| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 18 | | tagDensity | 0.556 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1429 | | 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) | |
| 51.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1429 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "streaming" | | 2 | "standard" | | 3 | "weight" | | 4 | "familiar" | | 5 | "chilling" | | 6 | "chaotic" | | 7 | "constructed" | | 8 | "dancing" | | 9 | "scanning" | | 10 | "velvet" | | 11 | "scanned" | | 12 | "silence" |
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| 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) | |
| 68.45% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 3 | | narrationSentences | 96 | | filterMatches | | | hedgeMatches | | 0 | "appeared to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1429 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1267 | | uniqueNames | 14 | | maxNameDensity | 0.95 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Tomás" | | discoveredNames | | London | 2 | | Harlow | 1 | | Quinn | 12 | | Tomás | 12 | | Herrera | 2 | | Tube | 1 | | Camden | 1 | | Morris | 4 | | Saint | 1 | | Christopher | 1 | | Internal | 1 | | Affairs | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Morris" | | 5 | "Saint" | | 6 | "Christopher" |
| | places | | | globalScore | 1 | | windowScore | 0.833 | |
| 56.25% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 80 | | glossingSentenceCount | 3 | | matches | | 0 | "seemed active now" | | 1 | "herbs that seemed to writhe in their packaging" | | 2 | "sounded like wind through dry leaves" |
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| 60.04% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.4 | | wordCount | 1429 | | matches | | 0 | "not the pitch black of a derelict tunnel, but a wash of unnatural, flickering light" | | 1 | "not out of respect, but out of a predatory curiosity" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 46.1 | | std | 25.06 | | cv | 0.544 | | sampleLengths | | 0 | 72 | | 1 | 94 | | 2 | 17 | | 3 | 103 | | 4 | 68 | | 5 | 65 | | 6 | 42 | | 7 | 53 | | 8 | 22 | | 9 | 42 | | 10 | 28 | | 11 | 36 | | 12 | 30 | | 13 | 7 | | 14 | 83 | | 15 | 63 | | 16 | 62 | | 17 | 36 | | 18 | 47 | | 19 | 6 | | 20 | 92 | | 21 | 54 | | 22 | 42 | | 23 | 11 | | 24 | 28 | | 25 | 30 | | 26 | 47 | | 27 | 26 | | 28 | 51 | | 29 | 21 | | 30 | 51 |
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| 86.99% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 96 | | matches | | 0 | "was plastered" | | 1 | "were chained" | | 2 | "was replaced" | | 3 | "was cracked" | | 4 | "been transformed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 212 | | matches | | 0 | "wasn't letting" | | 1 | "was chasing" | | 2 | "was speaking" |
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| 60.44% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 3 | | flaggedSentences | 3 | | totalSentences | 104 | | ratio | 0.029 | | matches | | 0 | "Detective Harlow Quinn didn't feel the cold biting through her coat; she only felt the burn in her lungs and the rhythmic thud of her boots against the wet concrete." | | 1 | "One moment, the roar of London traffic and the drumming rain filled her ears; the next, a hushed, chaotic murmur replaced it." | | 2 | "The hunt was no longer just about catching a suspect; it was about surviving a world that refused to acknowledge its own existence." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1272 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.02358490566037736 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.008647798742138365 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 13.74 | | std | 7.89 | | cv | 0.574 | | sampleLengths | | 0 | 18 | | 1 | 30 | | 2 | 21 | | 3 | 3 | | 4 | 18 | | 5 | 27 | | 6 | 17 | | 7 | 13 | | 8 | 19 | | 9 | 12 | | 10 | 5 | | 11 | 4 | | 12 | 23 | | 13 | 19 | | 14 | 4 | | 15 | 19 | | 16 | 25 | | 17 | 9 | | 18 | 9 | | 19 | 11 | | 20 | 6 | | 21 | 24 | | 22 | 14 | | 23 | 1 | | 24 | 1 | | 25 | 2 | | 26 | 24 | | 27 | 21 | | 28 | 20 | | 29 | 10 | | 30 | 9 | | 31 | 23 | | 32 | 8 | | 33 | 15 | | 34 | 30 | | 35 | 10 | | 36 | 12 | | 37 | 13 | | 38 | 20 | | 39 | 9 | | 40 | 11 | | 41 | 17 | | 42 | 13 | | 43 | 23 | | 44 | 10 | | 45 | 20 | | 46 | 7 | | 47 | 5 | | 48 | 11 | | 49 | 21 |
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| 60.58% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.4326923076923077 | | totalSentences | 104 | | uniqueOpeners | 45 | |
| 36.63% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 91 | | matches | | 0 | "Instead, he reached into his" |
| | ratio | 0.011 | |
| 74.95% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 91 | | matches | | 0 | "He slipped, his hand grazing" | | 1 | "She landed hard, the impact" | | 2 | "Her closely cropped salt-and-pepper hair" | | 3 | "she shouted, her voice raw" | | 4 | "He didn't look back." | | 5 | "She had seen the reports," | | 6 | "She had lost DS Morris" | | 7 | "She wasn't letting another suspect" | | 8 | "They were chained shut, or" | | 9 | "He didn't fumble for a" | | 10 | "He pressed the bone token" | | 11 | "His warm brown eyes locked" | | 12 | "she snapped, drawing her service" | | 13 | "he said, stepping backward into" | | 14 | "He turned and vanished into" | | 15 | "Her left wrist felt heavy," | | 16 | "They would call it obsession." | | 17 | "They would say she was" | | 18 | "She thought of Morris, of" | | 19 | "She thought of the look" |
| | ratio | 0.363 | |
| 20.44% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 80 | | totalSentences | 91 | | matches | | 0 | "Detective Harlow Quinn didn't feel" | | 1 | "Tonight, she pushed." | | 2 | "He slipped, his hand grazing" | | 3 | "Quinn vaulted the fence a" | | 4 | "She landed hard, the impact" | | 5 | "Her closely cropped salt-and-pepper hair" | | 6 | "she shouted, her voice raw" | | 7 | "He didn't look back." | | 8 | "Tomás darted into an alleyway" | | 9 | "The area was a graveyard" | | 10 | "She had seen the reports," | | 11 | "She had lost DS Morris" | | 12 | "She wasn't letting another suspect" | | 13 | "Tomás reached the heavy iron" | | 14 | "They were chained shut, or" | | 15 | "He didn't fumble for a" | | 16 | "He pressed the bone token" | | 17 | "The iron groaned, a sound" | | 18 | "The doors swung inward, revealing" | | 19 | "Quinn skidded to a halt" |
| | ratio | 0.879 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 91 | | matches | | 0 | "Even from twenty feet away," | | 1 | "If she walked away, the" |
| | ratio | 0.022 | |
| 2.55% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 11 | | matches | | 0 | "He slipped, his hand grazing the rusted metal, but recovered with a grace that spoke of survival instincts honed far beyond the NHS training he'd once possessed…" | | 1 | "She had lost DS Morris to one of those unsolvable anomalies three years ago, a gap in her memory that festered like an open wound." | | 2 | "Instead, he reached into his pocket, his fingers brushing the Saint Christopher medallion hidden beneath his shirt before pulling out a small, pale object." | | 3 | "The iron groaned, a sound like a dying animal, and the chains fell away as if severed by an invisible blade." | | 4 | "The weight of the gun in her hand was familiar, a grounding anchor in a world that felt increasingly unmoored." | | 5 | "Paperwork meant the file on DS Morris would be pulled out, dusted off, and picked apart by Internal Affairs who would ask why she was chasing a former paramedic…" | | 6 | "She thought of the look in his eyes the last time she saw him, a confusion that mirrored her own now." | | 7 | "Tomás Herrera was the closest link she had to the underworld that had swallowed her partner." | | 8 | "A man whose reflection didn't match his movements sold bundles of dried herbs that seemed to writhe in their packaging." | | 9 | "Quinn moved through the crowd, her bearing rigid, her eyes scanning for Tomás." | | 10 | "The hunt was no longer just about catching a suspect; it was about surviving a world that refused to acknowledge its own existence." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 4 | | matches | | 0 | "she shouted, her voice raw against the roar of the city" | | 1 | "Tomás said, his voice barely audible over the rain" | | 2 | "she called out, her voice cutting through the alien din" | | 3 | "she said, her voice low and steady" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 5 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "she snapped (snap)" | | 2 | "she called out (call out)" | | 3 | "he hissed (hiss)" | | 4 | "Tomás warned (warn)" |
| | dialogueSentences | 18 | | tagDensity | 0.556 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |