugliness she used to specialize in before everything got strange." | | 3 | "The late-night drinkers and delivery drivers and club kids with their arms around each other — all of them fell away as Herrera took routes that grew quieter, darker, more deliberate." | | 4 | "Beyond it, Quinn could see the faded tilework of an old Underground station entrance — the kind that had been closed for decades, bricked up and forgotten in the layers of the city's history." | | 5 | "In the yellow glow of a distant streetlamp, she caught a flash of pale material — bone, she thought, though she couldn't say why the word arrived so readily." | | 6 | "He pressed it to something on the fence — a panel, a reader, she couldn't tell — and the chain-link gate swung inward with a groan that the rain swallowed." | | 7 | "The gate was solid under her hand when she tested it — locked, or sealed, or simply refusing her." | | 8 | "Not merely unlit — dark in a way that suggested depth, that suggested the stairs led somewhere much further than the platform below." | | 9 | "Three years ago, she'd drawn that same weapon on something she still couldn't describe — something that had taken DS Morris in a room full of evidence that didn't make sense and wouldn't stop not making sense no matter how many times she reviewed the file." | | 10 | "And now Tomás Herrera — disgraced paramedic, associate of a group she was building a case against — had walked through a gate locked by something that wasn't a key and descended into a light that shouldn't exist beneath an abandoned Tube station in the rain." | | 11 | "She unzipped her jacket and pulled the lock pick set from her inside pocket — the one she wasn't supposed to own, the one that had saved her more times than regulation ever had." | | 12 | "The old station entrance loomed above her, its tilework releasing the smell of damp earth and something else — something sharp and sweet that she couldn't place, like incense in a church she'd never attended." | | 13 | "The light grew warmer, closer, and the walls of the stairwell began to change — the grime and water damage giving way to carved stone, to symbols she didn't recognize, to the unmistakable sensation of entering a space that had been built with intention and secrecy and the quiet confidence of people who knew they would never be found." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1572 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.022264631043257 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.003816793893129771 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 122 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 122 | | mean | 12.97 | | std | 11.57 | | cv | 0.892 | | sampleLengths | | 0 | 16 | | 1 | 27 | | 2 | 20 | | 3 | 1 | | 4 | 22 | | 5 | 6 | | 6 | 21 | | 7 | 7 | | 8 | 9 | | 9 | 14 | | 10 | 7 | | 11 | 22 | | 12 | 18 | | 13 | 11 | | 14 | 26 | | 15 | 2 | | 16 | 2 | | 17 | 25 | | 18 | 2 | | 19 | 5 | | 20 | 15 | | 21 | 6 | | 22 | 7 | | 23 | 6 | | 24 | 5 | | 25 | 7 | | 26 | 33 | | 27 | 6 | | 28 | 9 | | 29 | 5 | | 30 | 39 | | 31 | 12 | | 32 | 4 | | 33 | 11 | | 34 | 23 | | 35 | 5 | | 36 | 6 | | 37 | 11 | | 38 | 31 | | 39 | 12 | | 40 | 15 | | 41 | 19 | | 42 | 13 | | 43 | 3 | | 44 | 11 | | 45 | 14 | | 46 | 1 | | 47 | 1 | | 48 | 34 | | 49 | 15 |
| |
| 45.56% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.35833333333333334 | | totalSentences | 120 | | uniqueOpeners | 43 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 102 | | matches | | 0 | "Then Herrera stopped." | | 1 | "Then the second." | | 2 | "Somewhere below, Tomás Herrera was" | | 3 | "Somewhere below, the answers she'd" |
| | ratio | 0.039 | |
| 70.98% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 102 | | matches | | 0 | "She checked her watch —" | | 1 | "She'd been standing here for" | | 2 | "She'd come here on a" | | 3 | "They gathered at the bar" | | 4 | "They left separately, never together," | | 5 | "He was average height —" | | 6 | "He turned up his collar" | | 7 | "She counted to five, then" | | 8 | "He knew where he was" | | 9 | "It drowned footsteps, blurred vision," | | 10 | "He turned onto Dean Street." | | 11 | "She adjusted, cutting through a" | | 12 | "He didn't look back." | | 13 | "They moved north through the" | | 14 | "He cut through a construction" | | 15 | "He crossed a junction where" | | 16 | "He stood at the mouth" | | 17 | "He pressed it to something" | | 18 | "He slipped through." | | 19 | "Her heart beat against her" |
| | ratio | 0.373 | |
| 53.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 102 | | matches | | 0 | "Harlow Quinn pressed herself into" | | 1 | "She checked her watch —" | | 2 | "She'd been standing here for" | | 3 | "She'd come here on a" | | 4 | "They gathered at the bar" | | 5 | "They left separately, never together," | | 6 | "The door opened, and a" | | 7 | "Quinn straightened, her eyes tracking" | | 8 | "He was average height —" | | 9 | "He turned up his collar" | | 10 | "Patients who couldn't be identified." | | 11 | "She counted to five, then" | | 12 | "Herrera walked with purpose but" | | 13 | "He knew where he was" | | 14 | "This wasn't a man wandering." | | 15 | "This was a man keeping" | | 16 | "Quinn matched his pace from" | | 17 | "The rain was a gift" | | 18 | "It drowned footsteps, blurred vision," | | 19 | "He turned onto Dean Street." |
| | ratio | 0.814 | |
| 98.04% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 102 | | matches | | 0 | "Whoever ran the Raven's Nest" | | 1 | "Either he was clean and" |
| | ratio | 0.02 | |
| 2.34% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 12 | | matches | | 0 | "Quinn straightened, her eyes tracking him with the precision that had earned her commendations and a reputation for being impossible to shake." | | 1 | "Quinn matched his pace from half a block back, using parked cars and awnings as cover, her shoes finding the shallow puddles instead of the deep ones out of hab…" | | 2 | "The late-night drinkers and delivery drivers and club kids with their arms around each other — all of them fell away as Herrera took routes that grew quieter, d…" | | 3 | "Beyond it, Quinn could see the faded tilework of an old Underground station entrance — the kind that had been closed for decades, bricked up and forgotten in th…" | | 4 | "She watched the gate, half-expecting it to swing open again, half-expecting Herrera to reappear with a weapon and the calm eyes of someone who'd been expecting …" | | 5 | "Not merely unlit — dark in a way that suggested depth, that suggested the stairs led somewhere much further than the platform below." | | 6 | "Three years ago, she'd drawn that same weapon on something she still couldn't describe — something that had taken DS Morris in a room full of evidence that didn…" | | 7 | "He'd been a good man who laughed too loud at bad jokes and kept a photo of his daughters in his wallet." | | 8 | "And now Tomás Herrera — disgraced paramedic, associate of a group she was building a case against — had walked through a gate locked by something that wasn't a …" | | 9 | "She worked the tumblers with fingers that were steady despite the cold, despite the rain, despite the voice in her head that sounded like Morris telling her to …" | | 10 | "Somewhere below, the answers she'd been chasing for three years might be hiding in plain sight, disguised as the kind of place that shouldn't exist." | | 11 | "The light grew warmer, closer, and the walls of the stairwell began to change — the grime and water damage giving way to carved stone, to symbols she didn't rec…" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "the group she'd (would)" |
| | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |