| 87.50% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "Mehta said carefully [carefully]" | | 1 | "She moved back [back]" |
| | dialogueSentences | 32 | | tagDensity | 0.406 | | leniency | 0.813 | | rawRatio | 0.154 | | effectiveRatio | 0.125 | |
| 67.86% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1400 | | totalAiIsmAdverbs | 9 | | found | | | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "carefully" | | 3 | "slightly" | | 4 | "precisely" | | 5 | "perfectly" |
| |
| 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) | |
| 78.57% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1400 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "shattered" | | 1 | "etched" | | 2 | "magnetic" | | 3 | "database" | | 4 | "resolved" |
| |
| 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 | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 72 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1408 | | 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 | 35 | | wordCount | 1059 | | uniqueNames | 11 | | maxNameDensity | 1.13 | | worstName | "Mehta" | | maxWindowNameDensity | 3 | | worstWindowName | "Mehta" | | discoveredNames | | Camden | 1 | | Quinn | 11 | | Tube | 1 | | Priya | 1 | | Mehta | 12 | | Scene | 1 | | Crime | 1 | | European | 1 | | Morris | 2 | | Thomas | 1 | | Vane | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Mehta" | | 2 | "Crime" | | 3 | "Morris" | | 4 | "Thomas" | | 5 | "Vane" |
| | places | (empty) | | globalScore | 0.933 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1408 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 114 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 29.33 | | std | 24.57 | | cv | 0.838 | | sampleLengths | | 0 | 64 | | 1 | 34 | | 2 | 36 | | 3 | 105 | | 4 | 56 | | 5 | 55 | | 6 | 3 | | 7 | 26 | | 8 | 44 | | 9 | 7 | | 10 | 32 | | 11 | 6 | | 12 | 5 | | 13 | 91 | | 14 | 40 | | 15 | 17 | | 16 | 44 | | 17 | 4 | | 18 | 34 | | 19 | 11 | | 20 | 10 | | 21 | 3 | | 22 | 9 | | 23 | 11 | | 24 | 5 | | 25 | 54 | | 26 | 8 | | 27 | 25 | | 28 | 72 | | 29 | 21 | | 30 | 2 | | 31 | 5 | | 32 | 45 | | 33 | 7 | | 34 | 11 | | 35 | 63 | | 36 | 10 | | 37 | 43 | | 38 | 5 | | 39 | 67 | | 40 | 12 | | 41 | 25 | | 42 | 7 | | 43 | 41 | | 44 | 25 | | 45 | 36 | | 46 | 27 | | 47 | 45 |
| |
| 86.99% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 96 | | matches | | 0 | "been decommissioned" | | 1 | "been photographed" | | 2 | "were stoppered" | | 3 | "were handwritten" | | 4 | "been flagged" | | 5 | "were angled" |
| |
| 49.34% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 177 | | matches | | 0 | "was spinning" | | 1 | "was pointing" | | 2 | "was opening" | | 3 | "was looking" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 114 | | ratio | 0.079 | | matches | | 0 | "The abandoned station smelled of wet concrete and something older — a mineral bitterness that caught at the back of the throat like pennies dissolving on the tongue." | | 1 | "At the far end, her colleague DS Priya Mehta crouched beside a collection of market stalls — or what remained of them." | | 2 | "Vane looked peaceful in the particular theatrical way that sometimes happened — eyes closed, expression slack rather than strained." | | 3 | "\"It's flagged at the station as a known location for — \" Mehta consulted her notebook — \"unlicensed trade in controlled substances. Vice has been trying to get a warrant for months.\"" | | 4 | "They were stoppered with wax, their contents dark — deep amber, near-black in some cases — and the labels, when she could read them, were handwritten in a script she didn't recognise." | | 5 | "Not like this — not a slow, deliberate rotation, tracking something as methodically as a clock hand." | | 6 | "She straightened and looked back at the body, then at the stalls, then at the platform entrance — the old passenger access, long bricked up, though someone had clearly removed a section of the brickwork recently." | | 7 | "Not merely clean — unmarked." | | 8 | "The direction it pointed had changed — and it was pointing now, she realised, directly at the bricked-up entrance." |
| |
| 95.23% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1056 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 48 | | adverbRatio | 0.045454545454545456 | | lyAdverbCount | 19 | | lyAdverbRatio | 0.017992424242424244 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 12.35 | | std | 10.76 | | cv | 0.872 | | sampleLengths | | 0 | 28 | | 1 | 19 | | 2 | 17 | | 3 | 23 | | 4 | 11 | | 5 | 9 | | 6 | 13 | | 7 | 14 | | 8 | 8 | | 9 | 8 | | 10 | 29 | | 11 | 8 | | 12 | 22 | | 13 | 9 | | 14 | 3 | | 15 | 18 | | 16 | 9 | | 17 | 15 | | 18 | 2 | | 19 | 2 | | 20 | 28 | | 21 | 13 | | 22 | 21 | | 23 | 21 | | 24 | 3 | | 25 | 19 | | 26 | 7 | | 27 | 8 | | 28 | 19 | | 29 | 4 | | 30 | 3 | | 31 | 10 | | 32 | 7 | | 33 | 32 | | 34 | 6 | | 35 | 5 | | 36 | 2 | | 37 | 16 | | 38 | 22 | | 39 | 6 | | 40 | 32 | | 41 | 6 | | 42 | 7 | | 43 | 4 | | 44 | 8 | | 45 | 15 | | 46 | 13 | | 47 | 17 | | 48 | 35 | | 49 | 3 |
| |
| 68.42% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.4473684210526316 | | totalSentences | 114 | | uniqueOpeners | 51 | |
| 41.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 80 | | matches | | 0 | "Then she put the notebook" |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 80 | | matches | | 0 | "She'd been on the job" | | 1 | "She was twelve years younger" | | 2 | "She walked slowly along the" | | 3 | "She looked at them without" | | 4 | "They were stoppered with wax," | | 5 | "She moved further along." | | 6 | "She stared at it." | | 7 | "It moved with what she" | | 8 | "she called, keeping her voice" | | 9 | "She straightened and looked back" | | 10 | "She said it aloud not" | | 11 | "She moved back toward the" | | 12 | "It had shifted its angle" | | 13 | "She went back to it," | | 14 | "She stood up very slowly." | | 15 | "She'd built her entire understanding" | | 16 | "She'd lost Morris to a" | | 17 | "she said, keeping her voice" | | 18 | "She turned to face Mehta" | | 19 | "She pulled a small notebook" |
| | ratio | 0.25 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 80 | | matches | | 0 | "The abandoned station smelled of" | | 1 | "Quinn descended the maintenance stairs" | | 2 | "She'd been on the job" | | 3 | "This one felt wrong in" | | 4 | "The call had come in" | | 5 | "A utility worker, rerouted to" | | 6 | "The Tube station had been" | | 7 | "That much she'd confirmed on" | | 8 | "The tiles on the curved" | | 9 | "The platform itself was perhaps" | | 10 | "Glass vials shattered." | | 11 | "The body lay between two" | | 12 | "The Scene of Crime officers" | | 13 | "Mehta stood as she approached," | | 14 | "She was twelve years younger" | | 15 | "Quinn crouched beside the body," | | 16 | "Vane looked peaceful in the" | | 17 | "Mehta consulted her notebook" | | 18 | "She walked slowly along the" | | 19 | "She looked at them without" |
| | ratio | 0.675 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 80 | | matches | | 0 | "Now, forty minutes later, Quinn" | | 1 | "If his heart had stopped," |
| | ratio | 0.025 | |
| 69.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 4 | | matches | | 0 | "The abandoned station smelled of wet concrete and something older — a mineral bitterness that caught at the back of the throat like pennies dissolving on the to…" | | 1 | "Near the far wall, almost beneath the platform's decorative tiling, she found something that hadn't been flagged." | | 2 | "She'd lost Morris to a case that had never resolved, never made sense no matter how many times she'd read back through her own notes, and she'd filed the cognit…" | | 3 | "Mehta was looking at her with an expression that was three-quarters concern and one quarter something more careful." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 32 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |