| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1518 | | totalAiIsmAdverbs | 1 | | 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) | |
| 60.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1518 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "flicker" | | 1 | "shattered" | | 2 | "glint" | | 3 | "charged" | | 4 | "footsteps" | | 5 | "echoed" | | 6 | "flickered" | | 7 | "electric" | | 8 | "throbbed" | | 9 | "streaming" | | 10 | "resolve" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 105 | | matches | (empty) | |
| 74.83% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 2 | | narrationSentences | 105 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 105 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1510 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 1510 | | uniqueNames | 12 | | maxNameDensity | 0.86 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 3 | | Harlow | 2 | | Quinn | 13 | | Morris | 6 | | London | 1 | | Herrera | 9 | | Tomás | 2 | | Christopher | 1 | | Market | 3 | | Tube | 1 | | Veil | 2 | | Detective | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Herrera" | | 4 | "Tomás" | | 5 | "Christopher" | | 6 | "Market" | | 7 | "Tube" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 58.54% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 82 | | glossingSentenceCount | 3 | | matches | | 0 | "felt like inviting history to repeat" | | 1 | "not quite human" | | 2 | "not quite resolve no matter how she focused" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1510 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 105 | | matches | | |
| 10.58% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 16 | | mean | 94.38 | | std | 17.65 | | cv | 0.187 | | sampleLengths | | 0 | 77 | | 1 | 111 | | 2 | 97 | | 3 | 119 | | 4 | 80 | | 5 | 111 | | 6 | 77 | | 7 | 85 | | 8 | 97 | | 9 | 61 | | 10 | 98 | | 11 | 98 | | 12 | 87 | | 13 | 128 | | 14 | 75 | | 15 | 109 |
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| 98.58% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 105 | | matches | | 0 | "was said" | | 1 | "been locked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 254 | | matches | | 0 | "was heading" | | 1 | "was descending" | | 2 | "was bleeding" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 2 | | flaggedSentences | 8 | | totalSentences | 105 | | ratio | 0.076 | | matches | | 0 | "The worn leather strap of her watch bit into her left wrist with every swing of her arm; she did not need to glance at it to feel the ragged minutes burning." | | 1 | "The man—Herrera, Tomás Herrera, former NHS, unlicensed cutter of last resort for people who preferred not to visit proper hospitals—cut left hard into a narrow passage between a shuttered bookshop and a kebab van whose grease-fogged windows glowed amber." | | 2 | "He had a pale scar running the length of his left forearm; she knew that scar from the photographs in the file, knife mark from an earlier life he preferred no one examine." | | 3 | "Emergency lighting—ancient fluorescent tubes that buzzed and flickered—cast everything in a sickly intermittent green." | | 4 | "Light spilled out—not electric, not entirely." | | 5 | "She checked her watch by force of habit—eleven forty-three—and felt the leather strap tug against skin gone clammy." | | 6 | "Figures moved between them—some human enough, some less so." | | 7 | "Whatever this place was—whatever it sold, whatever rules it ran on—she had come too far for Morris, too far for the empty places in the files, to turn now." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1536 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 56 | | adverbRatio | 0.036458333333333336 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.006510416666666667 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 105 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 105 | | mean | 14.38 | | std | 9.79 | | cv | 0.681 | | sampleLengths | | 0 | 21 | | 1 | 22 | | 2 | 34 | | 3 | 10 | | 4 | 13 | | 5 | 32 | | 6 | 26 | | 7 | 6 | | 8 | 18 | | 9 | 6 | | 10 | 39 | | 11 | 16 | | 12 | 18 | | 13 | 5 | | 14 | 19 | | 15 | 4 | | 16 | 36 | | 17 | 2 | | 18 | 7 | | 19 | 33 | | 20 | 22 | | 21 | 4 | | 22 | 5 | | 23 | 6 | | 24 | 21 | | 25 | 36 | | 26 | 7 | | 27 | 5 | | 28 | 11 | | 29 | 14 | | 30 | 37 | | 31 | 3 | | 32 | 10 | | 33 | 8 | | 34 | 37 | | 35 | 1 | | 36 | 1 | | 37 | 13 | | 38 | 14 | | 39 | 5 | | 40 | 13 | | 41 | 16 | | 42 | 8 | | 43 | 8 | | 44 | 6 | | 45 | 14 | | 46 | 3 | | 47 | 3 | | 48 | 20 | | 49 | 2 |
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| 75.24% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4857142857142857 | | totalSentences | 105 | | uniqueOpeners | 51 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 96 | | matches | | 0 | "Somewhere above, a train rumbled" | | 1 | "Then she was descending, shoulders" | | 2 | "Then she dropped onto the" |
| | ratio | 0.031 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 96 | | matches | | 0 | "Her closely cropped salt-and-pepper hair" | | 1 | "She caught herself with a" | | 2 | "He had a pale scar" | | 3 | "He vaulted a low railing" | | 4 | "Her shoulder clipped the railing." | | 5 | "He was heading for the" | | 6 | "She had read the fringe" | | 7 | "She had dismissed most of" | | 8 | "He slipped through like smoke." | | 9 | "He went left." | | 10 | "She went left." | | 11 | "He hit the opposite platform," | | 12 | "She checked her watch by" | | 13 | "Her brown eyes stayed fixed" | | 14 | "She could radio in." | | 15 | "She thought of Morris’s empty" | | 16 | "She thought of the ship-shape" | | 17 | "She vaulted the far platform" | | 18 | "Her bolt of salt-and-pepper hair" | | 19 | "He did not look back" |
| | ratio | 0.229 | |
| 64.17% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 96 | | matches | | 0 | "Detective Harlow Quinn drove through" | | 1 | "Her closely cropped salt-and-pepper hair" | | 2 | "Water streamed off her sharp" | | 3 | "The worn leather strap of" | | 4 | "DS Morris had taught her" | | 5 | "Morris had also died beneath" | | 6 | "Quinn did not believe in" | | 7 | "The man—Herrera, Tomás Herrera, former" | | 8 | "Quinn took the corner low," | | 9 | "She caught herself with a" | | 10 | "Rain hissed against her face." | | 11 | "Herrera glanced back once." | | 12 | "The irony was not lost" | | 13 | "He had a pale scar" | | 14 | "He vaulted a low railing" | | 15 | "Quinn vaulted after him." | | 16 | "Her shoulder clipped the railing." | | 17 | "Pain flared and she ignored" | | 18 | "The alley funnelled them toward" | | 19 | "The rain softened the city’s" |
| | ratio | 0.792 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 66 | | technicalSentenceCount | 11 | | matches | | 0 | "The man—Herrera, Tomás Herrera, former NHS, unlicensed cutter of last resort for people who preferred not to visit proper hospitals—cut left hard into a narrow …" | | 1 | "He vaulted a low railing without breaking stride and dropped into a service alley that smelled of rotten vegetables and wet cardboard." | | 2 | "The rain softened the city’s edges but sharpened sound: the slap of his trainers, the heavier thud of her own steel-toes, the distant wail of a siren that might…" | | 3 | "An abandoned station somewhere beneath the northern reaches of Camden, a place that moved or was said to move after every full moon, reachable only with a bone …" | | 4 | "Then she was descending, shoulders brushing damp walls that smelled of old piss and darker things." | | 5 | "Emergency lighting—ancient fluorescent tubes that buzzed and flickered—cast everything in a sickly intermittent green." | | 6 | "A warm, murmuring, gold-and-violet light that throbbed like a heartbeat." | | 7 | "Herrera was already across the tracks, leaping with the sure-footed ease of a man who had done this more than once." | | 8 | "The door began to swing shut behind him, leisurely, as if whatever waited inside knew she was there and wanted her to choose." | | 9 | "Call for backup that would arrive too late saying all the right phrases about securing the scene and leaving the weirdness to other departments that did not exi…" | | 10 | "A man with too many joints sold glass vials that glowed sickle-blue." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |