Run: 2026-07-25-01KYCPWA4A3K94R5D06PWDMYRW

Run Details

Duration:
55.4s
Cost:
$0.079025
Provider:
Amazon Bedrock

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<codex> <character id="4416" name="Detective Harlow Quinn" aliases="Quinn, Detective Quinn, Harlow" pronouns="she/her" species="Human" storyRole="Antagonist"> <eyeColor>brown</eyeColor> <hair>closely cropped salt-and-pepper</hair> <height>5'9"</height> <age>41</age> <jawline>sharp jaw</jawline> <watch>worn leather watch on her left wrist</watch> <bearing>military precision</bearing> <description>A Metropolitan Police detective with 18 years of decorated service who suspects the clique is involved in criminal activity.</description> <backstory>She lost her partner, DS Morris, during a case three years ago under unexplained circumstances that had supernatural origins she doesn't yet understand.</backstory> </character> <character id="4414" name="Eva Kowalski" aliases="Eva, Evie" pronouns="she/her" species="Human" storyRole="Best Friend"> <eyeColor>green</eyeColor> <hair>curly red</hair> <height>5'4"</height> <age>26</age> <glasses>round glasses</glasses> <satchel>worn leather satchel full of books</satchel> <freckles>freckled complexion</freckles> <nervousHabit>tucking hair behind her left ear</nervousHabit> <description>Aurora's childhood friend and an occult researcher.</description> <backstory>Moved to London two years before Aurora and works as a research assistant at the British Museum's restricted archives. She holds a master's degree in Ancient History from Oxford.</backstory> </character> <location id="856" name="The Veil Market" aliases="Veil Market, the Market, underground market" realm="Earth"> <currentLocation>abandoned Tube station beneath Camden</currentLocation> <entryRequirement>bone token</entryRequirement> <schedule>moves locations every full moon</schedule> <description>A hidden supernatural black market that sells enchanted goods, banned alchemical substances, and information.</description> </location> <item id="2004" name="Veil Compass" aliases="the Compass, shadow compass" type="Tool" origin="The Veil Market"> <casingMaterial>small brass compass</casingMaterial> <faceMarkings>face etched with protective sigils</faceMarkings> <needle>points toward the nearest supernatural rift or portal</needle> <patina>casing has a patina of verdigris</patina> <creator>crafted by a Shade artisan</creator> <description>A compass attuned to supernatural energy.</description> </item> </codex> Write a fully fleshed out scene of at least 1000 words in the mystery genre. A detective arrives at a crime scene in an unusual location. Something is wrong — the evidence doesn't add up. A colleague is present, offering a different interpretation. Through careful observation and deduction, the detective begins to see what others have missed. Use the codex entries above as your world reference for characters and setting. Only include the prose of the scene without any markdown or commentary.

Model response

AI
The service tunnel smelled of wet iron and old paper, and Detective Harlow Quinn had been in enough basements to know the difference between damp and something worse. She descended the maintenance stairs behind Camden Lock, one hand on the rail, the other holding her torch low so the beam wouldn't blind the constable coming up. Forty-one steps. She counted them out of habit, the way she counted exits in restaurants and cameras on high streets. At the bottom, the tunnel opened into a disused Northern Line platform that the maps in the Transport for London archive insisted had been sealed in 1961. The seal, apparently, had opinions. "Ma'am." PC Adeyemi stood at the tape with his notebook already open, which she appreciated. "Body's at the far end. Tiling's collapsed down there, so mind your footing." "Who called it in?" "Anonymous. Payphone on Chalk Farm Road — one of the three left in the borough. Male voice, thirty seconds, no name." "Time?" "Four-eighteen this morning." Quinn ducked under the tape. The platform stretched away into dark, its curved ceiling furred with a century of soot. Advertisements clung to the wall in fragments: a woman's hand holding a cigarette, half a word — CANNOT — the rest scaled away to plaster. Someone had rigged two work lamps on tripods and their glare made the shadows behind the pillars look solid, like things you could push against. There was a smell layered under the damp. Not decomposition. Something like a struck match, or ozone after a storm. "Quinn." Detective Sergeant Bell came up the platform toward her with his coat over his arm and his tie already loosened, a man who dressed for the office and kept getting sent to holes in the ground. "You'll love this. Male, forty to fifty, no ID, no phone, no keys. Cause of death looks like blunt trauma to the back of the skull. Body's cold, rigor's fully established, so we're talking twelve hours minimum. Blood's dry." "Where's the blood?" Bell stopped. "Where's the—" "You said blunt trauma to the skull. Where's the blood?" He gestured, vaguely triumphant. "Under him. Pooled." She walked past him. The man lay on his side ten feet from the tunnel mouth, one arm folded under his body, the other extended along the platform edge as if he had been reaching for something on the tracks. Grey trousers, good ones. A jumper worn thin at the elbows. Bare feet, and that was the first thing that snagged in Quinn's mind like wool on a nail. Bare feet on a filthy platform, and the soles were clean. Pale as candle wax and clean. She crouched. Her knees complained. Eighteen years and they'd started keeping a ledger. The blood was there, right enough — a dark halo spread beneath the head, dried to a matte crust that had cracked like riverbed mud. She shone the torch along its edge. Then she moved the torch slowly outward, tracing the shape of it, and the wrongness settled over her the way it always did: not as a thought but as a discomfort, a sound just outside hearing. "Bell. Come here and tell me what you see." He came, reluctant, and crouched beside her with a grunt. "Blood pool. Consistent with the wound." "How far from the wound?" "Six inches?" "Eight. And the pool is what, twenty inches across?" "Roughly." "Now look at the ceiling." Bell looked up. There was nothing there but soot and the ghost of a maintenance ladder bolted into the brick. "Nothing," he said. "That's my point." Quinn stood, sweeping the torch in a slow arc. "Blunt trauma to the back of the skull produces cast-off. It sprays. On the swing back, on the swing through. You get it on walls, ceilings, the assailant's cuffs. There is a pool of blood on this platform and there is no cast-off anywhere. Not on the pillar, not on the tiles, not on that advertisement." She let the beam rest on the smoking woman's hand. "It's as though someone poured it out of a jug." "Or he was hit somewhere else and moved." "Then the pool would be a transfer stain, not a pool. Blood doesn't keep flowing an hour after the heart stops, and it certainly doesn't gather itself into a neat circle to make our lives easier." She lowered the torch. "There's more. Where are the drag marks?" Bell shifted his weight. "It's dusty. Maybe the responding officers—" "There's forty years of dust on this platform, Bell. There are your footprints, mine, Adeyemi's, and three sets from the paramedics who came down and went straight back up. I counted." She turned in place. "There is not one mark leading to that body. No drag, no scuff, no heel-strike. He didn't walk here and nobody carried him. The dust around him is undisturbed within — what, three feet? Look at it. It's smooth as a duvet." Bell looked. She watched him look, watched the moment where the pattern resolved and he flinched from it, the way most people did. It was easier to believe in a sloppy assailant than in a body that had arrived without arriving. "So somebody swept," he said. "Brush, jacket, whatever. Covering their tracks." "Sweeping leaves striations. Come and see if you can find one." "Quinn—" "You know what I think? I think you want the whole thing to be Tuesday." She said it without heat. "Rough sleeper gets into a sealed station because someone's cut the grille again. Argument over a sleeping spot. Someone takes a length of pipe to him and legs it. That's a story you can write up in an hour, and every part of it is plausible, and none of it is what happened here." "It's a working theory." "It's a wish." She moved to the body's other side, careful of the collapsed tiling, and crouched again. The dead man's face was slack and unremarkable — a face you'd forget queuing behind it. But his eyes were open, and the whites had gone a faint, uniform grey, like milk stirred with ash. Quinn had seen a lot of dead eyes. She had never seen that. Her thumb found the face of her watch and rubbed it. Old habit. Three years old, precisely: the same gesture she'd made standing in a warehouse in Deptford with DS Morris's radio still crackling somewhere she couldn't find, in a room with no other doors. "Look at his hands," she said. Bell came around and looked. The dead man's extended hand was curled, and in the palm, pressed into the flesh, was a shape — a small circular impression, perhaps an inch and a half across, with a raised bar across the middle. It had bruised. Which meant he'd been gripping it hard while his heart still beat. "Held something," Bell said. "Coin?" "Too big. And there's no coin." She rose, and swept the torch along the platform edge, down onto the trackbed where the rails had been lifted and only the sleepers remained, black and rotten. "But there's an impression, which means the object was removed, which means someone was here after he died. And they came and went without touching the dust." "You're saying two people levitated." "I'm saying the dust is a fact and the pool is a fact and the grey in his eyes is a fact, and I'm not going to pretend they're not just because they don't fit your sleeping-spot theory." She straightened her coat. "Get SOCO down here and tell them I want the dust photographed before anyone else sets foot past that pillar. And I want that payphone's kiosk dusted, though I expect it'll be wiped." Bell held out for a moment. Then, quietly: "And what are you going to do?" Quinn looked down the tunnel mouth, where the work lamps couldn't reach and the darkness had that particular quality — not empty, but occupied — that she had been refusing to name for three years. "There's a girl at the British Museum," she said. "Restricted archives. Kowalski. Red hair, glasses, carries about nine stone of books wherever she goes." She clicked the torch off, and the tunnel breathed cold up at her. "She was standing in the crowd on Chalk Farm Road at half four this morning, according to Adeyemi, and she didn't stay to be interviewed. That's twice this month she's turned up where I'm standing." "That's not evidence." "No," Quinn agreed. "It's a pattern. Evidence is what you find after you stop arguing with the pattern." She went back up the forty-one steps into the grey of Camden morning, and she did not tell Bell that as she passed the tunnel mouth, the small hairs along her arms had risen — all of them, at once, as if something enormous had turned over in its sleep.
created_at"2026-07-25T13:19:21.231Z" 7/25/2026, 1:19:21 PM
model"anthropic/claude-opus-5-20260723"
app_id182717
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latency2312
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generation_time55296
tokens_prompt896
tokens_completion2123
native_tokens_prompt1285
native_tokens_completion2904
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native_tokens_reasoning0
native_tokens_cached0
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num_input_audio_prompt(null)
num_media_completion0
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origin"https://ncbench.com/"
is_byokfalse
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latency2312
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Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags16
adverbTagCount0
adverbTags(empty)
dialogueSentences52
tagDensity0.308
leniency0.615
rawRatio0
effectiveRatio0
93.18% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1467
totalAiIsmAdverbs2
found
0
adverb"slowly"
count1
1
adverb"precisely"
count1
highlights
0"slowly"
1"precisely"
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)
89.78% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1467
totalAiIsms3
found
0
word"tracing"
count1
1
word"weight"
count1
2
word"resolved"
count1
highlights
0"tracing"
1"weight"
2"resolved"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches0
maxInWindow0
found(empty)
highlights(empty)
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences67
matches(empty)
78.89% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount3
hedgeCount0
narrationSentences67
filterMatches
0"look"
1"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences102
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen68
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1477
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions17
unquotedAttributions0
matches(empty)
96.62% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions30
wordCount843
uniqueNames14
maxNameDensity1.07
worstName"Bell"
maxWindowNameDensity2
worstWindowName"Bell"
discoveredNames
Detective2
Harlow1
Quinn7
Camden2
Lock1
Northern1
Line1
Transport1
London1
Adeyemi1
Sergeant1
Bell9
Deptford1
Morris1
persons
0"Harlow"
1"Quinn"
2"Adeyemi"
3"Sergeant"
4"Bell"
5"Morris"
places
0"Transport"
1"London"
2"Deptford"
globalScore0.966
windowScore1
85.90% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences39
glossingSentenceCount1
matches
0"Something like a struck match, or ozone afte"
64.59% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches2
per1kWords1.354
wordCount1477
matches
0"not as a thought but as a discomfort, a sound just outside hearing"
1"not empty, but occupied"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences102
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs54
mean27.35
std28.08
cv1.026
sampleLengths
028
175
25
328
44
521
61
73
870
920
1076
113
124
1310
147
154
1682
1713
1868
199
2016
215
222
239
241
255
2620
273
2888
298
3047
3110
3277
3341
3411
3511
361
3774
384
393
4063
4145
426
4357
445
4561
465
4775
4815
4935
89.55% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences67
matches
0"been sealed"
1"was curled"
2"been lifted"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs130
matches(empty)
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount8
semicolonCount0
flaggedSentences6
totalSentences102
ratio0.059
matches
0"Advertisements clung to the wall in fragments: a woman's hand holding a cigarette, half a word — CANNOT — the rest scaled away to plaster."
1"The blood was there, right enough — a dark halo spread beneath the head, dried to a matte crust that had cracked like riverbed mud."
2"The dead man's face was slack and unremarkable — a face you'd forget queuing behind it."
3"The dead man's extended hand was curled, and in the palm, pressed into the flesh, was a shape — a small circular impression, perhaps an inch and a half across, with a raised bar across the middle."
4"Quinn looked down the tunnel mouth, where the work lamps couldn't reach and the darkness had that particular quality — not empty, but occupied — that she had been refusing to name for three years."
5"She went back up the forty-one steps into the grey of Camden morning, and she did not tell Bell that as she passed the tunnel mouth, the small hairs along her arms had risen — all of them, at once, as if something enormous had turned over in its sleep."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount837
adjectiveStacks0
stackExamples(empty)
adverbCount25
adverbRatio0.02986857825567503
lyAdverbCount6
lyAdverbRatio0.007168458781362007
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences102
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences102
mean14.48
std13.88
cv0.959
sampleLengths
028
128
22
318
427
55
615
713
84
921
101
113
125
1315
1425
1525
168
172
1810
1937
2039
213
222
232
2410
254
263
274
2836
294
307
3118
3211
336
342
353
368
3725
387
3936
409
4110
426
435
442
459
461
475
483
4917
86.93% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats3
diversityRatio0.5392156862745098
totalSentences102
uniqueOpeners55
61.73% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences54
matches
0"Then she moved the torch"
ratio0.019
64.44% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount21
totalSentences54
matches
0"She descended the maintenance stairs"
1"She counted them out of"
2"He gestured, vaguely triumphant."
3"She walked past him."
4"Her knees complained."
5"She shone the torch along"
6"He came, reluctant, and crouched"
7"She let the beam rest"
8"She lowered the torch"
9"She turned in place"
10"She watched him look, watched"
11"It was easier to believe"
12"She said it without heat"
13"She moved to the body's"
14"She had never seen that."
15"Her thumb found the face"
16"It had bruised."
17"She rose, and swept the"
18"She straightened her coat"
19"She clicked the torch off,"
ratio0.389
71.11% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount42
totalSentences54
matches
0"The service tunnel smelled of"
1"She descended the maintenance stairs"
2"She counted them out of"
3"The seal, apparently, had opinions."
4"PC Adeyemi stood at the"
5"Quinn ducked under the tape."
6"The platform stretched away into"
7"Advertisements clung to the wall"
8"Someone had rigged two work"
9"Something like a struck match,"
10"Detective Sergeant Bell came up"
11"He gestured, vaguely triumphant."
12"She walked past him."
13"The man lay on his"
14"A jumper worn thin at"
15"Her knees complained."
16"The blood was there, right"
17"She shone the torch along"
18"He came, reluctant, and crouched"
19"Bell looked up."
ratio0.778
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences54
matches(empty)
ratio0
87.91% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences26
technicalSentenceCount2
matches
0"The man lay on his side ten feet from the tunnel mouth, one arm folded under his body, the other extended along the platform edge as if he had been reaching for…"
1"She went back up the forty-one steps into the grey of Camden morning, and she did not tell Bell that as she passed the tunnel mouth, the small hairs along her a…"
93.75% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags16
uselessAdditionCount1
matches
0"She clicked, and the tunnel breathed cold up at her"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags7
fancyCount1
fancyTags
0"Quinn agreed (agree)"
dialogueSentences52
tagDensity0.135
leniency0.269
rawRatio0.143
effectiveRatio0.038
85.4794%